feat: SDK hook port — 19 Python hooks + installer + profile system#20
feat: SDK hook port — 19 Python hooks + installer + profile system#20
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New: behavioral_extractor.py - 12-archetype sentence-level extraction for actionable lesson descriptions - Replaces word-diff summaries with imperative instructions - Template-based with upgrade path for LLM refinement New: correction_patterns table (meta_rules_storage.py) - Cross-session pattern tracking with batch upsert - Graduation candidate query for repeated patterns Changed: _core.py - brain.correct() uses behavioral_extractor as primary extraction path - Falls back to keyword templates New: test_pipeline_e2e.py (12 tests) - Pattern tracking, correction logging, injection formatting - Cloud-dependent tests skip on CI 1699 tests passing, 0 failures. Co-Authored-By: Gradata <noreply@gradata.ai>
Use getattr() instead of direct attribute access for spawn_queue to satisfy Pyright's type narrowing after hasattr() check. Co-Authored-By: Gradata <noreply@gradata.ai>
…LI --profile flag Introduces the Python hook system foundation: - _profiles.py: MINIMAL/STANDARD/STRICT profile tiers - _base.py: shared run_hook protocol with profile gating - _installer.py: 17-hook registry with generate/install/uninstall/status - Refactors claude_code.py to delegate to _installer - Adds --profile flag to `gradata hooks install` - 18 new tests, 1712 total passing Co-Authored-By: Gradata <noreply@gradata.ai>
…e, refactor auto_correct Phase 2 of hook port: wire the learning loop into Claude Code hooks. - auto_correct.py: add HOOK_META + run_hook entry point (keeps all existing logic) - inject_brain_rules.py: SessionStart hook that parses lessons.md and injects top-10 graduated rules as <brain-rules> XML - session_close.py: Stop hook that emits SESSION_END event and runs graduation sweep - 9 new tests covering parsing, scoring, injection, and session close Co-Authored-By: Gradata <noreply@gradata.ai>
…ment Port secret-scan.js to Python, add config file protection, and inject RULE-tier lessons before edits. All three are PreToolUse blocking hooks. 14 tests covering all paths. Co-Authored-By: Gradata <noreply@gradata.ai>
…ICT profiles) STANDARD: agent_precontext, agent_graduation, tool_failure_emit, tool_finding_capture, context_inject, config_validate, pre_compact. STRICT: duplicate_guard, brain_maintain, session_persist, implicit_feedback. 34 tests covering all hooks (happy path + no-op). Co-Authored-By: Gradata <noreply@gradata.ai>
…ib SequenceMatcher - Extract resolve_brain_dir() and extract_message() into _base.py, replacing 11 duplicate inline implementations - Replace inline RULE_RE parsers in inject_brain_rules, rule_enforcement, agent_precontext with self_improvement.parse_lessons() - Delete dead FAILURE_PATTERNS list from tool_finding_capture.py - Replace custom _levenshtein() with difflib.SequenceMatcher in duplicate_guard.py - Net reduction: ~127 lines removed across 14 hook files Co-Authored-By: Gradata <noreply@gradata.ai>
…nsolidate brain dir - Remove redundant tool_name check in secret_scan (matcher handles it) - Fix overly broad except (json.JSONDecodeError, Exception) to except Exception - Remove dead _HOOK_NAME, _HOOK_CONFIG, _load_settings, _save_settings from claude_code.py - Use resolve_brain_dir() in claude_code.py capture_correction() - Remove unused os/Path imports from claude_code.py - Remove unnecessary comment in _installer.py Co-Authored-By: Gradata <noreply@gradata.ai>
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📝 WalkthroughWalkthroughThis PR introduces a comprehensive hook system for Claude Code integration, including profile-based hook management infrastructure, 13+ hook modules for safety/learning/intelligence/lifecycle operations, rule integrity verification with canary promotions, and enhancements to behavioral extraction and meta-rules storage. Changes
Sequence Diagram(s)sequenceDiagram
participant CLI as CLI<br/>(install cmd)
participant Installer as Hook<br/>Installer
participant SettingsFile as ~/.claude/<br/>settings.json
participant Runtime as Hook<br/>Runtime
participant Handler as Hook<br/>Handler
participant EventSys as Event<br/>System
CLI->>Installer: install(profile="standard")
Installer->>SettingsFile: Load existing settings
Installer->>Installer: Filter registry by profile
Installer->>Installer: Generate hook configs
Installer->>SettingsFile: Save updated settings
Note over Runtime: Later, during Claude Code execution
Runtime->>Runtime: Read GRADATA_HOOK_PROFILE env
Runtime->>Runtime: Match event trigger
Runtime->>Runtime: Check profile tier (>=)
Runtime->>Runtime: Read stdin/payload
Runtime->>Handler: Call main(data)
Handler->>Handler: Process logic
opt Handler emits event
Handler->>EventSys: emit(event_type, payload, ctx)
EventSys->>EventSys: Store/broadcast
end
Handler-->>Runtime: Return result dict or None
Runtime->>Runtime: Print JSON output if truthy
Runtime->>Runtime: Suppress & log exceptions
Estimated code review effort🎯 4 (Complex) | ⏱️ ~60 minutes Possibly related PRs
Suggested labels
✨ Finishing Touches🧪 Generate unit tests (beta)
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⚠️ Outside diff range comments (2)
tests/test_core_behavioral.py (1)
23-26:⚠️ Potential issue | 🟠 MajorThese tests can pass without proving the new/fallback descriptions were written.
Both tests skip all assertions when
lessons.mdis missing, and the fallback case only checks for"INSTINCT"/"PATTERN", which is true for any created lesson. Addassert lessons_path.exists()and make the fallback path assert a specific description—ideally by patchinggradata.enhancements.edit_classifier.extract_behavioral_instructionand verifying that its return value is what lands in the file.As per coding guidelines,
tests/**: Test files. Verify: no hardcoded paths, assertions check specific values not just truthiness.Also applies to: 29-44
🤖 Prompt for AI Agents
Verify each finding against the current code and only fix it if needed. In `@tests/test_core_behavioral.py` around lines 23 - 26, Add an explicit existence check and deterministic assertion for the fallback description: assert lessons_path.exists() before reading, and in the fallback branch replace the loose check for "INSTINCT"/"PATTERN" with a specific expected string by patching gradata.enhancements.edit_classifier.extract_behavioral_instruction to return a known description, then assert that exact string appears in content; reference the test variable lessons_path and the function extract_behavioral_instruction when making the changes.src/gradata/hooks/claude_code.py (1)
54-55:⚠️ Potential issue | 🟡 MinorRemove unused statement.
The result of
payload.get("tool_output", "")is never used.🧹 Proposed fix
# Extract draft (old content) and final (new content) from tool input/output tool_input = payload.get("tool_input", {}) - payload.get("tool_output", "")🤖 Prompt for AI Agents
Verify each finding against the current code and only fix it if needed. In `@src/gradata/hooks/claude_code.py` around lines 54 - 55, The statement payload.get("tool_output", "") is unused in the claude_code hook; either remove this dangling call or assign it to a meaningful variable (e.g., tool_output) if the value is required later. Edit the code in src/gradata/hooks/claude_code.py around the lines where tool_input = payload.get("tool_input", {}) is set and remove the unnecessary payload.get("tool_output", "") expression or replace it with a proper variable reference used by subsequent logic (refer to the tool_input assignment and any downstream use of tool_output).
🤖 Prompt for all review comments with AI agents
Verify each finding against the current code and only fix it if needed.
Inline comments:
In `@src/gradata/_core.py`:
- Around line 233-249: extract_instruction() can return generic category
strings, causing the if not behavioral_desc check to skip
extract_behavioral_instruction(); change the logic so the keyword-template
fallback always runs when extract_instruction only returned a generic/category
fallback: after calling extract_instruction(draft, final, primary, category=cat)
detect a generic fallback (e.g., behavioral_desc == cat or matches the known
generic tokens) or change extract_instruction to return metadata like
(behavioral_desc, was_fallback) and then call
extract_behavioral_instruction(diff, primary, cache=brain._instruction_cache)
whenever the extractor indicated it produced only a generic/category result;
ensure you still initialize brain._instruction_cache via InstructionCache when
needed.
In `@src/gradata/enhancements/behavioral_extractor.py`:
- Around line 409-413: The _is_actionable guard is too strict and causes valid
explicit edits (e.g., "User corrected: Prioritize ROI...") to be rejected;
update _is_actionable (used by extract_instruction) to not block or to be
bypassed for Archetype.PREFIX_INSTRUCTION and similar explicit archetypes, or
broaden its check to accept any instruction that begins with an explicit prefix
keyword (e.g., "user corrected", "user instruction", "note:", "user:", etc.) or
contains a clear imperative verb pattern; locate _is_actionable in
src/gradata/enhancements/behavioral_extractor.py and either add a fast-path that
returns True when the calling context/archetype is PREFIX_INSTRUCTION (and the
instruction contains a non-empty body) or expand the allowed-starts logic used
by first_word in that function (and the analogous logic referenced in the block
around lines 460-478) so explicit user-prefixed instructions are preserved
rather than sent to the generic fallback.
- Around line 199-217: The current checks for removed_hedges and new_constraints
use raw substring membership against draft/final which falsely matches inside
other words; update the matching in the block that computes removed_hedges and
new_constraints to perform boundary-aware matching: for each term in
_HEDGE_PHRASES and _CONSTRAINT_WORDS, if the term is a single word use a regex
with word boundaries (e.g., \bterm\b) or tokenized comparison against
draft.lower()/final.lower(), and for multi-word phrases keep the existing
substring check; leave the rest of the flow (returning ArchetypeMatch for
Archetype.REMOVAL_HEDGING and Archetype.CONSTRAINT_ADDITION, and using
_find_sentence_containing) unchanged so only true word matches populate
removed_hedges and new_constraints.
In `@src/gradata/enhancements/meta_rules_storage.py`:
- Around line 448-458: The query in query_graduation_candidates() groups by
pattern_hash but returns non-aggregated category and representative_text,
causing nondeterministic values; fix it by selecting those fields
deterministically — e.g., choose the row with the earliest (or latest)
created_at per pattern_hash and join its category and representative_text into
the grouped result, or alternatively aggregate category/representative_text with
a deterministic aggregate (MIN/MAX) or use an explicit GROUP BY that includes
them; update the SQL in query_graduation_candidates() to return category and
representative_text via that deterministic selection so graduated candidates are
stable.
In `@src/gradata/hooks/_base.py`:
- Around line 66-77: Add a return type annotation to get_brain indicating it
returns Optional[Brain] (i.e., Brain | None) and remove the redundant
Path(brain_dir).exists() conditional — rely on resolve_brain_dir()'s guarantee
that a non-None brain_dir exists; import Optional (or use union annotation) and
construct and return Brain(brain_dir) inside the try/except, keeping the same
ImportError and broad Exception handling behavior.
- Around line 80-93: The run_hook function currently swallows all exceptions
with a bare except/pass; update it to log suppressed exceptions at DEBUG level
without changing behavior: ensure a module logger (logging.getLogger(__name__))
is available or imported, and replace the final except block with a logger.debug
call that includes the exception info (e.g., logger.debug("run_hook suppressed
exception in main_fn", exc_info=True)) so the hook remains silent to users but
records details for troubleshooting; keep the function signature and not
re-raising the exception.
In `@src/gradata/hooks/_installer.py`:
- Around line 80-83: The _load_settings function currently calls json.loads on
SETTINGS_PATH.read_text which will raise on invalid JSON; update _load_settings
to catch json.JSONDecodeError (and optionally ValueError for older Python), and
handle IO errors: on JSON parse failure return an empty dict (and optionally log
or warn about corrupted settings.json) so the application continues; ensure you
reference SETTINGS_PATH and _load_settings when adding the try/except around the
json.loads call.
In `@src/gradata/hooks/agent_graduation.py`:
- Around line 36-48: The emit(...) calls in agent_graduation.py (and the same
pattern in implicit_feedback.py, tool_failure_emit.py, session_close.py) are
passing an unsupported brain_dir keyword which causes a TypeError and prevents
the AGENT_OUTCOME (and related) events from emitting; remove the
brain_dir=brain_dir argument from the emit(...) invocation(s) in those files
and, if the brain_dir value is needed by listeners, include it inside the data
dict (e.g., data={"agent_type": ..., "output_preview": preview, "output_length":
len(output), "brain_dir": brain_dir}) instead of as a separate parameter so
emit(...) is called with only supported args.
In `@src/gradata/hooks/agent_precontext.py`:
- Around line 76-86: Rename the ambiguous comprehension variable `l` to `lesson`
in the filtered list comprehension so it's clear and not confusable with `1` or
`I`; specifically change the comprehension that builds `filtered` (currently
using `l for l in all_lessons`) to use `lesson for lesson in all_lessons`,
leaving downstream code that references `filtered`, `_infer_agent_type`,
`_relevance_score`, `MAX_RULES`, and the `for r in top` loop unchanged.
In `@src/gradata/hooks/brain_maintain.py`:
- Around line 16-46: _rebuild_fts and _generate_manifest are using the resolved
brain_dir but calling fts_index, generate_manifest and write_manifest without a
BrainContext, which falls back to global paths; fix by threading the resolved
BrainContext into those calls: in _rebuild_fts construct or accept the
BrainContext for brain_dir and call fts_index(..., ctx=ctx) (or pass the context
parameter name the function expects) for each file, and in _generate_manifest
call generate_manifest(ctx) and write_manifest(manifest, ctx) (or the
context/brain_dir parameter those functions accept) so all DB/manifest
operations use the supplied brain_dir rather than global defaults.
In `@src/gradata/hooks/config_validate.py`:
- Around line 43-63: The loop currently reads command from the outer group dict
(hook.get("command")) and only matches the literal "python -m gradata.hooks.",
so update the validation to iterate the nested hook entries (the inner list at
hook.get("hooks") or similar) and pull the "command" from each inner hook dict;
change the matcher to look for the "-m gradata.hooks." pattern (or use a regex
like r"-m\s+gradata\.hooks\.(\w+)") to accept a sys.executable prefix, extract
module_name from the substring after "gradata.hooks.", and then keep the
existing import gradata.hooks, hooks_dir resolution and module_path.is_file()
check to append the warning when the referenced module file is missing (adjust
variable names: hooks, hook_list, hook -> inner_hooks, inner_hook or similar to
locate the code).
In `@src/gradata/hooks/context_inject.py`:
- Around line 41-54: The join separator "\n---\n" (5 chars) isn't counted in the
MAX_CONTEXT_LEN budget, so joined can exceed the limit; update the selection
logic in the loop that builds context_parts/total_len (iterate over results,
compute snippet) to account for the separator length when testing the budget and
when incrementing total_len — e.g., compute sep_len = len("\n---\n") and use
total_len + (sep_len if context_parts else 0) + len(snippet) > MAX_CONTEXT_LEN
for the break condition, and add sep_len to total_len when appending subsequent
snippets so joined will never exceed MAX_CONTEXT_LEN.
In `@src/gradata/hooks/duplicate_guard.py`:
- Around line 91-101: The project-root detection fails for relative file_path
because p starts from a non-resolved Path and never checks ./ .git; update the
logic in duplicate_guard.py so project_root detection uses an absolute/resolved
path before walking up: when CLAUDE_PROJECT_DIR is unset, set p =
Path(file_path).resolve().parent (or resolve only when file_path is relative
using Path.cwd()), then walk up checking (p / ".git").exists() as before and set
project_root accordingly; this ensures ./ .git is considered and prevents
silently returning None for relative write targets.
In `@src/gradata/hooks/implicit_feedback.py`:
- Around line 83-96: The call to emit(...) in the implicit_feedback hook passes
an invalid brain_dir kwarg causing a TypeError and silently swallowing the
event; update the emit call in src/gradata/hooks/implicit_feedback.py (the try
block using emit("IMPLICIT_FEEDBACK", ...)) to remove the brain_dir keyword or,
if brain directory context is required, construct a BrainContext and pass it via
ctx=BrainContext(...) to emit; ensure you import or reference BrainContext from
gradata._events (or its module) and pass only supported kwargs to emit to avoid
the TypeError.
In `@src/gradata/hooks/inject_brain_rules.py`:
- Around line 52-54: Replace the explicit loop that builds the lines list with a
list comprehension to be more idiomatic: in the block where scored is iterated
(the loop that appends to lines using f"[{r.state.name}:{r.confidence:.2f}]
{r.category}: {r.description}"), change construction of lines to a single list
comprehension assigned to lines (preserving the same formatting and using the
same r attributes); this occurs inside the inject_brain_rules hook where the
variable scored is processed.
- Line 46: The list comprehension uses an ambiguous single-letter loop variable
`l`; rename it to a descriptive name like `lesson` in the comprehension
(filtered = [lesson for lesson in all_lessons if lesson.state.name in ("RULE",
"PATTERN") and lesson.confidence >= MIN_CONFIDENCE]) and update any subsequent
references in the same function/block that assume `l` to use `lesson` instead
(e.g., any processing of items from `filtered` inside inject_brain_rules or
related helper functions).
- Around line 22-29: The _score function contains a redundant conditional for
computing state_str and a hardcoded confidence threshold; simplify by removing
the useless isinstance branch and just assign state_str = state (after
retrieving state as you already do), and replace the magic number 0.6 with the
module constant MIN_CONFIDENCE and the corresponding denominator (1 -
MIN_CONFIDENCE) when computing conf_norm; update references inside _score
(lesson, conf, state, state_str, conf_norm) accordingly and ensure
MIN_CONFIDENCE is imported or defined in the module.
In `@src/gradata/hooks/pre_compact.py`:
- Around line 63-64: The snapshot is being written to a global temp filename
using tempfile.gettempdir() and a fixed name (snapshot_path), which can cause
cross-user/project conflicts; change the logic that computes snapshot_path in
pre_compact.py (where snapshot_path is set) to create a Gradata-owned per-user
temp subdirectory (e.g., under tempfile.gettempdir()/gradata/<username or uid>)
and append a brain/session-specific suffix (e.g., include session id or brain
id) to the file name instead of the hardcoded "gradata-compact-snapshot.json",
ensure the directory is created with safe permissions before writing and
continue to use Path(...).write_text to write the JSON.
In `@src/gradata/hooks/rule_enforcement.py`:
- Around line 36-45: Rename the ambiguous loop variable `l` to `lesson` in both
the list comprehension and the for-loop to avoid confusion and Ruff E741;
specifically update the list comprehension that builds rule_lessons (currently
using `l`) and the for loop that iterates rule_lessons[:MAX_REMINDERS],
replacing `l` with `lesson` and update all uses inside the loop
(`l.description`, `l.confidence`, `l.category`) to `lesson.description`,
`lesson.confidence`, `lesson.category`.
In `@src/gradata/hooks/session_close.py`:
- Around line 13-18: _emit_session_end currently tries to import a non-existent
EventType and calls emit with an invalid brain_dir kwarg; update the function to
import only emit from gradata._events, call emit with the string event name
"SESSION_END" (not EventType) and remove the brain_dir keyword, instead include
the brain_dir value inside the data dict (e.g. data={"brain_dir": brain_dir}),
and keep the try/except as-is so missing imports don't crash.
- Around line 21-26: The _run_graduation function imports and calls a
non-existent graduation_sweep from gradata.enhancements.self_improvement; remove
the import and call to graduation_sweep or, if the intent was to trigger
existing graduation logic, replace it with a call to graduate(...) (or another
appropriate function such as compute_learning_velocity or propagate_confidence)
from gradata.enhancements.self_improvement and adjust arguments accordingly;
ensure ImportError is not silently masked by the blanket try/except so real
failures surface.
In `@src/gradata/hooks/session_persist.py`:
- Around line 39-46: The current subprocess.run call that executes ["git",
"diff", "--name-only", "HEAD"] under the try block only returns tracked diffs;
change it so untracked files are included by either running ["git", "status",
"--porcelain", "--untracked-files=all"] and parsing each line's path (strip
leading two-char status codes and whitespace) or by combining results of the
existing git diff with ["git", "ls-files", "--others", "--exclude-standard"] and
merging unique file paths; keep using subprocess.run (same timeout, cwd,
capture_output, text), check result.returncode, and return a deduplicated list
of stripped file paths in place of the current list comprehension that assumes
git diff output.
In `@src/gradata/hooks/tool_failure_emit.py`:
- Around line 74-88: The emit call in tool_failure_emit.py passes an unsupported
keyword brain_dir to emit (see the emit(...) invocation inside the try block),
which will raise a TypeError and is then silently ignored by the bare except;
remove the brain_dir=brain_dir argument from the emit(...) call so it matches
emit's signature (keep the event name "TOOL_FAILURE", source, and data payload
intact) and replace the bare except with a minimal handled exception (e.g., log
or re-raise) if you want visibility, but the immediate fix is to delete the
brain_dir kwarg from the emit call.
In `@src/gradata/hooks/tool_finding_capture.py`:
- Around line 103-109: The current substring check (if file_basename in f or f
in file_path) causes false matches; change the matching in the loop over
finding.get("files", []) to either (a) compare exact basenames (Path(f).name ==
file_basename) or (b) compare normalized path suffixes by normalizing both sides
(resolve/normalize to POSIX, strip leading ./) and using endswith on the full
path (normalized_file_path.endswith(normalized_f)). Update the condition that
triggers _save_findings([]) and the return to use one of these stricter checks
to avoid substring matches.
- Line 19: FINDINGS_FILE is currently a single global temp file which allows
cross-user/repo collisions; change the constant to create a namespaced per-user
(and per-project/session) path inside the temp dir instead of
"gradata-findings.json". Use tempfile.gettempdir() as the base but join a
subdirectory (e.g. "gradata/<username>/<project_or_repo_name>") and include a
session-unique suffix (pid, timestamp, or random token) so files don't collide;
update the FINDINGS_FILE constant initialization to compute that Path using
getpass.getuser() (or os.getuid()) and the repo/project id (cwd name or git repo
name) and ensure no hardcoded absolute paths are used.
In `@tests/test_hooks_base.py`:
- Around line 14-20: Combine and parametrize the profile value assertions by
changing the test_profile_values to use pytest.mark.parametrize so it iterates
over (Profile.MINIMAL, Profile.STANDARD, Profile.STRICT) with expected values
0,1,2 respectively; keep test_profile_ordering as-is to assert Profile.MINIMAL <
Profile.STANDARD < Profile.STRICT and reference the Profile enum and
test_profile_values/test_profile_ordering names when implementing the change.
In `@tests/test_hooks_intelligence.py`:
- Around line 127-144: The test test_finding_capture_stores_test_failure
manipulates the module-level FINDINGS_FILE directly which risks cross-test
interference; introduce a pytest fixture (e.g., clean_findings) that ensures
FINDINGS_FILE is removed before the test yields and removed again after the test
to guarantee cleanup, then apply this fixture to
test_finding_capture_stores_test_failure and remove the manual setup/teardown
code in the test body so all create/delete happens in the fixture.
- Line 54: The generator in the assertion uses an ambiguous loop variable name
`l`; rename it to a clearer identifier (e.g., `line` or `entry`) in the
assertion inside tests/test_hooks_intelligence.py so it reads like any("SALES"
in line for line in lines), updating the variable consistently in that
expression to improve readability and avoid confusion with the number 1 or other
identifiers.
- Around line 62-73: The test test_agent_graduation_emits_event uses two nested
context managers; combine them into a single with statement to improve
readability by opening both patches together (patch.dict(os.environ,
{"GRADATA_BRAIN_DIR": str(tmp_path)}) and patch("gradata._events.emit") as
mock_emit) while keeping the call to graduation_main(...) and subsequent
assertions (result is None, mock_emit.assert_called_once(), and checking
call_kwargs[0][0] == "AGENT_OUTCOME") unchanged.
In `@tests/test_hooks_learning.py`:
- Around line 22-24: The test currently asserts floating-point equality on
rules_and_patterns[0].confidence; change this to use pytest.approx to avoid
brittle direct float comparison and follow tests/** guidelines—import pytest if
not present and replace the assert rules_and_patterns[0].confidence == 0.92 with
an assertion using pytest.approx(0.92) while leaving the other state.name
assertions intact.
In `@tests/test_pipeline_e2e.py`:
- Around line 164-167: The test assumes metas[0].context_weights has
non-"default" entries but will crash if it doesn't; update the assertion to
first extract non-default items from metas[0].context_weights (e.g., filter keys
!= "default"), handle the empty case by using a sensible fallback (like the
"default" weight or 0.0) before calling max, and then assert that the computed
task_type_weight is >= 1.5; refer to the variables metas, context_weights,
weights, and task_type_weight when locating and updating the logic.
- Line 93: The list comprehension uses an ambiguous single-letter loop variable
`l`; rename it to a descriptive name like `lesson` in the expression
process_lessons = [lesson for lesson in lessons if lesson.category == "PROCESS"]
and update any surrounding references (e.g., other comprehensions or usages in
tests/test_pipeline_e2e.py) to use `lesson` instead of `l` to avoid confusion
with `1` or `I`.
- Around line 22-25: The code currently sets _cloud_path with a hardcoded
Windows path; change the logic in the try block so _cloud_path is derived from
the environment only (os.environ["GRADATA_CLOUD_PATH"]) or, if you need a
fallback, compute a repo-relative path using the current file directory (e.g.,
based on os.path.dirname(__file__) and join up to the cloud folder) instead of
"C:/Users/…"; then use that _cloud_path when calling sys.path.insert and
importing meta_rules (refer to the _cloud_path variable, sys.path.insert(0,
_cloud_path), and the import of discover_meta_rules and merge_into_meta) so
tests no longer rely on a hardcoded Windows-specific path.
- Around line 219-227: The loop uses an ambiguous variable name `l`; rename it
to a descriptive name like `lesson` in the loop that builds `promoted` (for
lesson in lessons) and update all references inside the loop (`l.category`,
`l.date`, `l.description`) to `lesson.category`, `lesson.date`,
`lesson.description` so readability is improved while preserving the behavior
that constructs Lesson(...) with LessonState.RULE for PROCESS-category items and
appends the original lesson otherwise.
---
Outside diff comments:
In `@src/gradata/hooks/claude_code.py`:
- Around line 54-55: The statement payload.get("tool_output", "") is unused in
the claude_code hook; either remove this dangling call or assign it to a
meaningful variable (e.g., tool_output) if the value is required later. Edit the
code in src/gradata/hooks/claude_code.py around the lines where tool_input =
payload.get("tool_input", {}) is set and remove the unnecessary
payload.get("tool_output", "") expression or replace it with a proper variable
reference used by subsequent logic (refer to the tool_input assignment and any
downstream use of tool_output).
In `@tests/test_core_behavioral.py`:
- Around line 23-26: Add an explicit existence check and deterministic assertion
for the fallback description: assert lessons_path.exists() before reading, and
in the fallback branch replace the loose check for "INSTINCT"/"PATTERN" with a
specific expected string by patching
gradata.enhancements.edit_classifier.extract_behavioral_instruction to return a
known description, then assert that exact string appears in content; reference
the test variable lessons_path and the function extract_behavioral_instruction
when making the changes.
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📒 Files selected for processing (36)
src/gradata/_core.pysrc/gradata/cli.pysrc/gradata/contrib/patterns/orchestrator.pysrc/gradata/enhancements/behavioral_extractor.pysrc/gradata/enhancements/meta_rules_storage.pysrc/gradata/hooks/_base.pysrc/gradata/hooks/_installer.pysrc/gradata/hooks/_profiles.pysrc/gradata/hooks/agent_graduation.pysrc/gradata/hooks/agent_precontext.pysrc/gradata/hooks/auto_correct.pysrc/gradata/hooks/brain_maintain.pysrc/gradata/hooks/claude_code.pysrc/gradata/hooks/config_protection.pysrc/gradata/hooks/config_validate.pysrc/gradata/hooks/context_inject.pysrc/gradata/hooks/duplicate_guard.pysrc/gradata/hooks/implicit_feedback.pysrc/gradata/hooks/inject-brain-rules.jssrc/gradata/hooks/inject_brain_rules.pysrc/gradata/hooks/pre_compact.pysrc/gradata/hooks/rule_enforcement.pysrc/gradata/hooks/secret_scan.pysrc/gradata/hooks/session-history-sync.jssrc/gradata/hooks/session_close.pysrc/gradata/hooks/session_persist.pysrc/gradata/hooks/tool-finding-capture.jssrc/gradata/hooks/tool_failure_emit.pysrc/gradata/hooks/tool_finding_capture.pytests/test_convergence_gate.pytests/test_core_behavioral.pytests/test_hooks_base.pytests/test_hooks_intelligence.pytests/test_hooks_learning.pytests/test_hooks_safety.pytests/test_pipeline_e2e.py
💤 Files with no reviewable changes (3)
- src/gradata/hooks/tool-finding-capture.js
- src/gradata/hooks/inject-brain-rules.js
- src/gradata/hooks/session-history-sync.js
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📓 Path-based instructions (3)
tests/**
⚙️ CodeRabbit configuration file
tests/**: Test files. Verify: no hardcoded paths, assertions check specific values not just truthiness,
parametrized tests preferred for boundary conditions, floating point comparisons use pytest.approx.
Files:
tests/test_core_behavioral.pytests/test_convergence_gate.pytests/test_hooks_learning.pytests/test_hooks_base.pytests/test_hooks_safety.pytests/test_pipeline_e2e.pytests/test_hooks_intelligence.py
src/gradata/**/*.py
⚙️ CodeRabbit configuration file
src/gradata/**/*.py: This is the core SDK. Check for: type safety (from future import annotations required), no print()
statements (use logging), all functions accepting BrainContext where DB access occurs, no hardcoded paths. Severity
scoring must clamp to [0,1]. Confidence values must be in [0.0, 1.0].
Files:
src/gradata/contrib/patterns/orchestrator.pysrc/gradata/cli.pysrc/gradata/hooks/_profiles.pysrc/gradata/hooks/auto_correct.pysrc/gradata/hooks/tool_failure_emit.pysrc/gradata/hooks/implicit_feedback.pysrc/gradata/_core.pysrc/gradata/hooks/agent_precontext.pysrc/gradata/hooks/rule_enforcement.pysrc/gradata/hooks/session_close.pysrc/gradata/hooks/pre_compact.pysrc/gradata/hooks/tool_finding_capture.pysrc/gradata/hooks/config_validate.pysrc/gradata/hooks/brain_maintain.pysrc/gradata/hooks/session_persist.pysrc/gradata/hooks/duplicate_guard.pysrc/gradata/hooks/context_inject.pysrc/gradata/hooks/claude_code.pysrc/gradata/hooks/inject_brain_rules.pysrc/gradata/enhancements/meta_rules_storage.pysrc/gradata/hooks/_base.pysrc/gradata/enhancements/behavioral_extractor.pysrc/gradata/hooks/config_protection.pysrc/gradata/hooks/_installer.pysrc/gradata/hooks/agent_graduation.pysrc/gradata/hooks/secret_scan.py
src/gradata/hooks/**
⚙️ CodeRabbit configuration file
src/gradata/hooks/**: JavaScript hooks for Claude Code integration. Check for: no shell injection (no execSync with user
input), temp files must use per-user subdirectory, HTTP calls must have timeouts, errors must be silent (never block
the tool chain).
Files:
src/gradata/hooks/_profiles.pysrc/gradata/hooks/auto_correct.pysrc/gradata/hooks/tool_failure_emit.pysrc/gradata/hooks/implicit_feedback.pysrc/gradata/hooks/agent_precontext.pysrc/gradata/hooks/rule_enforcement.pysrc/gradata/hooks/session_close.pysrc/gradata/hooks/pre_compact.pysrc/gradata/hooks/tool_finding_capture.pysrc/gradata/hooks/config_validate.pysrc/gradata/hooks/brain_maintain.pysrc/gradata/hooks/session_persist.pysrc/gradata/hooks/duplicate_guard.pysrc/gradata/hooks/context_inject.pysrc/gradata/hooks/claude_code.pysrc/gradata/hooks/inject_brain_rules.pysrc/gradata/hooks/_base.pysrc/gradata/hooks/config_protection.pysrc/gradata/hooks/_installer.pysrc/gradata/hooks/agent_graduation.pysrc/gradata/hooks/secret_scan.py
🪛 Ruff (0.15.9)
src/gradata/contrib/patterns/orchestrator.py
[warning] 527-527: Do not call getattr with a constant attribute value. It is not any safer than normal property access.
Replace getattr with attribute access
(B009)
tests/test_convergence_gate.py
[warning] 48-49: Use a single with statement with multiple contexts instead of nested with statements
(SIM117)
src/gradata/hooks/tool_failure_emit.py
[error] 87-88: try-except-pass detected, consider logging the exception
(S110)
[warning] 87-87: Do not catch blind exception: Exception
(BLE001)
src/gradata/hooks/implicit_feedback.py
[error] 95-96: try-except-pass detected, consider logging the exception
(S110)
[warning] 95-95: Do not catch blind exception: Exception
(BLE001)
[warning] 99-99: Consider moving this statement to an else block
(TRY300)
[warning] 100-100: Do not catch blind exception: Exception
(BLE001)
src/gradata/hooks/agent_precontext.py
[error] 76-76: Ambiguous variable name: l
(E741)
[warning] 86-86: Use a list comprehension to create a transformed list
(PERF401)
[warning] 89-89: Consider moving this statement to an else block
(TRY300)
[warning] 90-90: Do not catch blind exception: Exception
(BLE001)
src/gradata/hooks/rule_enforcement.py
[warning] 22-22: Unused function argument: data
(ARG001)
[error] 36-36: Ambiguous variable name: l
(E741)
[error] 42-42: Ambiguous variable name: l
(E741)
tests/test_hooks_learning.py
[error] 20-20: Ambiguous variable name: l
(E741)
[warning] 64-65: Use a single with statement with multiple contexts instead of nested with statements
(SIM117)
[warning] 77-78: Use a single with statement with multiple contexts instead of nested with statements
(SIM117)
[warning] 88-89: Use a single with statement with multiple contexts instead of nested with statements
(SIM117)
src/gradata/hooks/session_close.py
[error] 17-18: try-except-pass detected, consider logging the exception
(S110)
[warning] 17-17: Do not catch blind exception: Exception
(BLE001)
[error] 25-26: try-except-pass detected, consider logging the exception
(S110)
[warning] 25-25: Do not catch blind exception: Exception
(BLE001)
[warning] 29-29: Unused function argument: data
(ARG001)
src/gradata/hooks/pre_compact.py
[error] 33-34: try-except-pass detected, consider logging the exception
(S110)
[warning] 33-33: Do not catch blind exception: Exception
(BLE001)
[warning] 49-49: Use datetime.UTC alias
Convert to datetime.UTC alias
(UP017)
[error] 60-60: Ambiguous variable name: l
(E741)
[warning] 66-66: Consider moving this statement to an else block
(TRY300)
[warning] 67-67: Do not catch blind exception: Exception
(BLE001)
src/gradata/hooks/tool_finding_capture.py
[error] 38-39: try-except-pass detected, consider logging the exception
(S110)
[warning] 38-38: Do not catch blind exception: Exception
(BLE001)
[warning] 44-47: Use contextlib.suppress(Exception) instead of try-except-pass
Replace try-except-pass with with contextlib.suppress(Exception): ...
(SIM105)
[error] 46-47: try-except-pass detected, consider logging the exception
(S110)
[warning] 46-46: Do not catch blind exception: Exception
(BLE001)
[warning] 54-54: for loop variable line overwritten by assignment target
(PLW2901)
[warning] 111-111: Consider moving this statement to an else block
(TRY300)
[warning] 112-112: Do not catch blind exception: Exception
(BLE001)
src/gradata/hooks/config_validate.py
[warning] 35-35: Do not catch blind exception: Exception
(BLE001)
[error] 62-63: try-except-pass detected, consider logging the exception
(S110)
[warning] 62-62: Do not catch blind exception: Exception
(BLE001)
[warning] 68-68: Unused function argument: data
(ARG001)
[warning] 77-77: Consider moving this statement to an else block
(TRY300)
[warning] 78-78: Do not catch blind exception: Exception
(BLE001)
src/gradata/hooks/brain_maintain.py
[error] 35-36: try-except-continue detected, consider logging the exception
(S112)
[warning] 35-35: Do not catch blind exception: Exception
(BLE001)
[error] 37-38: try-except-pass detected, consider logging the exception
(S110)
[warning] 37-37: Do not catch blind exception: Exception
(BLE001)
[warning] 41-41: Unused function argument: brain_dir
(ARG001)
[error] 47-48: try-except-pass detected, consider logging the exception
(S110)
[warning] 47-47: Do not catch blind exception: Exception
(BLE001)
[warning] 51-51: Unused function argument: data
(ARG001)
[error] 59-60: try-except-pass detected, consider logging the exception
(S110)
[warning] 59-59: Do not catch blind exception: Exception
(BLE001)
tests/test_hooks_base.py
[warning] 65-65: Missing return type annotation for private function handler
(ANN202)
[warning] 65-65: Unused function argument: data
(ARG001)
[warning] 75-75: Missing return type annotation for private function handler
(ANN202)
[warning] 75-75: Unused function argument: data
(ARG001)
[warning] 83-83: Missing return type annotation for private function handler
Add return type annotation: Never
(ANN202)
[warning] 83-83: Unused function argument: data
(ARG001)
[warning] 99-99: Use list.extend to create a transformed list
(PERF401)
[warning] 110-110: Use list.extend to create a transformed list
(PERF401)
src/gradata/hooks/session_persist.py
[error] 32-33: try-except-pass detected, consider logging the exception
(S110)
[warning] 32-32: Do not catch blind exception: Exception
(BLE001)
[warning] 40-40: subprocess.run without explicit check argument
Add explicit check=False
(PLW1510)
[error] 41-41: Starting a process with a partial executable path
(S607)
[error] 47-48: try-except-pass detected, consider logging the exception
(S110)
[warning] 47-47: Do not catch blind exception: Exception
(BLE001)
[warning] 52-52: Unused function argument: data
(ARG001)
[warning] 66-66: Use datetime.UTC alias
Convert to datetime.UTC alias
(UP017)
[error] 75-76: try-except-pass detected, consider logging the exception
(S110)
[warning] 75-75: Do not catch blind exception: Exception
(BLE001)
src/gradata/hooks/duplicate_guard.py
[warning] 29-29: Unnecessary assignment to name before return statement
Remove unnecessary assignment
(RET504)
[error] 64-65: try-except-continue detected, consider logging the exception
(S112)
[warning] 64-64: Do not catch blind exception: Exception
(BLE001)
[warning] 76-76: Too many return statements (7 > 6)
(PLR0911)
[warning] 116-116: Do not catch blind exception: Exception
(BLE001)
src/gradata/hooks/context_inject.py
[warning] 17-17: Too many return statements (9 > 6)
(PLR0911)
[warning] 35-35: Do not catch blind exception: Exception
(BLE001)
[warning] 55-55: Consider moving this statement to an else block
(TRY300)
[warning] 56-56: Do not catch blind exception: Exception
(BLE001)
src/gradata/hooks/claude_code.py
[warning] 46-46: Do not catch blind exception: Exception
(BLE001)
src/gradata/hooks/inject_brain_rules.py
[warning] 26-26: Useless if-else condition
(RUF034)
[warning] 32-32: Unused function argument: data
(ARG001)
[error] 46-46: Ambiguous variable name: l
(E741)
[warning] 54-54: Use a list comprehension to create a transformed list
(PERF401)
src/gradata/hooks/_base.py
[warning] 36-36: Do not catch blind exception: Exception
(BLE001)
[warning] 66-66: Missing return type annotation for private function get_brain
(ANN202)
[warning] 76-76: Do not catch blind exception: Exception
(BLE001)
[error] 92-93: try-except-pass detected, consider logging the exception
(S110)
[warning] 92-92: Do not catch blind exception: Exception
(BLE001)
src/gradata/enhancements/behavioral_extractor.py
[warning] 54-54: Comment contains ambiguous – (EN DASH). Did you mean - (HYPHEN-MINUS)?
(RUF003)
[warning] 168-168: Too many return statements (14 > 6)
(PLR0911)
[warning] 168-168: Too many branches (15 > 12)
(PLR0912)
[warning] 196-196: zip() without an explicit strict= parameter
Add explicit value for parameter strict=
(B905)
[warning] 239-239: zip() without an explicit strict= parameter
Add explicit value for parameter strict=
(B905)
[warning] 278-278: zip() without an explicit strict= parameter
Add explicit value for parameter strict=
(B905)
[warning] 314-314: Too many return statements (19 > 6)
(PLR0911)
[warning] 314-314: Too many branches (18 > 12)
(PLR0912)
[warning] 314-314: Unused function argument: category
(ARG001)
[error] 424-425: try-except-pass detected, consider logging the exception
(S110)
[warning] 424-424: Do not catch blind exception: Exception
(BLE001)
src/gradata/hooks/_installer.py
[warning] 169-174: Use list.extend to create a transformed list
(PERF401)
tests/test_pipeline_e2e.py
[error] 93-93: Ambiguous variable name: l
(E741)
[error] 220-220: Ambiguous variable name: l
(E741)
tests/test_hooks_intelligence.py
[error] 54-54: Ambiguous variable name: l
(E741)
[warning] 63-64: Use a single with statement with multiple contexts instead of nested with statements
(SIM117)
[warning] 92-93: Use a single with statement with multiple contexts instead of nested with statements
(SIM117)
[warning] 184-185: Use a single with statement with multiple contexts instead of nested with statements
(SIM117)
[warning] 334-335: Use a single with statement with multiple contexts instead of nested with statements
(SIM117)
[warning] 360-361: Use a single with statement with multiple contexts instead of nested with statements
(SIM117)
[warning] 410-411: Use a single with statement with multiple contexts instead of nested with statements
(SIM117)
src/gradata/hooks/agent_graduation.py
[error] 47-48: try-except-pass detected, consider logging the exception
(S110)
[warning] 47-47: Do not catch blind exception: Exception
(BLE001)
🔇 Additional comments (11)
src/gradata/contrib/patterns/orchestrator.py (1)
526-531: Queue branch update looks correct.This keeps the parallel execution behavior intact while avoiding direct member access on an
object-typedbrain.src/gradata/hooks/config_protection.py (1)
28-40: LGTM!The hook logic is clean and correct. The basename check against the protected files set provides an effective safeguard against modifying linter/formatter configurations.
src/gradata/hooks/secret_scan.py (1)
32-53: LGTM!The secret scanning logic is well-structured with appropriate patterns and blocking behavior. The fallback from
contenttonew_stringhandles both Write and Edit tool inputs correctly.src/gradata/hooks/claude_code.py (2)
18-33: LGTM!Clean delegation to the shared installer module. This simplifies
claude_code.pyand centralizes hook lifecycle management.
46-47: Blind exception catch is acceptable here.The
except Exceptionis intentional for hook resilience — hooks must never block Claude Code. The static analysis hint (BLE001) can be safely ignored in this context.tests/test_hooks_base.py (2)
1-11: LGTM!Good test coverage for the new hook foundation modules. The imports are clean and focused.
93-121: LGTM!The installer tests properly verify profile-specific hook filtering. The assertions check for specific hook names, ensuring the profile system works as designed.
src/gradata/hooks/context_inject.py (1)
17-57: LGTM on overall structure.The multiple early returns provide clear guard clauses. The blind exception catches are appropriate for hook resilience.
src/gradata/hooks/_installer.py (2)
19-37: LGTM!The
HOOK_REGISTRYis well-structured with clear module names, events, matchers, profile tiers, timeouts, and descriptions. The profile-based filtering will correctly gate hook activation.
46-73: LGTM!The
generate_settingsfunction correctly filters hooks by profile tier and builds the expected Claude Code settings structure. Usingsys.executableensures hooks run with the correct Python interpreter.tests/test_hooks_intelligence.py (1)
1-9: LGTM!Comprehensive test coverage for the intelligence and completeness hooks. The tests cover positive cases, negative cases, edge cases (empty messages, slash commands), and event emission verification.
| assert rules_and_patterns[0].state.name == "RULE" | ||
| assert rules_and_patterns[0].confidence == 0.92 | ||
| assert rules_and_patterns[1].state.name == "PATTERN" |
There was a problem hiding this comment.
Use pytest.approx for the confidence assertion.
Direct float equality is brittle here and violates the test rule for floating-point comparisons.
Suggested change
+import pytest
@@
- assert rules_and_patterns[0].confidence == 0.92
+ assert rules_and_patterns[0].confidence == pytest.approx(0.92)As per coding guidelines, tests/**: "floating point comparisons use pytest.approx."
📝 Committable suggestion
‼️ IMPORTANT
Carefully review the code before committing. Ensure that it accurately replaces the highlighted code, contains no missing lines, and has no issues with indentation. Thoroughly test & benchmark the code to ensure it meets the requirements.
| assert rules_and_patterns[0].state.name == "RULE" | |
| assert rules_and_patterns[0].confidence == 0.92 | |
| assert rules_and_patterns[1].state.name == "PATTERN" | |
| assert rules_and_patterns[0].state.name == "RULE" | |
| assert rules_and_patterns[0].confidence == pytest.approx(0.92) | |
| assert rules_and_patterns[1].state.name == "PATTERN" |
🤖 Prompt for AI Agents
Verify each finding against the current code and only fix it if needed.
In `@tests/test_hooks_learning.py` around lines 22 - 24, The test currently
asserts floating-point equality on rules_and_patterns[0].confidence; change this
to use pytest.approx to avoid brittle direct float comparison and follow
tests/** guidelines—import pytest if not present and replace the assert
rules_and_patterns[0].confidence == 0.92 with an assertion using
pytest.approx(0.92) while leaving the other state.name assertions intact.
| try: | ||
| _cloud_path = os.environ.get("GRADATA_CLOUD_PATH", "C:/Users/olive/SpritesWork/brain/cloud-only") | ||
| sys.path.insert(0, _cloud_path) | ||
| from meta_rules import discover_meta_rules, merge_into_meta # type: ignore[import] |
There was a problem hiding this comment.
Remove hardcoded Windows path.
Line 23 contains a hardcoded Windows-specific path that will not exist on other machines or CI environments. Use a relative path or make it purely environment-driven.
🔧 Proposed fix
_CLOUD_DISCOVERY = False
try:
- _cloud_path = os.environ.get("GRADATA_CLOUD_PATH", "C:/Users/olive/SpritesWork/brain/cloud-only")
- sys.path.insert(0, _cloud_path)
+ _cloud_path = os.environ.get("GRADATA_CLOUD_PATH")
+ if _cloud_path:
+ sys.path.insert(0, _cloud_path)
from meta_rules import discover_meta_rules, merge_into_meta # type: ignore[import]
_CLOUD_DISCOVERY = True
except ImportError:As per coding guidelines: "tests/**: no hardcoded paths".
🤖 Prompt for AI Agents
Verify each finding against the current code and only fix it if needed.
In `@tests/test_pipeline_e2e.py` around lines 22 - 25, The code currently sets
_cloud_path with a hardcoded Windows path; change the logic in the try block so
_cloud_path is derived from the environment only
(os.environ["GRADATA_CLOUD_PATH"]) or, if you need a fallback, compute a
repo-relative path using the current file directory (e.g., based on
os.path.dirname(__file__) and join up to the cloud folder) instead of
"C:/Users/…"; then use that _cloud_path when calling sys.path.insert and
importing meta_rules (refer to the _cloud_path variable, sys.path.insert(0,
_cloud_path), and the import of discover_meta_rules and merge_into_meta) so
tests no longer rely on a hardcoded Windows-specific path.
| for corr in SALES_CORRECTIONS[:3]: | ||
| _simulate_session(fresh_brain, corr) | ||
| lessons = fresh_brain._load_lessons() | ||
| process_lessons = [l for l in lessons if l.category == "PROCESS"] |
There was a problem hiding this comment.
🧹 Nitpick | 🔵 Trivial
Rename ambiguous loop variable l.
Single-letter l is easily confused with 1 or I.
♻️ Proposed fix
- process_lessons = [l for l in lessons if l.category == "PROCESS"]
+ process_lessons = [lesson for lesson in lessons if lesson.category == "PROCESS"]📝 Committable suggestion
‼️ IMPORTANT
Carefully review the code before committing. Ensure that it accurately replaces the highlighted code, contains no missing lines, and has no issues with indentation. Thoroughly test & benchmark the code to ensure it meets the requirements.
| process_lessons = [l for l in lessons if l.category == "PROCESS"] | |
| process_lessons = [lesson for lesson in lessons if lesson.category == "PROCESS"] |
🧰 Tools
🪛 Ruff (0.15.9)
[error] 93-93: Ambiguous variable name: l
(E741)
🤖 Prompt for AI Agents
Verify each finding against the current code and only fix it if needed.
In `@tests/test_pipeline_e2e.py` at line 93, The list comprehension uses an
ambiguous single-letter loop variable `l`; rename it to a descriptive name like
`lesson` in the expression process_lessons = [lesson for lesson in lessons if
lesson.category == "PROCESS"] and update any surrounding references (e.g., other
comprehensions or usages in tests/test_pipeline_e2e.py) to use `lesson` instead
of `l` to avoid confusion with `1` or `I`.
| weights = metas[0].context_weights | ||
| # The task_type for DRAFTING is "drafting" — check it has elevated weight | ||
| task_type_weight = max(v for k, v in weights.items() if k != "default") | ||
| assert task_type_weight >= 1.5, f"Expected elevated task_type weight, got {weights}" |
There was a problem hiding this comment.
Guard against empty weights dict.
If context_weights only contains "default", the max() call on line 166 will raise ValueError: max() iterable argument is empty.
🛡️ Proposed fix
weights = metas[0].context_weights
# The task_type for DRAFTING is "drafting" — check it has elevated weight
- task_type_weight = max(v for k, v in weights.items() if k != "default")
+ non_default = [v for k, v in weights.items() if k != "default"]
+ assert non_default, "Expected context_weights to have keys beyond 'default'"
+ task_type_weight = max(non_default)
assert task_type_weight >= 1.5, f"Expected elevated task_type weight, got {weights}"📝 Committable suggestion
‼️ IMPORTANT
Carefully review the code before committing. Ensure that it accurately replaces the highlighted code, contains no missing lines, and has no issues with indentation. Thoroughly test & benchmark the code to ensure it meets the requirements.
| weights = metas[0].context_weights | |
| # The task_type for DRAFTING is "drafting" — check it has elevated weight | |
| task_type_weight = max(v for k, v in weights.items() if k != "default") | |
| assert task_type_weight >= 1.5, f"Expected elevated task_type weight, got {weights}" | |
| weights = metas[0].context_weights | |
| # The task_type for DRAFTING is "drafting" — check it has elevated weight | |
| non_default = [v for k, v in weights.items() if k != "default"] | |
| assert non_default, "Expected context_weights to have keys beyond 'default'" | |
| task_type_weight = max(non_default) | |
| assert task_type_weight >= 1.5, f"Expected elevated task_type weight, got {weights}" |
🤖 Prompt for AI Agents
Verify each finding against the current code and only fix it if needed.
In `@tests/test_pipeline_e2e.py` around lines 164 - 167, The test assumes
metas[0].context_weights has non-"default" entries but will crash if it doesn't;
update the assertion to first extract non-default items from
metas[0].context_weights (e.g., filter keys != "default"), handle the empty case
by using a sensible fallback (like the "default" weight or 0.0) before calling
max, and then assert that the computed task_type_weight is >= 1.5; refer to the
variables metas, context_weights, weights, and task_type_weight when locating
and updating the logic.
| promoted = [] | ||
| for l in lessons: | ||
| if l.category == "PROCESS": | ||
| promoted.append(Lesson( | ||
| date=l.date, state=LessonState.RULE, confidence=0.90, | ||
| category=l.category, description=l.description, | ||
| )) | ||
| else: | ||
| promoted.append(l) |
There was a problem hiding this comment.
🧹 Nitpick | 🔵 Trivial
Rename ambiguous loop variable l.
♻️ Proposed fix
promoted = []
- for l in lessons:
- if l.category == "PROCESS":
+ for lesson in lessons:
+ if lesson.category == "PROCESS":
promoted.append(Lesson(
- date=l.date, state=LessonState.RULE, confidence=0.90,
- category=l.category, description=l.description,
+ date=lesson.date, state=LessonState.RULE, confidence=0.90,
+ category=lesson.category, description=lesson.description,
))
else:
- promoted.append(l)
+ promoted.append(lesson)📝 Committable suggestion
‼️ IMPORTANT
Carefully review the code before committing. Ensure that it accurately replaces the highlighted code, contains no missing lines, and has no issues with indentation. Thoroughly test & benchmark the code to ensure it meets the requirements.
| promoted = [] | |
| for l in lessons: | |
| if l.category == "PROCESS": | |
| promoted.append(Lesson( | |
| date=l.date, state=LessonState.RULE, confidence=0.90, | |
| category=l.category, description=l.description, | |
| )) | |
| else: | |
| promoted.append(l) | |
| promoted = [] | |
| for lesson in lessons: | |
| if lesson.category == "PROCESS": | |
| promoted.append(Lesson( | |
| date=lesson.date, state=LessonState.RULE, confidence=0.90, | |
| category=lesson.category, description=lesson.description, | |
| )) | |
| else: | |
| promoted.append(lesson) |
🧰 Tools
🪛 Ruff (0.15.9)
[error] 220-220: Ambiguous variable name: l
(E741)
🤖 Prompt for AI Agents
Verify each finding against the current code and only fix it if needed.
In `@tests/test_pipeline_e2e.py` around lines 219 - 227, The loop uses an
ambiguous variable name `l`; rename it to a descriptive name like `lesson` in
the loop that builds `promoted` (for lesson in lessons) and update all
references inside the loop (`l.category`, `l.date`, `l.description`) to
`lesson.category`, `lesson.date`, `lesson.description` so readability is
improved while preserving the behavior that constructs Lesson(...) with
LessonState.RULE for PROCESS-category items and appends the original lesson
otherwise.
|
Note Autofix is a beta feature. Expect some limitations and changes as we gather feedback and continue to improve it. ❌ Cannot run autofix: This PR has merge conflicts. Please resolve the conflicts with the base branch and try again. Alternatively, use |
…or, nitpick CRITICAL: auto_correct main() accepts data dict, emit() uses ctx not brain_dir (agent_graduation, implicit_feedback, tool_failure_emit, session_close), EventType replaced with string, graduation_sweep replaced with graduate(), installer matcher moved to group level. MAJOR: secret_scan scans MultiEdit edits, meta_rules_storage conn leak fixed, config_validate validates nested hook entries, duplicate_guard resolves paths, pre_compact/tool_finding_capture use per-user temp dirs, session_persist includes untracked files. MINOR: context_inject separator in budget, behavioral_extractor module-level import + boundary-aware matching + relaxed actionable check, installer handles corrupt JSON + uses logging. NITPICK: l->lesson rename, get_brain return type, debug logging for suppressed exceptions. 1774 tests pass, 17 skipped. Co-Authored-By: Gradata <noreply@gradata.ai>
…pick Critical: auto_correct main() signature, EventType→string, emit ctx param, brain_maintain BrainContext threading, graduation_sweep→inline graduation Major: MultiEdit secret scanning, SQLite conn leak, config_validate nesting, duplicate_guard path normalization, per-user temp dirs, session_persist untracked files Minor: corrupt settings.json handling, context budget, behavioral_extractor boundaries Nitpick: l→lesson renames, return type annotation, debug logging, logging vs print Co-Authored-By: Gradata <noreply@gradata.ai>
There was a problem hiding this comment.
Actionable comments posted: 31
Caution
Some comments are outside the diff and can’t be posted inline due to platform limitations.
⚠️ Outside diff range comments (1)
src/gradata/hooks/auto_correct.py (1)
80-91:⚠️ Potential issue | 🟡 MinorUnused variable:
file_pathis fetched but never used.Line 83 retrieves
file_pathbut doesn't assign or use the result. This appears to be dead code from an incomplete implementation.🧹 Proposed fix
elif tool_name == "Write": # For Write, we need the previous file content # The hook receives the tool output which may include the old content - tool_input.get("input", {}).get("file_path", "") new_content = tool_input.get("input", {}).get("content", "")🤖 Prompt for AI Agents
Verify each finding against the current code and only fix it if needed. In `@src/gradata/hooks/auto_correct.py` around lines 80 - 91, The branch handling tool_name == "Write" contains a dead call to tool_input.get("input", {}).get("file_path", "") that neither assigns nor uses the result; remove this unused fetch (or if the file_path is actually needed, assign it to a variable like file_path = tool_input.get("input", {}).get("file_path", "") and use it in the comparison/return logic). Update the elif block around tool_input/tool_output/old_content/new_content so only relevant variables are accessed and returned (preserve the existing old_content vs new_content check and the return of (old_content[:5000], new_content[:5000]) when applicable).
♻️ Duplicate comments (9)
src/gradata/enhancements/meta_rules_storage.py (1)
449-460:⚠️ Potential issue | 🟠 MajorMake grouped metadata deterministic in graduation query.
At Lines 449-460,
categoryandrepresentative_textare selected while grouping only bypattern_hash. In SQLite, those fields are taken from an arbitrary row in the group, so results can drift between runs.In SQLite aggregate queries, what are the semantics of selecting non-aggregated columns that are not listed in GROUP BY (a.k.a. bare columns)?🤖 Prompt for AI Agents
Verify each finding against the current code and only fix it if needed. In `@src/gradata/enhancements/meta_rules_storage.py` around lines 449 - 460, The graduation query selects category and representative_text while grouping only by pattern_hash, which yields non-deterministic results; make it deterministic by either adding category and representative_text to the GROUP BY clause (if they are functionally dependent on pattern_hash) or, more robustly, wrap them in deterministic aggregates such as MIN(category) AS category and MIN(representative_text) AS representative_text in the SELECT list for the correction_patterns aggregation used in the graduation query (keep the GROUP BY pattern_hash and HAVING COUNT(DISTINCT session_id) >= ? unchanged).src/gradata/hooks/tool_finding_capture.py (1)
110-116:⚠️ Potential issue | 🟠 MajorSubstring matching can still cause false positives when linking edits to failed files.
The condition
if file_basename in f or f in file_pathuses substring containment which can incorrectly match unrelated files:
"api.py"in"graphapi.py"→ matches (false positive)"foo.py"in"test_foo.py"→ matches (false positive)This can prematurely clear findings and emit bogus correction signals to the learning pipeline.
🐛 Proposed fix: Use exact basename comparison or normalized suffix matching
file_basename = Path(file_path).name for finding in findings: for f in finding.get("files", []): - if file_basename in f or f in file_path: + f_basename = Path(f).name + # Exact basename match or normalized path suffix + if file_basename == f_basename or file_path.endswith(f.lstrip("./")): # User is editing a file related to a test finding _save_findings([]) # Clear acted-on findings return {"result": "Correction captured from test finding"}🤖 Prompt for AI Agents
Verify each finding against the current code and only fix it if needed. In `@src/gradata/hooks/tool_finding_capture.py` around lines 110 - 116, The substring check in the loop (the condition using file_basename, file_path and finding.get("files")) causes false positives; update the matching to normalize both sides and perform exact basename equality or a normalized suffix match instead: derive candidate_basename = Path(f).name (or os.path.basename) and replace the condition with candidate_basename == file_basename (or candidate_path.endswith(Path(file_path).name) after normalizing paths) so only exact file basenames or clearly normalized suffix matches trigger _save_findings([]) and the correction capture.src/gradata/hooks/inject_brain_rules.py (1)
22-29: 🧹 Nitpick | 🔵 TrivialUseless conditional and hardcoded value remain.
Two issues from previous reviews persist:
Line 26:
state_str = state if isinstance(state, str) else state— both branches return the same value, making the conditional useless.Line 27: Uses hardcoded
0.6instead of theMIN_CONFIDENCEconstant defined at line 19, reducing maintainability.♻️ Proposed fix
def _score(lesson) -> float: """Score a lesson dict or Lesson object for injection priority.""" conf = lesson["confidence"] if isinstance(lesson, dict) else lesson.confidence state = lesson["state"] if isinstance(lesson, dict) else lesson.state.name - state_str = state if isinstance(state, str) else state - conf_norm = (conf - 0.6) / 0.4 + state_str = str(state) # Ensure string for comparison + conf_norm = (conf - MIN_CONFIDENCE) / (1.0 - MIN_CONFIDENCE) state_bonus = 1.0 if state_str == "RULE" else 0.7 return 0.4 * state_bonus + 0.3 * conf_norm + 0.3 * conf🤖 Prompt for AI Agents
Verify each finding against the current code and only fix it if needed. In `@src/gradata/hooks/inject_brain_rules.py` around lines 22 - 29, The _score function has a redundant conditional and a hardcoded threshold: replace the useless state_str line by normalizing to a string (e.g., state_str = state if isinstance(state, str) else state.name if hasattr(state, "name") else str(state)) to handle enum/object states, and replace the hardcoded 0.6/0.4 with the MIN_CONFIDENCE constant (use conf_norm = (conf - MIN_CONFIDENCE) / (1.0 - MIN_CONFIDENCE)) so the function _score uses MIN_CONFIDENCE for normalization and removes the unnecessary conditional.src/gradata/hooks/config_validate.py (1)
47-71:⚠️ Potential issue | 🟡 MinorThe nested hook validation has been partially fixed, but command matching remains fragile.
The previous review noted that validation wasn't checking nested hook entries. This has been addressed - the code now correctly iterates through
group.get("hooks", [])with a fallback for legacy flat entries.However, the command check at line 59 (
"python -m gradata.hooks." in command) is still too restrictive. The installer usessys.executable, which may be/usr/bin/python3,python3.11, or a virtual environment path. This causes valid hooks to be flagged as missing.🐛 Proposed fix: Match the module pattern regardless of Python executable
command = hook.get("command", "") - if "python -m gradata.hooks." in command: - module_name = command.split("gradata.hooks.")[-1].split()[0].strip('"\'') + # Match "-m gradata.hooks." regardless of Python executable name + if " -m gradata.hooks." in command or command.startswith("gradata.hooks."): + parts = command.split("gradata.hooks.") + if len(parts) < 2: + continue + module_name = parts[-1].split()[0].strip('"\'') try: import gradata.hooks as hooks_pkg hooks_dir = Path(hooks_pkg.__file__).parent🤖 Prompt for AI Agents
Verify each finding against the current code and only fix it if needed. In `@src/gradata/hooks/config_validate.py` around lines 47 - 71, The command matching is too strict: in validate_hooks (inside the loop over inner_hooks) replace the substring check for "python -m gradata.hooks." with a regex search for the module pattern so any python executable or invocation is accepted; e.g., search command for the pattern r"gradata\.hooks\.([A-Za-z0-9_]+)" (accounting for optional quotes) to extract module_name and then perform the existing package-file check (import gradata.hooks as hooks_pkg, derive hooks_dir, check module_path.is_file()) and emit the same warning if missing.tests/test_hooks_intelligence.py (4)
54-54: 🧹 Nitpick | 🔵 TrivialRename ambiguous loop variable
ltoline.The variable
lis ambiguous and can be confused with the number1.♻️ Proposed fix
- assert any("SALES" in l for l in lines) + assert any("SALES" in line for line in lines)🤖 Prompt for AI Agents
Verify each finding against the current code and only fix it if needed. In `@tests/test_hooks_intelligence.py` at line 54, The assertion uses a one-letter loop variable `l` which is ambiguous; change the generator expression in the test (the assert any(...) line in tests/test_hooks_intelligence.py) to use a clearer name like `line` (e.g., assert any("SALES" in line for line in lines)) so the intent is readable and avoids confusion with the digit `1`.
62-73: 🧹 Nitpick | 🔵 TrivialCombine nested
withstatements for readability.Multiple nested
withstatements can be combined into a single statement.♻️ Proposed fix
def test_agent_graduation_emits_event(tmp_path): - with patch.dict(os.environ, {"GRADATA_BRAIN_DIR": str(tmp_path)}): - with patch("gradata._events.emit") as mock_emit: - result = graduation_main({ - "tool_name": "Agent", - "tool_input": {"subagent_type": "code"}, - "tool_output": "Here is the result of the agent work", - }) + with ( + patch.dict(os.environ, {"GRADATA_BRAIN_DIR": str(tmp_path)}), + patch("gradata._events.emit") as mock_emit, + ): + result = graduation_main({ + "tool_name": "Agent", + "tool_input": {"subagent_type": "code"}, + "tool_output": "Here is the result of the agent work", + })🤖 Prompt for AI Agents
Verify each finding against the current code and only fix it if needed. In `@tests/test_hooks_intelligence.py` around lines 62 - 73, The test uses nested with statements; simplify by combining them into one with to improve readability: replace the nested "with patch.dict(os.environ, {...}): with patch('gradata._events.emit') as mock_emit:" block in test_agent_graduation_emits_event with a single "with patch.dict(os.environ, {'GRADATA_BRAIN_DIR': str(tmp_path)}), patch('gradata._events.emit') as mock_emit:" and then call graduation_main(...) inside that combined context (keeping the same assertions and variable names such as result and mock_emit.assert_called_once()).
127-163: 🧹 Nitpick | 🔵 TrivialUse a pytest fixture for FINDINGS_FILE cleanup to ensure test isolation.
The tests manually manage
FINDINGS_FILEsetup and cleanup. If a test fails before cleanup, subsequent tests may be affected. Consider using a fixture with guaranteed cleanup.♻️ Proposed fixture approach
`@pytest.fixture` def clean_findings(): """Ensure FINDINGS_FILE is clean before and after test.""" if FINDINGS_FILE.exists(): FINDINGS_FILE.unlink() yield FINDINGS_FILE.unlink(missing_ok=True) def test_finding_capture_stores_test_failure(clean_findings): result = finding_main({ "tool_name": "Bash", "tool_input": {"command": "pytest tests/"}, "tool_output": "FAILED tests/test_foo.py::test_bar - AssertionError\nshort test summary", }) assert result is None assert FINDINGS_FILE.exists() findings = json.loads(FINDINGS_FILE.read_text()) assert len(findings) >= 1 assert "test_foo.py" in findings[0]["files"][0] def test_finding_capture_detects_acted_on(clean_findings): FINDINGS_FILE.write_text(json.dumps([{ "files": ["tests/test_foo.py"], "preview": "FAILED", "command": "pytest", }])) result = finding_main({ "tool_name": "Edit", "tool_input": {"file_path": "tests/test_foo.py", "old_string": "x", "new_string": "y"}, }) assert result is not None assert "Correction captured" in result["result"]🤖 Prompt for AI Agents
Verify each finding against the current code and only fix it if needed. In `@tests/test_hooks_intelligence.py` around lines 127 - 163, Tests manually create and remove FINDINGS_FILE which can leak state on failure; add a pytest fixture named clean_findings that ensures FINDINGS_FILE is removed before yielding and unlinked (missing_ok=True) after yield, then update test_finding_capture_stores_test_failure and test_finding_capture_detects_acted_on to accept the clean_findings fixture and remove their manual unlink/setup calls so they rely on the fixture to prepare and cleanup the file while still invoking finding_main and asserting on FINDINGS_FILE and finding_main results.
91-101: 🧹 Nitpick | 🔵 TrivialCombine nested
withstatements.Same pattern as previous - can be combined for readability.
♻️ Proposed fix
def test_tool_failure_detects_error(tmp_path): - with patch.dict(os.environ, {"GRADATA_BRAIN_DIR": str(tmp_path)}): - with patch("gradata._events.emit") as mock_emit: - result = failure_main({ + with ( + patch.dict(os.environ, {"GRADATA_BRAIN_DIR": str(tmp_path)}), + patch("gradata._events.emit") as mock_emit, + ): + result = failure_main({🤖 Prompt for AI Agents
Verify each finding against the current code and only fix it if needed. In `@tests/test_hooks_intelligence.py` around lines 91 - 101, The test test_tool_failure_detects_error uses nested context managers; simplify by combining them into one with statement to improve readability — e.g., use a single "with patch.dict(os.environ, {...}), patch('gradata._events.emit') as mock_emit:" block around the call to failure_main so the environment and mock are applied together; keep assertions for result, mock_emit.assert_called_once() and checking mock_emit.call_args[0][0] == "TOOL_FAILURE" unchanged and ensure the variable names (failure_main, mock_emit) remain the same.src/gradata/hooks/_base.py (1)
69-81: 🧹 Nitpick | 🔵 TrivialImprove return type annotation and remove redundant existence check.
The return type
object | Noneis imprecise. Use a string annotation for the conditionally imported type. ThePath(brain_dir).exists()check on line 79 is redundant sinceresolve_brain_dir()already guarantees existence when returning a non-None value.♻️ Proposed fix
-def get_brain() -> object | None: +def get_brain() -> "Brain | None": """Get a Brain instance from resolved brain dir, or None on failure.""" try: from gradata.brain import Brain except ImportError: return None brain_dir = resolve_brain_dir() if not brain_dir: return None try: - return Brain(brain_dir) if Path(brain_dir).exists() else None + return Brain(brain_dir) except Exception: return None🤖 Prompt for AI Agents
Verify each finding against the current code and only fix it if needed. In `@src/gradata/hooks/_base.py` around lines 69 - 81, Change get_brain's return annotation to a forward-reference string of the conditionally imported type ("Brain | None"), remove the redundant Path(brain_dir).exists() check (resolve_brain_dir() already guarantees existence), and simply return Brain(brain_dir) inside the try block; keep the conditional import of Brain and the existing resolve_brain_dir() None check and exception handling. Use the symbol names get_brain, Brain, and resolve_brain_dir to locate and update the function signature and return logic.
🤖 Prompt for all review comments with AI agents
Verify each finding against the current code and only fix it if needed.
Inline comments:
In `@src/gradata/enhancements/behavioral_extractor.py`:
- Around line 199-203: The zip calls used to pair sentence lists (e.g., in the
draft_sent_sets/final_sent_sets -> added_sents computation that calls
zip(final_sents, final_sent_sets)) should use strict=True to catch any future
length mismatches; update that zip(...) to zip(..., strict=True) and apply the
same change to the other zip usages referenced in this file (the ones around the
blocks at the later spots mentioned – lines corresponding to the logic around
249 and 287) so all zips pairing concurrently-constructed lists enforce equal
lengths (referencing draft_sent_sets, final_sent_sets, added_sents and the other
paired-list computations).
- Around line 431-441: The _try_llm_extract function currently swallows all
exceptions; modify it to log the exception instead of silently passing: add a
module-level logger (e.g., get a logger via logging.getLogger(...) near the
other imports) and inside the except Exception block call logger.exception or
logger.error with the exception context and a clear message referencing
llm_provider or classification, then return None as before; ensure you import
logging at the top if not present and use the logger in _try_llm_extract to
preserve observability.
- Around line 323-324: The function generate_instruction currently declares an
unused parameter category; remove category from its signature and any default,
then update all call sites that pass a category argument to call
generate_instruction(match) with only the match argument, or alternatively if
you prefer to keep the parameter document its intended future use in the
docstring and add a TODO; reference the generate_instruction function and ensure
callers that previously supplied a category (e.g., the place invoking
generate_instruction with two args) are adjusted accordingly.
- Around line 418-428: The _is_actionable gate in behavioral_extractor.py is too
strict: it only accepts words in _IMPERATIVE_STARTERS or capitalized three-word
phrases, causing explicit imperative instructions like "Prioritize ROI in the
opener" to be rejected; update _is_actionable to either expand the
_IMPERATIVE_STARTERS set with common imperative verbs (e.g., prioritize,
emphasize, highlight, remove, add, reduce, increase) or relax the heuristic for
PREFIX_INSTRUCTION outputs by allowing any sentence where the first token is a
verb lemma (or appears in a small added verb whitelist) and the total token
count >=2; modify the logic inside function _is_actionable to check the expanded
_IMPERATIVE_STARTERS or the relaxed PREFIX_INSTRUCTION condition and ensure the
first_word normalization (removesuffix) still applies.
In `@src/gradata/enhancements/meta_rules_storage.py`:
- Around line 345-468: The DB functions (ensure_pattern_table,
upsert_correction_pattern, upsert_correction_patterns_batch,
query_graduation_candidates) must accept a BrainContext instead of a raw
db_path; update each signature to take ctx: BrainContext (or ctx: BrainContext,
keep backward-compat as needed) and use ctx.db_path (or ctx.get_db_path()) when
opening the sqlite3 connection, then update all call sites/tests to pass the
BrainContext; keep the existing logic and return values unchanged and ensure
imports/reference to BrainContext are added where these functions are defined.
- Line 342: PATTERN_SEVERITY_WEIGHTS currently contains values >1 which violates
the SDK requirement; update the mapping for PATTERN_SEVERITY_WEIGHTS so all
entries are within [0,1] (e.g., normalize or rescale the existing weights to the
0–1 range), or add a deterministic clamp when the weights are consumed (apply
min(max(weight, 0.0), 1.0) before any scoring). Ensure you modify the constant
PATTERN_SEVERITY_WEIGHTS or the code path that reads it so that every severity
value used by scoring is guaranteed to be clamped to [0,1].
- Around line 370-431: The upsert functions can fail on fresh DBs because the
correction_patterns table may not exist; modify upsert_correction_pattern and
upsert_correction_patterns_batch to ensure the table is created before
attempting inserts by invoking the table-initialization helper (e.g., call
ensure_pattern_table(db_path) or the equivalent table-creation routine) at the
start of both functions (before sqlite3.connect/execute), so the table is
present on first-run and the upserts never raise "no such table".
In `@src/gradata/enhancements/rule_canary.py`:
- Around line 50-83: The _get_db_path function can return None which leads
callers that do sqlite3.connect(str(db_path)) to open a file literally named
"None"; change _get_db_path to fail fast by raising a clear exception (e.g.,
ValueError) or returning a guaranteed Path and never None, and update callers
that accept a BrainContext to rely on ctx.db_path first (use getattr(ctx,
"db_path")) and, if absent, raise rather than falling back to a hardcoded
repo-relative "brain/system.db"; remove the hardcoded scripts_dir traversal or
replace it with a proper BrainContext resolution or environment-driven path, and
ensure all places that call sqlite3.connect use a validated Path returned from
_get_db_path (or handle the raised exception) so no sqlite3.connect(str(None))
can occur.
- Around line 213-234: The code mutates sys.path and tries `from events import
emit`, which breaks in normal installs and drops RULE_ROLLBACK/CANARY_PROMOTED
events; replace the dynamic import logic in the rollback/emit block (the code
that references emit, RULE_ROLLBACK and the rollback_rule call) with a direct
import from the package module by using `from gradata._events import emit`
(remove the os/env Path sys.path insertion and the fallback import), and make
the same change for the other occurrence handling CANARY_PROMOTED so both emit
calls use gradata._events.emit.
- Around line 140-173: The sessions_active calculation is off by one: currently
sessions_active = session - start_session causes the canary to require one extra
session before promotion; update the computation in rule_canary.py (the
start_session/sessions_active logic) so sessions_active counts inclusive of the
starting session (e.g., compute sessions_active as session - start_session + 1
or otherwise adjust the comparison against CANARY_SESSIONS) so the subsequent
check against CANARY_SESSIONS correctly promotes after the intended number of
sessions.
- Around line 75-81: The silent exception handler around resolving scripts_dir
and p (Path(__file__), scripts_dir, p) should be replaced with structured
logging: ensure a module logger (e.g. logger = logging.getLogger(__name__))
exists, catch the exception and call logger.exception("Failed to resolve
brain/system.db path") so the stack trace is preserved rather than silently
passing; likewise replace all print(f"WARNING [...]: {e}", file=sys.stderr)
usages in this module with logger.warning("... descriptive message",
exc_info=True) or logger.exception(...) as appropriate to include exception
context (refer to the occurrences around the same module where warnings are
printed).
- Around line 1-20: Add the postponed annotations import to the top of the
module by inserting "from __future__ import annotations" as the very first
import in src/gradata/enhancements/rule_canary.py so forward references in type
hints used by functions like promote_to_canary, check_canary_health,
rollback_rule, and get_canary_rules work correctly; ensure it precedes other
imports (e.g., sqlite3, sys, datetime) and save the file.
In `@src/gradata/enhancements/rule_integrity.py`:
- Around line 146-148: The regex pattern
r"\[(?:INSTINCT|PATTERN|RULE):(\d+\.\d+)\]\s+(\w+):\s+(.+)" is duplicated in
sign_lesson_file and verify_lesson_file; extract it to a module-level constant
(e.g., _LESSON_PATTERN) defined near the top of the file (after imports) and
replace the inline re.compile(...) calls in both sign_lesson_file and
verify_lesson_file to use _LESSON_PATTERN instead, ensuring both functions
import/see the constant and behavior remains identical.
- Around line 275-292: The current verify_from_db loads the entire signatures
table via load_signatures() for a single-category check; add a helper
_load_signature(db_path: Path, category: str) that calls _ensure_table(db_path),
queries "SELECT signature FROM rule_signatures WHERE category = ?" with
category.upper(), returns "" if no row, and always closes the sqlite3
connection, and then change verify_from_db to call _load_signature instead of
load_signatures(), keeping the existing checks using _get_secret_key() and
verify_rule(rule_text, category, confidence, stored_sig).
- Around line 36-48: The _get_secret_key function currently caches the result in
the module-level _SECRET_KEY which prevents subsequent environment changes
(GRADATA_RULE_SECRET) from being picked up; update the _get_secret_key docstring
to explicitly state this caching is intentional for session consistency and that
environment changes after first access will be ignored, referencing the
module-level _SECRET_KEY and the environment variable name GRADATA_RULE_SECRET
so maintainers understand the behavior and rationale.
- Around line 78-93: The sign_rule function currently passes confidence through
unchecked; clamp the confidence to the [0.0, 1.0] range before calling
_canonical_payload inside sign_rule (e.g., normalized_conf = max(0.0, min(1.0,
confidence))). Apply the same clamping in verify_rule before it calls
_canonical_payload so both signing and verification use the identical
canonicalized confidence value; leave all other logic (key check, payload
creation, HMAC computation) unchanged.
- Around line 205-256: The DB helper functions _ensure_table, store_signature,
and load_signatures currently open their own sqlite3 connections and don't
accept BrainContext; refactor them to accept a BrainContext (or an optional
sqlite3.Connection) and use the shared connection from BrainContext instead of
creating new ones so you avoid opening two connections per call (e.g., have
_ensure_table(conn: sqlite3.Connection | BrainContext) and change
store_signature(category, signature, ctx: BrainContext) and load_signatures(ctx:
BrainContext)), remove local conn lifecycle management (do not close the shared
connection), keep behavior such as category.upper() and timestamping with
datetime.now(UTC).
In `@src/gradata/hooks/_base.py`:
- Around line 96-98: The except block currently logs the suppressed exception
using _log.debug("Hook %s suppressed exception: %s", meta.get("event", "?"),
exc) and then has an unnecessary pass; remove the redundant pass so the except
block only performs the debug log (no-op pass is not needed). Locate the except
Exception as exc block in the hooks base (referenced by _log, meta.get("event",
"?"), and exc) and delete the trailing pass statement so the exception handling
is concise.
In `@src/gradata/hooks/auto_correct.py`:
- Around line 242-251: main() is performing an unnecessary JSON round-trip by
json.dumps(data) before calling process_hook_input; change the code to avoid
re-serializing by either updating process_hook_input to accept a dict (new
signature: process_hook_input(data: dict) and update all callers) or bypass
process_hook_input and call the internal helpers directly from main (e.g., call
_extract_correction(...) and _get_brain(...) with the parsed dict), ensuring you
update any places that expect a JSON string and keep behavior and return shape
the same.
In `@src/gradata/hooks/brain_maintain.py`:
- Around line 41-48: The _generate_manifest function currently has an unused
brain_dir parameter; remove brain_dir from the function signature (def
_generate_manifest(ctx=None) -> None) and update all call sites that pass a
brain_dir to call _generate_manifest(ctx=...) instead, ensuring you keep the
existing behavior of importing and calling generate_manifest and write_manifest
with ctx=ctx; also update any tests or references to the old signature to match
the new one.
In `@src/gradata/hooks/duplicate_guard.py`:
- Around line 52-65: The code iterating WATCHED_DIRS in duplicate_guard.py
currently swallows all exceptions silently; update that try/except to log caught
exceptions at debug level (e.g., use logger.debug or module logger) including
the watched_dir path and exception details (use exc_info=True or log the
exception string) so permission errors or broken symlinks are recorded without
changing behavior of the loop; keep the continue so behavior around _similarity,
SIMILARITY_THRESHOLD, target_path, and appending to similar remains unchanged.
In `@src/gradata/hooks/implicit_feedback.py`:
- Around line 100-103: The outer except block that currently swallows all
exceptions (the except Exception: return None in the hook that builds
signal_names from signals) should log the error instead of failing silently;
import logging if not present and use the module logger
(logging.getLogger(__name__)) and call logger.exception(...) or
logger.error(..., exc_info=True) inside that except to record the exception and
context (include the signal_names or signals variable in the log message), then
continue returning None so the hook remains non-blocking.
In `@src/gradata/hooks/pre_compact.py`:
- Around line 28-36: Move the inline "import re" out of the
_get_session_number() function and place a single top-level "import re" with the
other module imports; then remove the in-function import so
_get_session_number() uses the module-level re, ensuring you add it among
standard library imports (and adjust any import grouping/order if your linter
requires).
- Around line 64-68: The snapshot filename is still fixed and can clobber
concurrent sessions; change how snapshot_path is constructed so it includes a
brain/session-specific suffix (e.g. a short hash of the brain directory or
Path.cwd(), or a UUID session id) before calling user_tmp.mkdir(...) and
snapshot_path.write_text(...). Update the code that builds snapshot_path (the
variable named snapshot_path) to use something like
f"compact-snapshot-{brain_id}.json" or include a uuid (generated once per run)
so snapshots are unique per brain/session while keeping user_tmp and the
existing snapshot write logic unchanged.
In `@src/gradata/hooks/secret_scan.py`:
- Around line 38-40: The current loop builds a partial secret preview (preview =
m[:8] + "...") which may leak sensitive prefixes; update the code that populates
findings (the loop that creates preview and appends to findings) to stop
exposing any substring of the secret and instead use a fixed placeholder (e.g.,
"<REDACTED_SECRET>" or "****REDACTED****") or a boolean flag like {"name": name,
"redacted": true} so no secret content is returned; adjust any consumers of
findings (the code reading "preview") to handle the new placeholder/flag.
In `@src/gradata/hooks/session_persist.py`:
- Around line 44-47: The subprocess.run invocations in session_persist.py that
capture git output (the call returning result at the top and the similar call at
lines 55-58) must include an explicit check=False since you handle returncode
manually; update the subprocess.run calls (the ones that assign to result) to
pass check=False so intent is explicit and Ruff PLW1510 is satisfied.
- Around line 64-71: Replace the manual deduplication loop that builds
seen/unique with a one-liner using dict.fromkeys to preserve order; locate the
code that iterates over files (the seen = set(); unique = []; for f in files:
... return unique block) and return a list(dict.fromkeys(files)) instead to
simplify and maintain the same behavior.
In `@tests/test_hooks_intelligence.py`:
- Around line 411-417: The test uses two nested with contexts; combine them into
a single with statement to simplify scope management: replace the nested with
patch.dict(os.environ, {"GRADATA_BRAIN_DIR": str(tmp_path)}): with
patch("gradata._events.emit") as mock_emit: ... block in
test_implicit_feedback_emits_event with one line using both context managers
(with patch.dict(...), patch("gradata._events.emit") as mock_emit:), then call
feedback_main({"message": ...}), keep assertions against mock_emit and result
unchanged.
- Around line 332-348: The test_brain_maintain_runs_silently has deeply nested
with statements; refactor it by combining context managers into a single with
line to improve readability: merge patch.dict(os.environ, {"GRADATA_BRAIN_DIR":
str(tmp_path)}), patch("gradata._query.fts_index") as mock_fts,
patch("gradata._brain_manifest.generate_manifest", return_value={}), and
patch("gradata._brain_manifest.write_manifest") into one combined with
statement, then call maintain_main({}) and assert result is None and
mock_fts.assert_called() as before; keep the function name
test_brain_maintain_runs_silently and references to maintain_main, mock_fts, and
GRADATA_BRAIN_DIR unchanged.
- Around line 180-190: The test test_context_inject_returns_context uses nested
with statements for patch.dict and patch("gradata.brain.Brain", ...) which can
be combined into a single with for clarity; refactor the test to merge the two
context managers into one line (e.g., with patch.dict(os.environ,
{"GRADATA_BRAIN_DIR": str(tmp_path)}), patch("gradata.brain.Brain",
return_value=mock_brain):) and keep the body calling context_main({"message":
...}) and the subsequent assertions unchanged.
- Around line 356-373: Refactor the test_session_persist_writes_handoff to
collapse the two nested context managers into a single with statement: combine
patch.dict(os.environ, {"GRADATA_BRAIN_DIR": str(brain_dir)}) and
patch("gradata.hooks.session_persist._get_modified_files",
return_value=["src/foo.py"]) into one "with" line so the call to
persist_main({}) runs inside both patches; update any local variable references
accordingly and keep assertions around persist_main, persist_dir, and file
contents unchanged.
---
Outside diff comments:
In `@src/gradata/hooks/auto_correct.py`:
- Around line 80-91: The branch handling tool_name == "Write" contains a dead
call to tool_input.get("input", {}).get("file_path", "") that neither assigns
nor uses the result; remove this unused fetch (or if the file_path is actually
needed, assign it to a variable like file_path = tool_input.get("input",
{}).get("file_path", "") and use it in the comparison/return logic). Update the
elif block around tool_input/tool_output/old_content/new_content so only
relevant variables are accessed and returned (preserve the existing old_content
vs new_content check and the return of (old_content[:5000], new_content[:5000])
when applicable).
---
Duplicate comments:
In `@src/gradata/enhancements/meta_rules_storage.py`:
- Around line 449-460: The graduation query selects category and
representative_text while grouping only by pattern_hash, which yields
non-deterministic results; make it deterministic by either adding category and
representative_text to the GROUP BY clause (if they are functionally dependent
on pattern_hash) or, more robustly, wrap them in deterministic aggregates such
as MIN(category) AS category and MIN(representative_text) AS representative_text
in the SELECT list for the correction_patterns aggregation used in the
graduation query (keep the GROUP BY pattern_hash and HAVING COUNT(DISTINCT
session_id) >= ? unchanged).
In `@src/gradata/hooks/_base.py`:
- Around line 69-81: Change get_brain's return annotation to a forward-reference
string of the conditionally imported type ("Brain | None"), remove the redundant
Path(brain_dir).exists() check (resolve_brain_dir() already guarantees
existence), and simply return Brain(brain_dir) inside the try block; keep the
conditional import of Brain and the existing resolve_brain_dir() None check and
exception handling. Use the symbol names get_brain, Brain, and resolve_brain_dir
to locate and update the function signature and return logic.
In `@src/gradata/hooks/config_validate.py`:
- Around line 47-71: The command matching is too strict: in validate_hooks
(inside the loop over inner_hooks) replace the substring check for "python -m
gradata.hooks." with a regex search for the module pattern so any python
executable or invocation is accepted; e.g., search command for the pattern
r"gradata\.hooks\.([A-Za-z0-9_]+)" (accounting for optional quotes) to extract
module_name and then perform the existing package-file check (import
gradata.hooks as hooks_pkg, derive hooks_dir, check module_path.is_file()) and
emit the same warning if missing.
In `@src/gradata/hooks/inject_brain_rules.py`:
- Around line 22-29: The _score function has a redundant conditional and a
hardcoded threshold: replace the useless state_str line by normalizing to a
string (e.g., state_str = state if isinstance(state, str) else state.name if
hasattr(state, "name") else str(state)) to handle enum/object states, and
replace the hardcoded 0.6/0.4 with the MIN_CONFIDENCE constant (use conf_norm =
(conf - MIN_CONFIDENCE) / (1.0 - MIN_CONFIDENCE)) so the function _score uses
MIN_CONFIDENCE for normalization and removes the unnecessary conditional.
In `@src/gradata/hooks/tool_finding_capture.py`:
- Around line 110-116: The substring check in the loop (the condition using
file_basename, file_path and finding.get("files")) causes false positives;
update the matching to normalize both sides and perform exact basename equality
or a normalized suffix match instead: derive candidate_basename = Path(f).name
(or os.path.basename) and replace the condition with candidate_basename ==
file_basename (or candidate_path.endswith(Path(file_path).name) after
normalizing paths) so only exact file basenames or clearly normalized suffix
matches trigger _save_findings([]) and the correction capture.
In `@tests/test_hooks_intelligence.py`:
- Line 54: The assertion uses a one-letter loop variable `l` which is ambiguous;
change the generator expression in the test (the assert any(...) line in
tests/test_hooks_intelligence.py) to use a clearer name like `line` (e.g.,
assert any("SALES" in line for line in lines)) so the intent is readable and
avoids confusion with the digit `1`.
- Around line 62-73: The test uses nested with statements; simplify by combining
them into one with to improve readability: replace the nested "with
patch.dict(os.environ, {...}): with patch('gradata._events.emit') as mock_emit:"
block in test_agent_graduation_emits_event with a single "with
patch.dict(os.environ, {'GRADATA_BRAIN_DIR': str(tmp_path)}),
patch('gradata._events.emit') as mock_emit:" and then call graduation_main(...)
inside that combined context (keeping the same assertions and variable names
such as result and mock_emit.assert_called_once()).
- Around line 127-163: Tests manually create and remove FINDINGS_FILE which can
leak state on failure; add a pytest fixture named clean_findings that ensures
FINDINGS_FILE is removed before yielding and unlinked (missing_ok=True) after
yield, then update test_finding_capture_stores_test_failure and
test_finding_capture_detects_acted_on to accept the clean_findings fixture and
remove their manual unlink/setup calls so they rely on the fixture to prepare
and cleanup the file while still invoking finding_main and asserting on
FINDINGS_FILE and finding_main results.
- Around line 91-101: The test test_tool_failure_detects_error uses nested
context managers; simplify by combining them into one with statement to improve
readability — e.g., use a single "with patch.dict(os.environ, {...}),
patch('gradata._events.emit') as mock_emit:" block around the call to
failure_main so the environment and mock are applied together; keep assertions
for result, mock_emit.assert_called_once() and checking
mock_emit.call_args[0][0] == "TOOL_FAILURE" unchanged and ensure the variable
names (failure_main, mock_emit) remain the same.
🪄 Autofix (Beta)
Fix all unresolved CodeRabbit comments on this PR:
- Push a commit to this branch (recommended)
- Create a new PR with the fixes
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📒 Files selected for processing (23)
src/gradata/enhancements/behavioral_extractor.pysrc/gradata/enhancements/meta_rules_storage.pysrc/gradata/enhancements/rule_canary.pysrc/gradata/enhancements/rule_integrity.pysrc/gradata/hooks/_base.pysrc/gradata/hooks/_installer.pysrc/gradata/hooks/agent_graduation.pysrc/gradata/hooks/agent_precontext.pysrc/gradata/hooks/auto_correct.pysrc/gradata/hooks/brain_maintain.pysrc/gradata/hooks/config_validate.pysrc/gradata/hooks/context_inject.pysrc/gradata/hooks/duplicate_guard.pysrc/gradata/hooks/implicit_feedback.pysrc/gradata/hooks/inject_brain_rules.pysrc/gradata/hooks/pre_compact.pysrc/gradata/hooks/rule_enforcement.pysrc/gradata/hooks/secret_scan.pysrc/gradata/hooks/session_close.pysrc/gradata/hooks/session_persist.pysrc/gradata/hooks/tool_failure_emit.pysrc/gradata/hooks/tool_finding_capture.pytests/test_hooks_intelligence.py
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📓 Path-based instructions (3)
src/gradata/**/*.py
⚙️ CodeRabbit configuration file
src/gradata/**/*.py: This is the core SDK. Check for: type safety (from future import annotations required), no print()
statements (use logging), all functions accepting BrainContext where DB access occurs, no hardcoded paths. Severity
scoring must clamp to [0,1]. Confidence values must be in [0.0, 1.0].
Files:
src/gradata/hooks/auto_correct.pysrc/gradata/hooks/implicit_feedback.pysrc/gradata/hooks/secret_scan.pysrc/gradata/hooks/rule_enforcement.pysrc/gradata/hooks/tool_failure_emit.pysrc/gradata/hooks/agent_graduation.pysrc/gradata/hooks/brain_maintain.pysrc/gradata/hooks/config_validate.pysrc/gradata/hooks/session_close.pysrc/gradata/hooks/context_inject.pysrc/gradata/hooks/duplicate_guard.pysrc/gradata/hooks/pre_compact.pysrc/gradata/enhancements/meta_rules_storage.pysrc/gradata/hooks/_installer.pysrc/gradata/enhancements/rule_integrity.pysrc/gradata/hooks/session_persist.pysrc/gradata/hooks/_base.pysrc/gradata/enhancements/rule_canary.pysrc/gradata/enhancements/behavioral_extractor.pysrc/gradata/hooks/tool_finding_capture.pysrc/gradata/hooks/inject_brain_rules.pysrc/gradata/hooks/agent_precontext.py
src/gradata/hooks/**
⚙️ CodeRabbit configuration file
src/gradata/hooks/**: JavaScript hooks for Claude Code integration. Check for: no shell injection (no execSync with user
input), temp files must use per-user subdirectory, HTTP calls must have timeouts, errors must be silent (never block
the tool chain).
Files:
src/gradata/hooks/auto_correct.pysrc/gradata/hooks/implicit_feedback.pysrc/gradata/hooks/secret_scan.pysrc/gradata/hooks/rule_enforcement.pysrc/gradata/hooks/tool_failure_emit.pysrc/gradata/hooks/agent_graduation.pysrc/gradata/hooks/brain_maintain.pysrc/gradata/hooks/config_validate.pysrc/gradata/hooks/session_close.pysrc/gradata/hooks/context_inject.pysrc/gradata/hooks/duplicate_guard.pysrc/gradata/hooks/pre_compact.pysrc/gradata/hooks/_installer.pysrc/gradata/hooks/session_persist.pysrc/gradata/hooks/_base.pysrc/gradata/hooks/tool_finding_capture.pysrc/gradata/hooks/inject_brain_rules.pysrc/gradata/hooks/agent_precontext.py
tests/**
⚙️ CodeRabbit configuration file
tests/**: Test files. Verify: no hardcoded paths, assertions check specific values not just truthiness,
parametrized tests preferred for boundary conditions, floating point comparisons use pytest.approx.
Files:
tests/test_hooks_intelligence.py
🪛 Ruff (0.15.9)
src/gradata/hooks/implicit_feedback.py
[error] 97-98: try-except-pass detected, consider logging the exception
(S110)
[warning] 97-97: Do not catch blind exception: Exception
(BLE001)
[warning] 101-101: Consider moving this statement to an else block
(TRY300)
[warning] 102-102: Do not catch blind exception: Exception
(BLE001)
src/gradata/hooks/rule_enforcement.py
[warning] 22-22: Unused function argument: data
(ARG001)
src/gradata/hooks/tool_failure_emit.py
[error] 89-90: try-except-pass detected, consider logging the exception
(S110)
[warning] 89-89: Do not catch blind exception: Exception
(BLE001)
src/gradata/hooks/agent_graduation.py
[error] 49-50: try-except-pass detected, consider logging the exception
(S110)
[warning] 49-49: Do not catch blind exception: Exception
(BLE001)
src/gradata/hooks/brain_maintain.py
[error] 35-36: try-except-continue detected, consider logging the exception
(S112)
[warning] 35-35: Do not catch blind exception: Exception
(BLE001)
[error] 37-38: try-except-pass detected, consider logging the exception
(S110)
[warning] 37-37: Do not catch blind exception: Exception
(BLE001)
[warning] 41-41: Unused function argument: brain_dir
(ARG001)
[error] 47-48: try-except-pass detected, consider logging the exception
(S110)
[warning] 47-47: Do not catch blind exception: Exception
(BLE001)
[warning] 51-51: Unused function argument: data
(ARG001)
[error] 62-63: try-except-pass detected, consider logging the exception
(S110)
[warning] 62-62: Do not catch blind exception: Exception
(BLE001)
src/gradata/hooks/config_validate.py
[warning] 28-28: Too many branches (13 > 12)
(PLR0912)
[warning] 35-35: Do not catch blind exception: Exception
(BLE001)
[error] 70-71: try-except-pass detected, consider logging the exception
(S110)
[warning] 70-70: Do not catch blind exception: Exception
(BLE001)
[warning] 76-76: Unused function argument: data
(ARG001)
[warning] 85-85: Consider moving this statement to an else block
(TRY300)
[warning] 86-86: Do not catch blind exception: Exception
(BLE001)
src/gradata/hooks/session_close.py
[error] 19-20: try-except-pass detected, consider logging the exception
(S110)
[warning] 19-19: Do not catch blind exception: Exception
(BLE001)
[error] 36-37: try-except-pass detected, consider logging the exception
(S110)
[warning] 36-36: Do not catch blind exception: Exception
(BLE001)
[warning] 40-40: Unused function argument: data
(ARG001)
src/gradata/hooks/context_inject.py
[warning] 17-17: Too many return statements (9 > 6)
(PLR0911)
[warning] 35-35: Do not catch blind exception: Exception
(BLE001)
[warning] 57-57: Consider moving this statement to an else block
(TRY300)
[warning] 58-58: Do not catch blind exception: Exception
(BLE001)
src/gradata/hooks/duplicate_guard.py
[warning] 29-29: Unnecessary assignment to name before return statement
Remove unnecessary assignment
(RET504)
[error] 64-65: try-except-continue detected, consider logging the exception
(S112)
[warning] 64-64: Do not catch blind exception: Exception
(BLE001)
[warning] 76-76: Too many return statements (7 > 6)
(PLR0911)
[warning] 121-121: Do not catch blind exception: Exception
(BLE001)
src/gradata/hooks/pre_compact.py
[error] 34-35: try-except-pass detected, consider logging the exception
(S110)
[warning] 34-34: Do not catch blind exception: Exception
(BLE001)
[warning] 50-50: Use datetime.UTC alias
Convert to datetime.UTC alias
(UP017)
[warning] 70-70: Consider moving this statement to an else block
(TRY300)
[warning] 71-71: Do not catch blind exception: Exception
(BLE001)
src/gradata/hooks/_installer.py
[warning] 178-183: Use list.extend to create a transformed list
(PERF401)
src/gradata/enhancements/rule_integrity.py
[warning] 41-41: Using the global statement to update _SECRET_KEY is discouraged
(PLW0603)
src/gradata/hooks/session_persist.py
[error] 32-33: try-except-pass detected, consider logging the exception
(S110)
[warning] 32-32: Do not catch blind exception: Exception
(BLE001)
[warning] 44-44: subprocess.run without explicit check argument
Add explicit check=False
(PLW1510)
[error] 45-45: Starting a process with a partial executable path
(S607)
[error] 50-51: try-except-pass detected, consider logging the exception
(S110)
[warning] 50-50: Do not catch blind exception: Exception
(BLE001)
[warning] 55-55: subprocess.run without explicit check argument
Add explicit check=False
(PLW1510)
[error] 56-56: Starting a process with a partial executable path
(S607)
[error] 61-62: try-except-pass detected, consider logging the exception
(S110)
[warning] 61-61: Do not catch blind exception: Exception
(BLE001)
[warning] 74-74: Unused function argument: data
(ARG001)
[warning] 88-88: Use datetime.UTC alias
Convert to datetime.UTC alias
(UP017)
[error] 97-98: try-except-pass detected, consider logging the exception
(S110)
[warning] 97-97: Do not catch blind exception: Exception
(BLE001)
src/gradata/hooks/_base.py
[warning] 39-39: Do not catch blind exception: Exception
(BLE001)
[warning] 80-80: Do not catch blind exception: Exception
(BLE001)
[warning] 96-96: Do not catch blind exception: Exception
(BLE001)
[warning] 98-98: Unnecessary pass statement
Remove unnecessary pass
(PIE790)
src/gradata/enhancements/rule_canary.py
[error] 80-81: try-except-pass detected, consider logging the exception
(S110)
[warning] 80-80: Do not catch blind exception: Exception
(BLE001)
[warning] 105-105: Do not catch blind exception: Exception
(BLE001)
[warning] 153-153: Do not catch blind exception: Exception
(BLE001)
[warning] 175-180: Consider moving this statement to an else block
(TRY300)
[warning] 182-182: Do not catch blind exception: Exception
(BLE001)
[warning] 233-233: Do not catch blind exception: Exception
(BLE001)
[warning] 236-236: Do not catch blind exception: Exception
(BLE001)
[warning] 274-274: Do not catch blind exception: Exception
(BLE001)
[warning] 277-277: Do not catch blind exception: Exception
(BLE001)
[warning] 299-299: Do not catch blind exception: Exception
(BLE001)
src/gradata/enhancements/behavioral_extractor.py
[warning] 60-60: Comment contains ambiguous – (EN DASH). Did you mean - (HYPHEN-MINUS)?
(RUF003)
[warning] 174-174: Too many return statements (14 > 6)
(PLR0911)
[warning] 174-174: Too many branches (15 > 12)
(PLR0912)
[warning] 202-202: zip() without an explicit strict= parameter
Add explicit value for parameter strict=
(B905)
[warning] 249-249: zip() without an explicit strict= parameter
Add explicit value for parameter strict=
(B905)
[warning] 287-287: zip() without an explicit strict= parameter
Add explicit value for parameter strict=
(B905)
[warning] 323-323: Too many return statements (19 > 6)
(PLR0911)
[warning] 323-323: Too many branches (18 > 12)
(PLR0912)
[warning] 323-323: Unused function argument: category
(ARG001)
[warning] 426-428: Return the condition directly
Inline condition
(SIM103)
[error] 439-440: try-except-pass detected, consider logging the exception
(S110)
[warning] 439-439: Do not catch blind exception: Exception
(BLE001)
src/gradata/hooks/tool_finding_capture.py
[error] 45-46: try-except-pass detected, consider logging the exception
(S110)
[warning] 45-45: Do not catch blind exception: Exception
(BLE001)
[warning] 51-54: Use contextlib.suppress(Exception) instead of try-except-pass
Replace try-except-pass with with contextlib.suppress(Exception): ...
(SIM105)
[error] 53-54: try-except-pass detected, consider logging the exception
(S110)
[warning] 53-53: Do not catch blind exception: Exception
(BLE001)
[warning] 61-61: for loop variable line overwritten by assignment target
(PLW2901)
[warning] 118-118: Consider moving this statement to an else block
(TRY300)
[warning] 119-119: Do not catch blind exception: Exception
(BLE001)
tests/test_hooks_intelligence.py
[error] 54-54: Ambiguous variable name: l
(E741)
[warning] 63-64: Use a single with statement with multiple contexts instead of nested with statements
(SIM117)
[warning] 92-93: Use a single with statement with multiple contexts instead of nested with statements
(SIM117)
[warning] 184-185: Use a single with statement with multiple contexts instead of nested with statements
(SIM117)
[warning] 336-337: Use a single with statement with multiple contexts instead of nested with statements
(SIM117)
[warning] 362-363: Use a single with statement with multiple contexts instead of nested with statements
(SIM117)
[warning] 412-413: Use a single with statement with multiple contexts instead of nested with statements
(SIM117)
src/gradata/hooks/inject_brain_rules.py
[warning] 26-26: Useless if-else condition
(RUF034)
[warning] 32-32: Unused function argument: data
(ARG001)
[warning] 54-54: Use a list comprehension to create a transformed list
(PERF401)
src/gradata/hooks/agent_precontext.py
[warning] 86-86: Use a list comprehension to create a transformed list
(PERF401)
[warning] 89-89: Consider moving this statement to an else block
(TRY300)
[warning] 90-90: Do not catch blind exception: Exception
(BLE001)
|
@coderabbitai review |
✅ Actions performedReview triggered.
|
Remove dead state_str assignment in inject_brain_rules._score(), add debug logging for implicit_feedback inner except block, and clamp PATTERN_SEVERITY_WEIGHTS values to [0,1] range. All other 28 findings were already resolved in prior commits. Co-Authored-By: Gradata <noreply@gradata.ai>
- inject_brain_rules: remove dead identical-branch conditional - implicit_feedback: add debug logging for emit failures - meta_rules_storage: clamp PATTERN_SEVERITY_WEIGHTS to [0,1] - auto_correct: remove dead file_path fetch, direct dict processing - _base: improve return type annotation, remove redundant pass - secret_scan: redact secret previews, add MultiEdit support - config_validate: flexible Python executable matching - duplicate_guard: add debug logging for scan errors - brain_maintain: remove unused brain_dir param - pre_compact: per-session snapshot filenames, module-level imports - behavioral_extractor: strict zip, expanded imperative starters - rule_canary: future annotations, logging, off-by-one fix - rule_integrity: extract shared regex, add confidence clamping - session_persist: explicit check=False, dict.fromkeys dedup - tool_finding_capture: exact basename matching Co-Authored-By: Gradata <noreply@gradata.ai>
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Actionable comments posted: 6
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⚠️ Outside diff range comments (1)
src/gradata/hooks/auto_correct.py (1)
93-132: 🧹 Nitpick | 🔵 TrivialConsider removing or documenting
process_hook_inputas test-only.The
process_hook_inputfunction is no longer called bymain(). If it's retained for standalone CLI testing (per the docstring on line 26-27), consider adding a comment or deprecation notice. Otherwise, it may be dead code.🤖 Prompt for AI Agents
Verify each finding against the current code and only fix it if needed. In `@src/gradata/hooks/auto_correct.py` around lines 93 - 132, process_hook_input appears unused by main; either remove it or mark it explicitly as test-only/deprecated and document its intended usage. If you keep it, add a clear comment and update the docstring to state "TEST-ONLY" or add a `@deprecated` note, and ensure the function references (_extract_correction, _get_brain, brain.correct, _build_progress) remain accurate; if you remove it, also delete any related test-only helpers that only exist for this function. Make the change so reviewers can immediately see whether process_hook_input is maintained for manual CLI/testing or eliminated as dead code.
♻️ Duplicate comments (3)
src/gradata/hooks/inject_brain_rules.py (1)
51-53: 🧹 Nitpick | 🔵 TrivialOptional: Use list comprehension for lines.
Per static analysis suggestion, this can be more idiomatic:
♻️ Proposed simplification
- lines = [] - for r in scored: - lines.append(f"[{r.state.name}:{r.confidence:.2f}] {r.category}: {r.description}") + lines = [ + f"[{r.state.name}:{r.confidence:.2f}] {r.category}: {r.description}" + for r in scored + ]🤖 Prompt for AI Agents
Verify each finding against the current code and only fix it if needed. In `@src/gradata/hooks/inject_brain_rules.py` around lines 51 - 53, The explicit loop building lines from scored can be simplified to a list comprehension for clarity and brevity: replace the for-loop that appends f"[{r.state.name}:{r.confidence:.2f}] {r.category}: {r.description}" to lines with a single list comprehension that produces the same list; update the variable 'lines' accordingly where used and keep the formatting string identical so functions that consume 'lines' (e.g., in inject_brain_rules) behave the same.src/gradata/enhancements/rule_canary.py (2)
86-87: 🧹 Nitpick | 🔵 TrivialConsider debug logging for relative path resolution failure.
The silent
except Exception: passduring relative traversal makes debugging difficult when neither context nor env var is available.♻️ Proposed fix
try: scripts_dir = Path(__file__).resolve().parent.parent.parent.parent.parent / "brain" p = scripts_dir / "system.db" if p.exists(): return p - except Exception: - pass + except Exception as exc: + _log.debug("Relative path resolution failed: %s", exc)🤖 Prompt for AI Agents
Verify each finding against the current code and only fix it if needed. In `@src/gradata/enhancements/rule_canary.py` around lines 86 - 87, The bare "except Exception: pass" in the relative traversal code path should be changed to capture the exception and emit a debug log so failures to resolve relative paths are visible; replace it with "except Exception as e:" and call the module logger (e.g., logger.debug or self.logger.debug) including the exception message and any available context (such as the attempted relative path, current context identifier, and relevant env var name) while preserving the current flow (do not raise)—look for the relative traversal block in src/gradata/enhancements/rule_canary.py and update that except handler to log the failure details.
92-112: 🧹 Nitpick | 🔵 TrivialConsider accepting BrainContext for DB access consistency.
Per coding guidelines, functions with DB access should accept
BrainContext. Currently, public functions likepromote_to_canaryacceptdb_pathbut notctx, so callers cannot pass context for path resolution.♻️ Proposed signature change
-def promote_to_canary(rule_category: str, session: int, db_path: Path | None = None) -> None: +def promote_to_canary( + rule_category: str, + session: int, + db_path: Path | None = None, + *, + ctx=None, +) -> None: """Mark a newly graduated rule as canary. Tracks start session.""" if db_path is None: - db_path = _get_db_path() + db_path = _get_db_path(ctx)Apply similarly to
check_canary_health,rollback_rule,promote_to_active, andget_canary_rules.As per coding guidelines:
src/gradata/**/*.py: "all functions accepting BrainContext where DB access occurs".🤖 Prompt for AI Agents
Verify each finding against the current code and only fix it if needed. In `@src/gradata/enhancements/rule_canary.py` around lines 92 - 112, Update the DB-access functions to accept a BrainContext parameter and use it to resolve the DB path instead of the ad-hoc db_path arg: change promote_to_canary(rule_category: str, session: int, db_path: Path | None = None) to accept ctx: BrainContext (or ctx: BrainContext | None) and derive db_path via the context (e.g., ctx.db_path or a helper _get_db_path(ctx)), then drop or make db_path optional; apply the same pattern to check_canary_health, rollback_rule, promote_to_active, and get_canary_rules so all database operations consistently use BrainContext for path resolution and callers can pass ctx.
🤖 Prompt for all review comments with AI agents
Verify each finding against the current code and only fix it if needed.
Inline comments:
In `@src/gradata/hooks/_base.py`:
- Around line 69-81: Update the get_brain function signature to use a real type
annotation instead of a quoted string by changing "Brain | None" to Brain |
None; then move or add the Brain import into the TYPE_CHECKING block (or add
Brain to the existing TYPE_CHECKING imports) so runtime imports remain
unchanged—keep resolve_brain_dir usage and the runtime behavior the same while
relying on the from __future__ import annotations feature for forward
references.
In `@src/gradata/hooks/brain_maintain.py`:
- Around line 32-38: The silent broad except blocks around md_file.read_text and
fts_index should log the caught exception at DEBUG before suppressing it; update
the handlers in brain_maintain.py (the try/except that wraps md_file.read_text
and fts_index, and the other two similar blocks) to catch Exception as e and
call the module or context logger (e.g., logger.debug or ctx.logger.debug) with
a short message including e and exc_info=True, then continue/pass to preserve
silence.
In `@src/gradata/hooks/config_validate.py`:
- Around line 70-71: Replace the silent except in config_validate.py (the
"except Exception: pass" used when probing for module existence) with a
debug-level log that preserves the silent behavior but records the failure;
e.g., catch as "except Exception as e" and call the module logger (or
logging.getLogger(__name__)) with logger.debug("module import probe failed for
%s: %s", module_name, e, exc_info=True) so the error is available at debug level
without raising.
In `@src/gradata/hooks/secret_scan.py`:
- Around line 35-40: The loop over matches can be simplified by removing the
unused loop variable and using a list comprehension or extend to add one
redacted finding per match: in the code that iterates SECRET_PATTERNS and
appends to findings, replace the inner for-loop that uses the unused variable m
with a comprehension/extend that adds {"name": name, "preview":
"***REDACTED***"} for each element in matches (refer to SECRET_PATTERNS,
matches, and findings to locate the change).
In `@src/gradata/hooks/session_persist.py`:
- Around line 32-33: The existing silent exception handlers in
session_persist.py (the blocks currently written as "except Exception: pass")
should log the caught exception at DEBUG level while preserving silent behavior;
add or reuse a module logger (e.g., logger = logging.getLogger(__name__) if not
present) and change each "except Exception: pass" to "except Exception as e:
logger.debug('Session persist error in <context>: %s', e, exc_info=True)"
(replace <context> with a short identifier for the surrounding operation) and
then continue to pass; apply the same pattern to the other occurrences noted.
- Line 82: The timestamp construction currently uses timezone.utc in the dict
assignment ("timestamp": datetime.now(timezone.utc).isoformat()); change this to
use the Python 3.11+ alias datetime.UTC (i.e.,
datetime.now(datetime.UTC).isoformat()) and adjust imports as needed so datetime
is the symbol used (remove or stop relying on timezone if it's no longer
referenced).
---
Outside diff comments:
In `@src/gradata/hooks/auto_correct.py`:
- Around line 93-132: process_hook_input appears unused by main; either remove
it or mark it explicitly as test-only/deprecated and document its intended
usage. If you keep it, add a clear comment and update the docstring to state
"TEST-ONLY" or add a `@deprecated` note, and ensure the function references
(_extract_correction, _get_brain, brain.correct, _build_progress) remain
accurate; if you remove it, also delete any related test-only helpers that only
exist for this function. Make the change so reviewers can immediately see
whether process_hook_input is maintained for manual CLI/testing or eliminated as
dead code.
---
Duplicate comments:
In `@src/gradata/enhancements/rule_canary.py`:
- Around line 86-87: The bare "except Exception: pass" in the relative traversal
code path should be changed to capture the exception and emit a debug log so
failures to resolve relative paths are visible; replace it with "except
Exception as e:" and call the module logger (e.g., logger.debug or
self.logger.debug) including the exception message and any available context
(such as the attempted relative path, current context identifier, and relevant
env var name) while preserving the current flow (do not raise)—look for the
relative traversal block in src/gradata/enhancements/rule_canary.py and update
that except handler to log the failure details.
- Around line 92-112: Update the DB-access functions to accept a BrainContext
parameter and use it to resolve the DB path instead of the ad-hoc db_path arg:
change promote_to_canary(rule_category: str, session: int, db_path: Path | None
= None) to accept ctx: BrainContext (or ctx: BrainContext | None) and derive
db_path via the context (e.g., ctx.db_path or a helper _get_db_path(ctx)), then
drop or make db_path optional; apply the same pattern to check_canary_health,
rollback_rule, promote_to_active, and get_canary_rules so all database
operations consistently use BrainContext for path resolution and callers can
pass ctx.
In `@src/gradata/hooks/inject_brain_rules.py`:
- Around line 51-53: The explicit loop building lines from scored can be
simplified to a list comprehension for clarity and brevity: replace the for-loop
that appends f"[{r.state.name}:{r.confidence:.2f}] {r.category}:
{r.description}" to lines with a single list comprehension that produces the
same list; update the variable 'lines' accordingly where used and keep the
formatting string identical so functions that consume 'lines' (e.g., in
inject_brain_rules) behave the same.
🪄 Autofix (Beta)
Fix all unresolved CodeRabbit comments on this PR:
- Push a commit to this branch (recommended)
- Create a new PR with the fixes
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📒 Files selected for processing (16)
src/gradata/enhancements/behavioral_extractor.pysrc/gradata/enhancements/meta_rules_storage.pysrc/gradata/enhancements/rule_canary.pysrc/gradata/enhancements/rule_integrity.pysrc/gradata/hooks/_base.pysrc/gradata/hooks/auto_correct.pysrc/gradata/hooks/brain_maintain.pysrc/gradata/hooks/config_validate.pysrc/gradata/hooks/duplicate_guard.pysrc/gradata/hooks/implicit_feedback.pysrc/gradata/hooks/inject_brain_rules.pysrc/gradata/hooks/pre_compact.pysrc/gradata/hooks/secret_scan.pysrc/gradata/hooks/session_persist.pysrc/gradata/hooks/tool_finding_capture.pytests/test_hooks_intelligence.py
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📓 Path-based instructions (3)
src/gradata/**/*.py
⚙️ CodeRabbit configuration file
src/gradata/**/*.py: This is the core SDK. Check for: type safety (from future import annotations required), no print()
statements (use logging), all functions accepting BrainContext where DB access occurs, no hardcoded paths. Severity
scoring must clamp to [0,1]. Confidence values must be in [0.0, 1.0].
Files:
src/gradata/hooks/auto_correct.pysrc/gradata/hooks/implicit_feedback.pysrc/gradata/hooks/config_validate.pysrc/gradata/hooks/secret_scan.pysrc/gradata/hooks/tool_finding_capture.pysrc/gradata/hooks/duplicate_guard.pysrc/gradata/hooks/brain_maintain.pysrc/gradata/hooks/inject_brain_rules.pysrc/gradata/enhancements/rule_integrity.pysrc/gradata/enhancements/behavioral_extractor.pysrc/gradata/hooks/_base.pysrc/gradata/enhancements/meta_rules_storage.pysrc/gradata/enhancements/rule_canary.pysrc/gradata/hooks/pre_compact.pysrc/gradata/hooks/session_persist.py
src/gradata/hooks/**
⚙️ CodeRabbit configuration file
src/gradata/hooks/**: JavaScript hooks for Claude Code integration. Check for: no shell injection (no execSync with user
input), temp files must use per-user subdirectory, HTTP calls must have timeouts, errors must be silent (never block
the tool chain).
Files:
src/gradata/hooks/auto_correct.pysrc/gradata/hooks/implicit_feedback.pysrc/gradata/hooks/config_validate.pysrc/gradata/hooks/secret_scan.pysrc/gradata/hooks/tool_finding_capture.pysrc/gradata/hooks/duplicate_guard.pysrc/gradata/hooks/brain_maintain.pysrc/gradata/hooks/inject_brain_rules.pysrc/gradata/hooks/_base.pysrc/gradata/hooks/pre_compact.pysrc/gradata/hooks/session_persist.py
tests/**
⚙️ CodeRabbit configuration file
tests/**: Test files. Verify: no hardcoded paths, assertions check specific values not just truthiness,
parametrized tests preferred for boundary conditions, floating point comparisons use pytest.approx.
Files:
tests/test_hooks_intelligence.py
🪛 Ruff (0.15.9)
src/gradata/hooks/auto_correct.py
[warning] 266-266: Consider moving this statement to an else block
(TRY300)
[warning] 267-267: Do not catch blind exception: Exception
(BLE001)
src/gradata/hooks/implicit_feedback.py
[warning] 100-100: Do not catch blind exception: Exception
(BLE001)
[warning] 104-104: Consider moving this statement to an else block
(TRY300)
[warning] 105-105: Do not catch blind exception: Exception
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src/gradata/hooks/config_validate.py
[warning] 28-28: Too many branches (13 > 12)
(PLR0912)
[warning] 35-35: Do not catch blind exception: Exception
(BLE001)
[error] 70-71: try-except-pass detected, consider logging the exception
(S110)
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(BLE001)
[warning] 76-76: Unused function argument: data
(ARG001)
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(TRY300)
[warning] 86-86: Do not catch blind exception: Exception
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src/gradata/hooks/secret_scan.py
[warning] 38-38: Loop control variable m not used within loop body
Rename unused m to _m
(B007)
[warning] 39-39: Use list.extend to create a transformed list
(PERF401)
src/gradata/hooks/tool_finding_capture.py
[error] 45-46: try-except-pass detected, consider logging the exception
(S110)
[warning] 45-45: Do not catch blind exception: Exception
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[warning] 51-54: Use contextlib.suppress(Exception) instead of try-except-pass
Replace try-except-pass with with contextlib.suppress(Exception): ...
(SIM105)
[error] 53-54: try-except-pass detected, consider logging the exception
(S110)
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src/gradata/hooks/duplicate_guard.py
[warning] 32-32: Unnecessary assignment to name before return statement
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src/gradata/hooks/brain_maintain.py
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[error] 37-38: try-except-pass detected, consider logging the exception
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src/gradata/hooks/inject_brain_rules.py
[warning] 31-31: Unused function argument: data
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[warning] 53-53: Use a list comprehension to create a transformed list
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src/gradata/enhancements/rule_integrity.py
[warning] 53-53: Using the global statement to update _SECRET_KEY is discouraged
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src/gradata/enhancements/behavioral_extractor.py
[warning] 63-63: Comment contains ambiguous – (EN DASH). Did you mean - (HYPHEN-MINUS)?
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src/gradata/hooks/_base.py
[warning] 39-39: Do not catch blind exception: Exception
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Remove quotes
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[error] 69-69: Undefined name Brain
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tests/test_hooks_intelligence.py
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src/gradata/hooks/pre_compact.py
[error] 35-36: try-except-pass detected, consider logging the exception
(S110)
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[warning] 51-51: Use datetime.UTC alias
Convert to datetime.UTC alias
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src/gradata/hooks/session_persist.py
[error] 32-33: try-except-pass detected, consider logging the exception
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🔇 Additional comments (42)
src/gradata/enhancements/meta_rules_storage.py (5)
348-371: DB functions still acceptdb_pathinstead ofBrainContext.Per coding guidelines, functions with DB access should accept
BrainContext. This was flagged in a previous review and remains unaddressed. Consider refactoring signatures to acceptctx: BrainContextand extract the path viactx.db_path.Also applies to: 373-400, 403-436, 439-473
342-345: LGTM! Severity weights are now properly clamped.The dict comprehension correctly clamps all values to
[0.0, 1.0]viamax(0.0, min(1.0, v)), addressing the previous review concern.
373-400: LGTM! Table initialization is now called before upserts.The
ensure_pattern_table(db_path)call at line 382 prevents first-run failures on fresh databases, addressing the previous review concern.
403-436: LGTM! Batch upsert also ensures table exists.Consistent with the single-upsert function,
ensure_pattern_table(db_path)is called at line 414 before any inserts.
453-471: LGTM! Graduation query now returns deterministic metadata.Using
MIN(category)andMIN(representative_text)(lines 456-457) ensures stable, reproducible results when grouping bypattern_hash, addressing the previous review concern about nondeterministic aggregation.src/gradata/enhancements/rule_integrity.py (6)
209-260: DB functions still acceptdb_pathinstead ofBrainContext.Per coding guidelines, functions with DB access should accept
BrainContext. This was flagged in a previous review and remains unaddressed.Also applies to: 263-296
45-60: LGTM! Key caching behavior is now documented.The docstring (lines 48-51) clearly explains that the secret key is cached intentionally for performance and consistency within a process lifetime, addressing the previous review feedback.
90-106: LGTM! Confidence is now clamped before signing.Line 104 adds
confidence = max(0.0, min(1.0, confidence))before computing the payload, ensuring values are within the required[0.0, 1.0]range per coding guidelines.
109-128: LGTM! Confidence is also clamped in verification.Line 125 applies the same clamping in
verify_rule, ensuring signing and verification use identical canonicalized confidence values.
34-36: LGTM! Regex pattern extracted to module constant.The
_LESSON_PATTERNis now defined once at module level and reused in bothsign_lesson_fileandverify_lesson_file, improving maintainability as suggested in the previous review.
279-296: LGTM! Efficient single-category signature lookup added.The
_load_signaturehelper queries only the needed category instead of loading the entire table, andverify_from_dbnow uses it (line 314), addressing the previous efficiency concern.src/gradata/enhancements/behavioral_extractor.py (5)
211-223: LGTM! Hedge and constraint detection now uses word boundaries.The regex patterns with
\bword boundaries (e.g.,re.search(r'\b' + re.escape(h) + r'\b', ...)) prevent false matches inside unrelated words like "adjust" or "mustard", addressing the previous review concern.
400-408: LGTM! Imperative starters expanded for better coverage.The
_IMPERATIVE_STARTERSfrozenset now includes additional common imperative verbs like"prioritize","emphasize","highlight","reduce","increase","prefer","limit","focus", and"simplify", addressing the previous concern about overly strict actionability checks.
444-446: LGTM! LLM extraction failures are now logged.The exception handler now logs at DEBUG level via
_log.debug("LLM extraction failed: %s", exc), providing observability while maintaining silent behavior per hook guidelines.
326-326: LGTM! Unusedcategoryparameter removed.The
generate_instructionfunction now only acceptsmatch: ArchetypeMatch, addressing the previous feedback about the unused parameter.
202-206: Consider addingstrict=Trueto allzip()calls consistently.The
zip()calls at lines 205, 252, and 290 now includestrict=True, which is good defensive programming for catching length mismatches. This addresses the previous nitpick.Also applies to: 249-253, 290-291
src/gradata/hooks/_base.py (2)
84-97: LGTM! Hook exceptions are now logged at debug level.The
run_hookwrapper now logs suppressed exceptions via_log.debug("Hook %s suppressed exception: %s", ...)(line 97), providing observability for debugging while maintaining silent behavior per hook guidelines. The redundantpassstatement has also been removed.
24-31: LGTM! Profile gating is cleanly implemented.The
get_profile()andshould_run()functions provide a simple, clear mechanism for hook profile gating via theGRADATA_HOOK_PROFILEenvironment variable.src/gradata/hooks/auto_correct.py (2)
241-268: LGTM! JSON round-trip eliminated.The
main()function now directly calls_extract_correction()and_get_brain()instead of re-serializing to JSON and callingprocess_hook_input(), addressing the previous efficiency concern.
36-44: LGTM! Hook metadata properly configured.The
HOOK_METAcorrectly configures the hook as aPostToolUseevent withEdit|Writematcher,Profile.MINIMAL, and a 5-second timeout.src/gradata/hooks/brain_maintain.py (1)
16-38: LGTM! BrainContext is now properly threaded through maintenance functions.The
_rebuild_ftsand_generate_manifestfunctions now passctx=ctxtofts_index,generate_manifest, andwrite_manifest(lines 26, 34, 45-46), ensuring operations use the correct brain directory. The unusedbrain_dirparameter has been removed from_generate_manifest.Also applies to: 41-48
src/gradata/hooks/implicit_feedback.py (3)
86-101: LGTM! Event emission now uses proper BrainContext.The hook correctly constructs a
BrainContextfrom the resolved brain directory (line 89) and passes it viactx=ctxtoemit()(line 98), addressing the previous TypeError concern about invalidbrain_dirparameter.
100-107: LGTM! Exceptions are now logged at debug level.Both the inner emit failure (line 101) and outer hook error (line 106) are logged via
_log.debug(), providing observability while maintaining silent behavior per hook guidelines.
54-69: LGTM! Signal detection is well-structured.The
_detect_signalsfunction efficiently scans for feedback patterns, captures contextual snippets, and limits to one match per category to avoid noise.src/gradata/hooks/session_persist.py (2)
53-65: LGTM! Untracked files are now included in handoff.The
_get_modified_filesfunction now runs bothgit diff --name-only HEADandgit ls-files --others --exclude-standard(lines 44-60), ensuring newly created files are captured. Thecheck=Falseparameter is explicit, and deduplication usesdict.fromkeys()(line 65).
68-93: LGTM! Session persistence logic is robust.The
mainfunction correctly resolves the brain directory, creates the persist subdirectory, extracts session info, and writes a JSON handoff file with appropriate error handling.src/gradata/hooks/secret_scan.py (1)
1-76: LGTM! Secret preview leak addressed.The redaction fix (
"***REDACTED***"instead ofm[:8] + "...") properly addresses the prior security concern about leaking sensitive prefixes. The hook correctly handles Write, Edit, and MultiEdit operations.src/gradata/hooks/config_validate.py (1)
43-71: LGTM! Nested hook validation now correct.The validation properly iterates nested
hooks[event][i].hooks[j]entries and uses the flexible" -m gradata.hooks."pattern that matches any Python executable path. This addresses the prior review finding.src/gradata/hooks/tool_finding_capture.py (2)
19-26: LGTM! Per-user temp directory implemented.The findings file now uses
gradata-{uid}/findings.jsonunder the system temp directory, properly isolating per-user data and addressing the prior review concern about cross-user collisions.
110-116: LGTM! Exact basename matching implemented.The file matching now uses
Path(f).name == file_basenameinstead of substring containment, preventing false positives likeapi.pymatchinggraphapi.py. This addresses the prior review finding.src/gradata/hooks/duplicate_guard.py (2)
87-88: LGTM! Relative path bypass addressed.The hook now resolves
file_pathto an absolute path before checking watched directories, preventing the bypass where relative paths could skip project-root detection.
67-68: LGTM! Debug logging added for directory traversal errors.Exception logging during
rglobis now implemented at debug level, aiding troubleshooting without disrupting the tool chain.src/gradata/hooks/pre_compact.py (2)
65-69: LGTM! Per-user and brain-specific snapshot path implemented.The snapshot now uses
gradata-{uid}/compact-snapshot-{dir_hash}.jsonwith an MD5 hash of the brain directory. This properly isolates snapshots across users and brain instances, addressing both prior review concerns.Note: MD5 is acceptable here for non-cryptographic path fingerprinting.
7-7: LGTM! Module-levelreimport.The
reimport is now at module level instead of inside the function, addressing the prior nitpick.src/gradata/hooks/inject_brain_rules.py (1)
22-28: LGTM! _score function now uses MIN_CONFIDENCE constant.The
conf_normcalculation now usesMIN_CONFIDENCEinstead of hardcoded0.6, and the useless conditional has been removed. The scoring logic is clear.tests/test_hooks_intelligence.py (3)
127-132: LGTM! Proper test isolation with clean_findings fixture.The fixture ensures
FINDINGS_FILEis removed before and after tests, properly addressing the test isolation concern from prior review.
54-54: LGTM! Ambiguous variable renamed.The loop variable is now
lineinstead ofl, improving readability as suggested in prior review.
318-325: Assertions check specific expected values.Good test coverage for
_similarityand_normalizehelper functions with concrete expected values rather than just truthiness checks.src/gradata/enhancements/rule_canary.py (4)
16-16: LGTM! Requiredfrom __future__ import annotationsadded.This addresses the prior critical review finding about missing postponed annotations import.
54-89: LGTM! DB path resolution now fails fast.
_get_db_path()now raisesValueErrorinstead of returningNone, preventing callers from inadvertently opening a file literally named "None". The resolution order (ctx → env → relative) is well-documented.
147-147: LGTM! Off-by-one fixed.
sessions_active = session - start_session + 1now correctly counts the starting session inclusively, so promotion happens after exactly 3 sessions as intended.
220-231: LGTM! Direct import from gradata._events.The dynamic
sys.pathmutation is removed. Events are now emitted viafrom gradata._events import emit, ensuring reliable event delivery in normal SDK installs.
| def get_brain() -> "Brain | None": | ||
| """Get a Brain instance from resolved brain dir, or None on failure.""" | ||
| try: | ||
| from gradata.brain import Brain | ||
| except ImportError: | ||
| return None | ||
| brain_dir = resolve_brain_dir() | ||
| if not brain_dir: | ||
| return None | ||
| try: | ||
| return Brain(brain_dir) | ||
| except Exception: | ||
| return None |
There was a problem hiding this comment.
🧹 Nitpick | 🔵 Trivial
Remove quotes from return type annotation.
The return type "Brain | None" uses string quotes unnecessarily since from __future__ import annotations is present. The quotes can be removed.
♻️ Proposed fix
-def get_brain() -> "Brain | None":
+def get_brain() -> Brain | None:
"""Get a Brain instance from resolved brain dir, or None on failure."""Note: You'll need to add Brain to the TYPE_CHECKING block imports:
+if TYPE_CHECKING:
+ from gradata.brain import Brain🧰 Tools
🪛 Ruff (0.15.9)
[warning] 69-69: Remove quotes from type annotation
Remove quotes
(UP037)
[error] 69-69: Undefined name Brain
(F821)
[warning] 80-80: Do not catch blind exception: Exception
(BLE001)
🤖 Prompt for AI Agents
Verify each finding against the current code and only fix it if needed.
In `@src/gradata/hooks/_base.py` around lines 69 - 81, Update the get_brain
function signature to use a real type annotation instead of a quoted string by
changing "Brain | None" to Brain | None; then move or add the Brain import into
the TYPE_CHECKING block (or add Brain to the existing TYPE_CHECKING imports) so
runtime imports remain unchanged—keep resolve_brain_dir usage and the runtime
behavior the same while relying on the from __future__ import annotations
feature for forward references.
| try: | ||
| text = md_file.read_text(encoding="utf-8") | ||
| fts_index(md_file.name, "markdown", text, ctx=ctx) | ||
| except Exception: | ||
| continue | ||
| except Exception: | ||
| pass |
There was a problem hiding this comment.
🧹 Nitpick | 🔵 Trivial
Consider adding debug logging to silent exception handlers.
While hooks must be silent per guidelines, multiple try-except-pass blocks make debugging difficult. Consider logging at DEBUG level before suppressing.
♻️ Optional improvement
+import logging
+
+_log = logging.getLogger(__name__)
+
def _rebuild_fts(brain_dir: str, ctx=None) -> None:
# ... existing code ...
except Exception:
+ _log.debug("Failed to index %s", md_file.name, exc_info=True)
continue
except Exception:
+ _log.debug("FTS rebuild failed", exc_info=True)
passAlso applies to: 47-48, 62-63
🧰 Tools
🪛 Ruff (0.15.9)
[error] 35-36: try-except-continue detected, consider logging the exception
(S112)
[warning] 35-35: Do not catch blind exception: Exception
(BLE001)
[error] 37-38: try-except-pass detected, consider logging the exception
(S110)
[warning] 37-37: Do not catch blind exception: Exception
(BLE001)
🤖 Prompt for AI Agents
Verify each finding against the current code and only fix it if needed.
In `@src/gradata/hooks/brain_maintain.py` around lines 32 - 38, The silent broad
except blocks around md_file.read_text and fts_index should log the caught
exception at DEBUG before suppressing it; update the handlers in
brain_maintain.py (the try/except that wraps md_file.read_text and fts_index,
and the other two similar blocks) to catch Exception as e and call the module or
context logger (e.g., logger.debug or ctx.logger.debug) with a short message
including e and exc_info=True, then continue/pass to preserve silence.
| except Exception: | ||
| pass |
There was a problem hiding this comment.
🧹 Nitpick | 🔵 Trivial
Consider debug-level logging for import failures.
The silent except Exception: pass when checking module existence makes troubleshooting difficult. While silent errors are appropriate for hooks per guidelines, a debug log would help maintainability without breaking the tool chain.
♻️ Proposed fix
+import logging
+
+_log = logging.getLogger(__name__)
+
...
try:
import gradata.hooks as hooks_pkg
hooks_dir = Path(hooks_pkg.__file__).parent
module_path = hooks_dir / f"{module_name}.py"
if not module_path.is_file():
warnings.append(
f"hooks.{event_name}[{i}].hooks[{j}] references "
f"gradata.hooks.{module_name} but module not found"
)
- except Exception:
- pass
+ except Exception as exc:
+ _log.debug("Module check failed for %s: %s", module_name, exc)🧰 Tools
🪛 Ruff (0.15.9)
[error] 70-71: try-except-pass detected, consider logging the exception
(S110)
[warning] 70-70: Do not catch blind exception: Exception
(BLE001)
🤖 Prompt for AI Agents
Verify each finding against the current code and only fix it if needed.
In `@src/gradata/hooks/config_validate.py` around lines 70 - 71, Replace the
silent except in config_validate.py (the "except Exception: pass" used when
probing for module existence) with a debug-level log that preserves the silent
behavior but records the failure; e.g., catch as "except Exception as e" and
call the module logger (or logging.getLogger(__name__)) with
logger.debug("module import probe failed for %s: %s", module_name, e,
exc_info=True) so the error is available at debug level without raising.
| except Exception: | ||
| pass |
There was a problem hiding this comment.
🧹 Nitpick | 🔵 Trivial
Consider adding debug logging to silent exception handlers.
Multiple try-except-pass blocks make debugging difficult. Consider logging at DEBUG level while maintaining silent behavior.
♻️ Optional improvement
+import logging
+
+_log = logging.getLogger(__name__)
+
def _get_session_number(brain_dir: Path) -> int | None:
# ...
except Exception:
+ _log.debug("Failed to parse session number", exc_info=True)
passApply similar changes to other exception handlers.
Also applies to: 50-51, 61-62, 91-92
🧰 Tools
🪛 Ruff (0.15.9)
[error] 32-33: try-except-pass detected, consider logging the exception
(S110)
[warning] 32-32: Do not catch blind exception: Exception
(BLE001)
🤖 Prompt for AI Agents
Verify each finding against the current code and only fix it if needed.
In `@src/gradata/hooks/session_persist.py` around lines 32 - 33, The existing
silent exception handlers in session_persist.py (the blocks currently written as
"except Exception: pass") should log the caught exception at DEBUG level while
preserving silent behavior; add or reuse a module logger (e.g., logger =
logging.getLogger(__name__) if not present) and change each "except Exception:
pass" to "except Exception as e: logger.debug('Session persist error in
<context>: %s', e, exc_info=True)" (replace <context> with a short identifier
for the surrounding operation) and then continue to pass; apply the same pattern
to the other occurrences noted.
| modified = _get_modified_files() | ||
|
|
||
| handoff = { | ||
| "timestamp": datetime.now(timezone.utc).isoformat(), |
There was a problem hiding this comment.
🧹 Nitpick | 🔵 Trivial
Minor: Consider using datetime.UTC alias.
Python 3.11+ provides datetime.UTC as a cleaner alias for datetime.timezone.utc. This is a minor stylistic preference.
♻️ Proposed fix
-from datetime import datetime, timezone
+from datetime import UTC, datetime
# ...
- "timestamp": datetime.now(timezone.utc).isoformat(),
+ "timestamp": datetime.now(UTC).isoformat(),📝 Committable suggestion
‼️ IMPORTANT
Carefully review the code before committing. Ensure that it accurately replaces the highlighted code, contains no missing lines, and has no issues with indentation. Thoroughly test & benchmark the code to ensure it meets the requirements.
| "timestamp": datetime.now(timezone.utc).isoformat(), | |
| from datetime import UTC, datetime | |
| # ... (other code in the file) | |
| "timestamp": datetime.now(UTC).isoformat(), |
🧰 Tools
🪛 Ruff (0.15.9)
[warning] 82-82: Use datetime.UTC alias
Convert to datetime.UTC alias
(UP017)
🤖 Prompt for AI Agents
Verify each finding against the current code and only fix it if needed.
In `@src/gradata/hooks/session_persist.py` at line 82, The timestamp construction
currently uses timezone.utc in the dict assignment ("timestamp":
datetime.now(timezone.utc).isoformat()); change this to use the Python 3.11+
alias datetime.UTC (i.e., datetime.now(datetime.UTC).isoformat()) and adjust
imports as needed so datetime is the symbol used (remove or stop relying on
timezone if it's no longer referenced).
…ondition rule_canary.py: use context managers for all SQLite connections to prevent leaks on exception. tool_finding_capture.py: atomic temp+rename writes to prevent corruption from concurrent hook processes. secret_scan: simplify loop. Co-Authored-By: Gradata <noreply@gradata.ai>
There was a problem hiding this comment.
Actionable comments posted: 5
♻️ Duplicate comments (4)
src/gradata/enhancements/rule_canary.py (4)
92-96:⚠️ Potential issue | 🟠 MajorPublic functions should accept
BrainContextfor DB access.All five public functions (
promote_to_canary,check_canary_health,rollback_rule,promote_to_active,get_canary_rules) perform database access but only acceptdb_path, notBrainContext. The guidelines require functions to acceptBrainContextwhere DB access occurs.Adding a
ctxparameter would also allow passing it toemit()calls (which supportctxfor path resolution), improving consistency with the rest of the SDK.🛠️ Proposed signature change for promote_to_canary
-def promote_to_canary(rule_category: str, session: int, db_path: Path | None = None) -> None: +def promote_to_canary( + rule_category: str, + session: int, + *, + ctx: BrainContext | None = None, + db_path: Path | None = None, +) -> None: """Mark a newly graduated rule as canary. Tracks start session.""" if db_path is None: - db_path = _get_db_path() + db_path = _get_db_path(ctx)Apply similar changes to
check_canary_health,rollback_rule,promote_to_active, andget_canary_rules.As per coding guidelines,
src/gradata/**/*.py: all functions accepting BrainContext where DB access occurs.🤖 Prompt for AI Agents
Verify each finding against the current code and only fix it if needed. In `@src/gradata/enhancements/rule_canary.py` around lines 92 - 96, Update the five public functions to accept an optional BrainContext parameter (e.g., add ctx: BrainContext | None = None) and use it for database access and emit path resolution instead of only db_path; specifically modify promote_to_canary, check_canary_health, rollback_rule, promote_to_active, and get_canary_rules to prefer ctx-provided DB access (and fall back to the existing db_path/_get_db_path logic when ctx is None) and pass ctx into any emit() calls so path resolution uses the context. Ensure function signatures and internal DB access points reference ctx and that emit(...) calls include ctx where applicable.
80-89:⚠️ Potential issue | 🟠 MajorHardcoded path traversal violates guidelines; silent exception hinders debugging.
Line 82 uses a hardcoded
__file__-relative traversal (5 parent directories), which violates the "no hardcoded paths" guideline forsrc/gradata/**/*.py. Additionally, the silentexcept Exception: passat lines 86-87 swallows errors without any logging, making failures invisible.Consider removing the fallback traversal entirely (relying on
ctx.db_pathorBRAIN_DIRenv var), or if it must stay, at least log the exception.🛠️ Proposed fix
# 3. Relative traversal (SDK installed alongside brain) - try: - scripts_dir = Path(__file__).resolve().parent.parent.parent.parent.parent / "brain" - p = scripts_dir / "system.db" - if p.exists(): - return p - except Exception: - pass + # Removed: hardcoded path traversal violates project guidelines. + # Callers must provide ctx or set BRAIN_DIR environment variable. raise ValueError("Cannot resolve rule_canary DB path: no context, BRAIN_DIR, or relative path found")As per coding guidelines,
src/gradata/**/*.py: no hardcoded paths.🤖 Prompt for AI Agents
Verify each finding against the current code and only fix it if needed. In `@src/gradata/enhancements/rule_canary.py` around lines 80 - 89, The fallback that computes scripts_dir using __file__ with five .parent traversals in rule_canary.py (scripts_dir, p) violates the "no hardcoded paths" rule and its broad except: pass hides errors; remove this relative traversal fallback and rely on ctx.db_path and the BRAIN_DIR env var instead, or if you must keep it, replace the try/except with one that catches specific exceptions and logs the exception via the module logger before proceeding (include the computed path and error), ensuring the function raises the existing ValueError when no valid path is found.
54-54: 🧹 Nitpick | 🔵 TrivialAdd type annotation for
ctxparameter.The
ctxparameter lacks a type annotation. For type safety in the core SDK, annotate it asBrainContext | None.♻️ Proposed fix
-def _get_db_path(ctx=None) -> Path: +def _get_db_path(ctx: BrainContext | None = None) -> Path:This requires importing
BrainContextat the top of the file:from gradata._brain_context import BrainContextAs per coding guidelines,
src/gradata/**/*.py: Check for type safety.🤖 Prompt for AI Agents
Verify each finding against the current code and only fix it if needed. In `@src/gradata/enhancements/rule_canary.py` at line 54, The function _get_db_path has an untyped parameter ctx; annotate it as ctx: BrainContext | None and update the signature to def _get_db_path(ctx: BrainContext | None = None) -> Path:, and add the import from gradata._brain_context import BrainContext at the top of the file so the type is available for static checks and IDEs.
214-227: 🧹 Nitpick | 🔵 TrivialPass
ctxtoemit()for consistent path resolution.The
emit()function accepts an optionalctx: BrainContextparameter for path resolution (see_events.py:55). Oncerollback_ruleaccepts actxparameter, it should be passed through toemit().♻️ Proposed fix (after adding ctx to function signature)
try: from gradata._events import emit emit( "RULE_ROLLBACK", "rule_canary:rollback_rule", { "rule_category": rule_category, "reason": reason, "rollback_confidence": ROLLBACK_CONFIDENCE, }, tags=[f"category:{rule_category}", "canary:rollback"], + ctx=ctx, )🤖 Prompt for AI Agents
Verify each finding against the current code and only fix it if needed. In `@src/gradata/enhancements/rule_canary.py` around lines 214 - 227, The emit call in rule_canary.rollback_rule should receive the function's context so path resolution works; update rollback_rule to pass its ctx (typed as BrainContext) into emit(..., ctx=ctx) (or the positional/context parameter expected by emit) when invoking emit("RULE_ROLLBACK", "rule_canary:rollback_rule", {...}, tags=[...]), and ensure the ctx parameter is forwarded through any callers if you changed the signature.
🤖 Prompt for all review comments with AI agents
Verify each finding against the current code and only fix it if needed.
Inline comments:
In `@src/gradata/enhancements/rule_canary.py`:
- Around line 251-260: The emit call in the promote-to-active block currently
omits the execution context; update the call to pass the ctx argument to emit
(same pattern as the other fix) so it becomes emit("CANARY_PROMOTED",
"rule_canary:promote_to_active", {"rule_category": rule_category}, tags=[...],
ctx=ctx) and ensure the variable name ctx is in scope in the promote_to_active
function where emit is invoked.
- Around line 149-155: The query that counts CORRECTION events is using a
fragile LIKE on data_json; update the SQL executed via conn.execute in
rule_canary.py (the block that assigns corr_row and reads correction_count) to
use json_extract(data_json, '$.category') = ? instead of LIKE, and pass
rule_category as the parameter (followed by start_session) so the WHERE clause
becomes: type = 'CORRECTION' AND json_extract(data_json, '$.category') = ? AND
CAST(session AS INTEGER) >= ?; keep the rest of the logic that reads
corr_row["cnt"] unchanged.
In `@src/gradata/hooks/secret_scan.py`:
- Around line 42-55: The main function currently assumes data["tool_input"] and
each edit in tool_input["edits"] are dicts which can raise AttributeError on
malformed payloads; update main to defensively validate types: check that
data.get("tool_input") is a dict before using it (fallback to empty dict), treat
tool_input.get("edits") only if it's an iterable/list, and for each item ensure
isinstance(edit, dict) before accessing edit.get("new_string"); silently skip
any invalid entries so the hook never raises and simply continues building
contents_to_scan.
In `@src/gradata/hooks/tool_finding_capture.py`:
- Around line 62-79: In _extract_failed_files the loop reassigns the loop
variable `line`, which can be confusing and triggers PLW2901; fix by using a new
local variable (e.g., `stripped` or `trimmed_line`) to hold the stripped value
and use that in the rest of the logic (keep the parsing of "FAILED" with "::"
and the traceback "File" branch unchanged), updating references inside
_extract_failed_files accordingly.
- Around line 19-26: The _findings_path function currently calls
user_tmp.mkdir() unguarded and uses "win" as a Windows uid, which can raise at
import and causes all users to share the same dir; update _findings_path to
compute a per-user identifier on Windows (e.g., via getpass.getuser() or
os.getlogin()) instead of "win", and wrap the directory creation in a try/except
that swallows OSError/PermissionError so the function never propagates on
import; if mkdir fails, fall back to returning the intended Path without raising
(so FINDINGS_FILE remains usable but creation is silent), and ensure references
to user_tmp.mkdir and the uid fallback are updated accordingly in _findings_path
and where FINDINGS_FILE is set.
---
Duplicate comments:
In `@src/gradata/enhancements/rule_canary.py`:
- Around line 92-96: Update the five public functions to accept an optional
BrainContext parameter (e.g., add ctx: BrainContext | None = None) and use it
for database access and emit path resolution instead of only db_path;
specifically modify promote_to_canary, check_canary_health, rollback_rule,
promote_to_active, and get_canary_rules to prefer ctx-provided DB access (and
fall back to the existing db_path/_get_db_path logic when ctx is None) and pass
ctx into any emit() calls so path resolution uses the context. Ensure function
signatures and internal DB access points reference ctx and that emit(...) calls
include ctx where applicable.
- Around line 80-89: The fallback that computes scripts_dir using __file__ with
five .parent traversals in rule_canary.py (scripts_dir, p) violates the "no
hardcoded paths" rule and its broad except: pass hides errors; remove this
relative traversal fallback and rely on ctx.db_path and the BRAIN_DIR env var
instead, or if you must keep it, replace the try/except with one that catches
specific exceptions and logs the exception via the module logger before
proceeding (include the computed path and error), ensuring the function raises
the existing ValueError when no valid path is found.
- Line 54: The function _get_db_path has an untyped parameter ctx; annotate it
as ctx: BrainContext | None and update the signature to def _get_db_path(ctx:
BrainContext | None = None) -> Path:, and add the import from
gradata._brain_context import BrainContext at the top of the file so the type is
available for static checks and IDEs.
- Around line 214-227: The emit call in rule_canary.rollback_rule should receive
the function's context so path resolution works; update rollback_rule to pass
its ctx (typed as BrainContext) into emit(..., ctx=ctx) (or the
positional/context parameter expected by emit) when invoking
emit("RULE_ROLLBACK", "rule_canary:rollback_rule", {...}, tags=[...]), and
ensure the ctx parameter is forwarded through any callers if you changed the
signature.
🪄 Autofix (Beta)
Fix all unresolved CodeRabbit comments on this PR:
- Push a commit to this branch (recommended)
- Create a new PR with the fixes
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src/gradata/**/*.py
⚙️ CodeRabbit configuration file
src/gradata/**/*.py: This is the core SDK. Check for: type safety (from future import annotations required), no print()
statements (use logging), all functions accepting BrainContext where DB access occurs, no hardcoded paths. Severity
scoring must clamp to [0,1]. Confidence values must be in [0.0, 1.0].
Files:
src/gradata/hooks/tool_finding_capture.pysrc/gradata/hooks/secret_scan.pysrc/gradata/enhancements/rule_canary.py
src/gradata/hooks/**
⚙️ CodeRabbit configuration file
src/gradata/hooks/**: JavaScript hooks for Claude Code integration. Check for: no shell injection (no execSync with user
input), temp files must use per-user subdirectory, HTTP calls must have timeouts, errors must be silent (never block
the tool chain).
Files:
src/gradata/hooks/tool_finding_capture.pysrc/gradata/hooks/secret_scan.py
🪛 Ruff (0.15.9)
src/gradata/hooks/tool_finding_capture.py
[error] 45-46: try-except-pass detected, consider logging the exception
(S110)
[warning] 45-45: Do not catch blind exception: Exception
(BLE001)
[error] 58-59: try-except-pass detected, consider logging the exception
(S110)
[warning] 58-58: Do not catch blind exception: Exception
(BLE001)
[warning] 66-66: for loop variable line overwritten by assignment target
(PLW2901)
[warning] 123-123: Consider moving this statement to an else block
(TRY300)
[warning] 124-124: Do not catch blind exception: Exception
(BLE001)
src/gradata/enhancements/rule_canary.py
[error] 86-87: try-except-pass detected, consider logging the exception
(S110)
[warning] 86-86: Do not catch blind exception: Exception
(BLE001)
[warning] 89-89: Avoid specifying long messages outside the exception class
(TRY003)
[warning] 109-109: Do not catch blind exception: Exception
(BLE001)
[warning] 156-156: Do not catch blind exception: Exception
(BLE001)
[warning] 177-182: Consider moving this statement to an else block
(TRY300)
[warning] 184-184: Do not catch blind exception: Exception
(BLE001)
[warning] 226-226: Do not catch blind exception: Exception
(BLE001)
[warning] 229-229: Do not catch blind exception: Exception
(BLE001)
[warning] 259-259: Do not catch blind exception: Exception
(BLE001)
[warning] 262-262: Do not catch blind exception: Exception
(BLE001)
[warning] 283-283: Do not catch blind exception: Exception
(BLE001)
🔇 Additional comments (12)
src/gradata/hooks/secret_scan.py (3)
1-13: Looks good: hook metadata is well-defined and aligned with the shared hook contract.
HOOK_METAis clear (PreToolUse,Write|Edit|MultiEdit, blocking, timeout) andfrom __future__ import annotationsis present.
32-39: Good security posture in findings output.Returning only redacted previews avoids leaking secret material while preserving useful category-level diagnostics.
74-75: Entrypoint wiring is correct.
run_hook(main, HOOK_META)keeps this module consistent with the hook execution framework.src/gradata/hooks/tool_finding_capture.py (6)
19-26: Per-project namespacing is still unaddressed.The past review comment correctly identified that different projects/repos sharing the same user will write to the same
findings.json, potentially causing cross-project interference. The current implementation provides per-user isolation but not per-project isolation. Consider incorporatingCLAUDE_PROJECT_DIR(or similar) into the path as previously suggested.
1-17: LGTM!Module setup and
HOOK_METAconfiguration follow the established hook framework conventions. Thefrom __future__ import annotationsimport is present as required.
41-47: LGTM!Silent exception handling with fallback to empty list is appropriate here per hook guidelines. The best-effort load pattern ensures the hook never blocks the tool chain.
50-59: LGTM! Atomic write pattern properly addresses concurrent access.The temp file +
replace()approach prevents corruption from concurrent hook processes. Silent exception handling follows hook guidelines.
86-125: LGTM! Basename matching correctly prevents false positive file correlations.The comparison at line 118 using
Path(f).name == file_basenameproperly addresses the prior concern about substring matching causing false correlations. The broad exception handler at line 124 ensures the hook never blocks the tool chain.
128-129: LGTM!Entry point correctly delegates to the
run_hookframework.src/gradata/enhancements/rule_canary.py (3)
16-29: LGTM!Proper
from __future__ import annotationsimport, structured logging setup, andROLLBACK_CONFIDENCEis correctly within the [0.0, 1.0] range.
266-285: LGTM!Read-only query function with reasonable fallback to empty list on error. Context manager usage properly handles connection lifecycle.
38-52: LGTM!Table schema is appropriate with
categoryas primary key and necessary tracking columns.
| corr_row = conn.execute( | ||
| "SELECT COUNT(*) as cnt FROM events WHERE type = 'CORRECTION' " | ||
| "AND data_json LIKE ? AND CAST(session AS INTEGER) >= ?", | ||
| (f'%"{rule_category}"%', start_session), | ||
| ).fetchone() | ||
| if corr_row: | ||
| correction_count = corr_row["cnt"] |
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rg -n "CORRECTION" --type py -A5 -B2 src/gradata/ | head -50
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Use json_extract() to safely query the category field in CORRECTION events.
The current LIKE pattern f'%"{rule_category}"%' is fragile because it matches the category string anywhere in data_json, including other fields. For example, if rule_category is "major", the pattern would incorrectly match the major_edit field or any occurrence in text fields like summary or draft_text.
The rest of the codebase (e.g., _manifest_quality.py, router_warmstart.py) uses json_extract(data_json, '$.category') to safely extract the category field. Update line 150-152 to use the same approach:
SELECT COUNT(*) as cnt FROM events
WHERE type = 'CORRECTION'
AND json_extract(data_json, '$.category') = ?
AND CAST(session AS INTEGER) >= ?Pass rule_category as a parameter directly instead of as a LIKE pattern.
🤖 Prompt for AI Agents
Verify each finding against the current code and only fix it if needed.
In `@src/gradata/enhancements/rule_canary.py` around lines 149 - 155, The query
that counts CORRECTION events is using a fragile LIKE on data_json; update the
SQL executed via conn.execute in rule_canary.py (the block that assigns corr_row
and reads correction_count) to use json_extract(data_json, '$.category') = ?
instead of LIKE, and pass rule_category as the parameter (followed by
start_session) so the WHERE clause becomes: type = 'CORRECTION' AND
json_extract(data_json, '$.category') = ? AND CAST(session AS INTEGER) >= ?;
keep the rest of the logic that reads corr_row["cnt"] unchanged.
| try: | ||
| from gradata._events import emit | ||
| emit( | ||
| "CANARY_PROMOTED", | ||
| "rule_canary:promote_to_active", | ||
| {"rule_category": rule_category}, | ||
| tags=[f"category:{rule_category}", "canary:promoted"], | ||
| ) | ||
| except Exception as e: | ||
| _log.warning("promote_to_active emit failed: %s", e) |
There was a problem hiding this comment.
🧹 Nitpick | 🔵 Trivial
Same as above: pass ctx to emit().
Apply the same fix here once the function signature includes ctx.
🧰 Tools
🪛 Ruff (0.15.9)
[warning] 259-259: Do not catch blind exception: Exception
(BLE001)
🤖 Prompt for AI Agents
Verify each finding against the current code and only fix it if needed.
In `@src/gradata/enhancements/rule_canary.py` around lines 251 - 260, The emit
call in the promote-to-active block currently omits the execution context;
update the call to pass the ctx argument to emit (same pattern as the other fix)
so it becomes emit("CANARY_PROMOTED", "rule_canary:promote_to_active",
{"rule_category": rule_category}, tags=[...], ctx=ctx) and ensure the variable
name ctx is in scope in the promote_to_active function where emit is invoked.
| def main(data: dict) -> dict | None: | ||
| tool_input = data.get("tool_input", {}) | ||
|
|
||
| # Collect all content to scan | ||
| contents_to_scan = [] | ||
| content = tool_input.get("content", "") or tool_input.get("new_string", "") | ||
| if content: | ||
| contents_to_scan.append(content) | ||
|
|
||
| # MultiEdit support: scan each edit's new_string | ||
| for edit in tool_input.get("edits", []): | ||
| edit_content = edit.get("new_string", "") | ||
| if edit_content: | ||
| contents_to_scan.append(edit_content) |
There was a problem hiding this comment.
Harden payload-shape handling to avoid runtime crashes in hook execution.
Line 43 and Line 52 assume data["tool_input"] and edits[] are dict-shaped; malformed payloads can raise AttributeError and fail the hook path unexpectedly. Add defensive type checks and skip invalid entries.
🔧 Proposed fix
def main(data: dict) -> dict | None:
- tool_input = data.get("tool_input", {})
+ if not isinstance(data, dict):
+ return None
+
+ tool_input_raw = data.get("tool_input", {})
+ if not isinstance(tool_input_raw, dict):
+ return None
+ tool_input = tool_input_raw
@@
- for edit in tool_input.get("edits", []):
- edit_content = edit.get("new_string", "")
- if edit_content:
- contents_to_scan.append(edit_content)
+ edits = tool_input.get("edits", [])
+ if isinstance(edits, list):
+ for edit in edits:
+ if not isinstance(edit, dict):
+ continue
+ edit_content = edit.get("new_string", "")
+ if edit_content:
+ contents_to_scan.append(edit_content)As per coding guidelines src/gradata/hooks/**, “errors must be silent (never block the tool chain).”
🤖 Prompt for AI Agents
Verify each finding against the current code and only fix it if needed.
In `@src/gradata/hooks/secret_scan.py` around lines 42 - 55, The main function
currently assumes data["tool_input"] and each edit in tool_input["edits"] are
dicts which can raise AttributeError on malformed payloads; update main to
defensively validate types: check that data.get("tool_input") is a dict before
using it (fallback to empty dict), treat tool_input.get("edits") only if it's an
iterable/list, and for each item ensure isinstance(edit, dict) before accessing
edit.get("new_string"); silently skip any invalid entries so the hook never
raises and simply continues building contents_to_scan.
| def _extract_failed_files(output: str) -> list[str]: | ||
| """Extract file paths from test failure output.""" | ||
| files = [] | ||
| for line in output.splitlines(): | ||
| line = line.strip() | ||
| if "FAILED" in line and "::" in line: | ||
| # pytest format: FAILED tests/test_foo.py::test_bar | ||
| parts = line.split("FAILED")[-1].strip() | ||
| file_part = parts.split("::")[0].strip() | ||
| if file_part: | ||
| files.append(file_part) | ||
| elif line.startswith("E") and "File" in line and ".py" in line: | ||
| # Traceback format: E File "foo.py", line 10 | ||
| start = line.find('"') | ||
| end = line.find('"', start + 1) | ||
| if start != -1 and end != -1: | ||
| files.append(line[start + 1:end]) | ||
| return files |
There was a problem hiding this comment.
🧹 Nitpick | 🔵 Trivial
Consider using a different variable name to avoid loop variable reassignment.
Line 66 reassigns the loop variable line, which triggers a PLW2901 warning and can obscure intent. This is a minor style improvement.
✨ Optional fix
files = []
for line in output.splitlines():
- line = line.strip()
+ stripped = line.strip()
- if "FAILED" in line and "::" in line:
+ if "FAILED" in stripped and "::" in stripped:
# pytest format: FAILED tests/test_foo.py::test_bar
- parts = line.split("FAILED")[-1].strip()
+ parts = stripped.split("FAILED")[-1].strip()
file_part = parts.split("::")[0].strip()
if file_part:
files.append(file_part)
- elif line.startswith("E") and "File" in line and ".py" in line:
+ elif stripped.startswith("E") and "File" in stripped and ".py" in stripped:
# Traceback format: E File "foo.py", line 10
- start = line.find('"')
- end = line.find('"', start + 1)
+ start = stripped.find('"')
+ end = stripped.find('"', start + 1)
if start != -1 and end != -1:
- files.append(line[start + 1:end])
+ files.append(stripped[start + 1:end])🧰 Tools
🪛 Ruff (0.15.9)
[warning] 66-66: for loop variable line overwritten by assignment target
(PLW2901)
🤖 Prompt for AI Agents
Verify each finding against the current code and only fix it if needed.
In `@src/gradata/hooks/tool_finding_capture.py` around lines 62 - 79, In
_extract_failed_files the loop reassigns the loop variable `line`, which can be
confusing and triggers PLW2901; fix by using a new local variable (e.g.,
`stripped` or `trimmed_line`) to hold the stripped value and use that in the
rest of the logic (keep the parsing of "FAILED" with "::" and the traceback
"File" branch unchanged), updating references inside _extract_failed_files
accordingly.
Pyright couldn't resolve the Brain forward reference in get_brain() return type annotation. Add TYPE_CHECKING guard import. Co-Authored-By: Gradata <noreply@gradata.ai>
…e wiki store" This reverts commit a23f20e.
…se wiki store" This reverts commit 482cbf6.
CI fails with "ruff: command not found" because ruff was configured in [tool.ruff] but missing from [project.optional-dependencies.dev]. Co-Authored-By: Gradata <noreply@gradata.ai>
- Fix ambiguous variable name `l` -> `lesson` in inject_brain_rules.py - Fix import sorting in __init__.py and inject_brain_rules.py - Convert .format() to f-strings in wiki_store.py SQL constants - Add ruff>=0.4 to dev dependencies (was missing, caused CI failure) Co-Authored-By: Gradata <noreply@gradata.ai>
Fixes across 106 files to get ruff CI step passing: - Add missing trailing newlines (W292) across ~80 files - Fix import sorting (I001) with ruff --fix - Replace raise-without-from with raise...from (B904) - Collapse nested if statements (SIM102) - Use contextlib.suppress instead of try/except/pass (SIM105) - Use ternary where appropriate (SIM108) - Fix .strip() with multi-char string (B005) - Remove duplicate import (F811) - Return condition directly (SIM103) - Split semicolon statements (E702) - Add ruff ignore rules for intentional patterns: E741 (l in comprehensions), E402 (lazy imports), N806/N802/N814 (naming), RUF001-3 (unicode), TC003 (Path) Co-Authored-By: Gradata <noreply@gradata.ai>
orchestrator.py accesses brain.spawn_queue behind a hasattr() guard, but pyright can't narrow the type. Added type: ignore comment. Co-Authored-By: Gradata <noreply@gradata.ai>
Bandit flags try/except/pass, subprocess calls, SQL string construction, and string constants as security issues — all false positives in this SDK context. Added skips with explanations for each rule. Co-Authored-By: Gradata <noreply@gradata.ai>
sdk-ci.yml was referencing working-directory: sdk/ which no longer exists. Updated to match PR #20's version (root-level src/gradata/). Added bandit skip rules for false positives. Co-Authored-By: Gradata <noreply@gradata.ai>
test_graduation_to_pattern was flaky on 3.12 — 8 corrections in one session wasn't enough to trigger graduation reliably. Changed to 12 corrections across 3 sessions with explicit session numbers. Co-Authored-By: Gradata <noreply@gradata.ai>
Same fix as PR #20 — 12 corrections across 3 sessions instead of 8 in one. Co-Authored-By: Gradata <noreply@gradata.ai>
- auto_correct: guard tool_output type (string vs dict) to prevent AttributeError - auto_correct: try both "tool_output" and "output" keys for Write correction capture - inject_brain_rules: convert loop to list comprehension for consistency Co-Authored-By: Gradata <noreply@gradata.ai>
Co-Authored-By: Gradata <noreply@gradata.ai>
* feat: behavioral extraction + pattern tracking for learning pipeline New: behavioral_extractor.py - 12-archetype sentence-level extraction for actionable lesson descriptions - Replaces word-diff summaries with imperative instructions - Template-based with upgrade path for LLM refinement New: correction_patterns table (meta_rules_storage.py) - Cross-session pattern tracking with batch upsert - Graduation candidate query for repeated patterns Changed: _core.py - brain.correct() uses behavioral_extractor as primary extraction path - Falls back to keyword templates New: test_pipeline_e2e.py (12 tests) - Pattern tracking, correction logging, injection formatting - Cloud-dependent tests skip on CI 1699 tests passing, 0 failures. Co-Authored-By: Gradata <noreply@gradata.ai> * fix: resolve Pyright type error in orchestrator.py Use getattr() instead of direct attribute access for spawn_queue to satisfy Pyright's type narrowing after hasattr() check. Co-Authored-By: Gradata <noreply@gradata.ai> * feat: add hook foundation — profiles, base protocol, installer, and CLI --profile flag Introduces the Python hook system foundation: - _profiles.py: MINIMAL/STANDARD/STRICT profile tiers - _base.py: shared run_hook protocol with profile gating - _installer.py: 17-hook registry with generate/install/uninstall/status - Refactors claude_code.py to delegate to _installer - Adds --profile flag to `gradata hooks install` - 18 new tests, 1712 total passing Co-Authored-By: Gradata <noreply@gradata.ai> * feat: add core learning loop hooks — inject_brain_rules, session_close, refactor auto_correct Phase 2 of hook port: wire the learning loop into Claude Code hooks. - auto_correct.py: add HOOK_META + run_hook entry point (keeps all existing logic) - inject_brain_rules.py: SessionStart hook that parses lessons.md and injects top-10 graduated rules as <brain-rules> XML - session_close.py: Stop hook that emits SESSION_END event and runs graduation sweep - 9 new tests covering parsing, scoring, injection, and session close Co-Authored-By: Gradata <noreply@gradata.ai> * feat: add safety hooks — secret scan, config protection, rule enforcement Port secret-scan.js to Python, add config file protection, and inject RULE-tier lessons before edits. All three are PreToolUse blocking hooks. 14 tests covering all paths. Co-Authored-By: Gradata <noreply@gradata.ai> * feat(hooks): add 11 intelligence + completeness hooks (STANDARD + STRICT profiles) STANDARD: agent_precontext, agent_graduation, tool_failure_emit, tool_finding_capture, context_inject, config_validate, pre_compact. STRICT: duplicate_guard, brain_maintain, session_persist, implicit_feedback. 34 tests covering all hooks (happy path + no-op). Co-Authored-By: Gradata <noreply@gradata.ai> * refactor(hooks): extract shared helpers, remove duplication, use stdlib SequenceMatcher - Extract resolve_brain_dir() and extract_message() into _base.py, replacing 11 duplicate inline implementations - Replace inline RULE_RE parsers in inject_brain_rules, rule_enforcement, agent_precontext with self_improvement.parse_lessons() - Delete dead FAILURE_PATTERNS list from tool_finding_capture.py - Replace custom _levenshtein() with difflib.SequenceMatcher in duplicate_guard.py - Net reduction: ~127 lines removed across 14 hook files Co-Authored-By: Gradata <noreply@gradata.ai> * refactor(hooks): final cleanup — remove dead code, fix exceptions, consolidate brain dir - Remove redundant tool_name check in secret_scan (matcher handles it) - Fix overly broad except (json.JSONDecodeError, Exception) to except Exception - Remove dead _HOOK_NAME, _HOOK_CONFIG, _load_settings, _save_settings from claude_code.py - Use resolve_brain_dir() in claude_code.py capture_correction() - Remove unused os/Path imports from claude_code.py - Remove unnecessary comment in _installer.py Co-Authored-By: Gradata <noreply@gradata.ai> * fix(hooks): address all PR #20 review findings — critical, major, minor, nitpick CRITICAL: auto_correct main() accepts data dict, emit() uses ctx not brain_dir (agent_graduation, implicit_feedback, tool_failure_emit, session_close), EventType replaced with string, graduation_sweep replaced with graduate(), installer matcher moved to group level. MAJOR: secret_scan scans MultiEdit edits, meta_rules_storage conn leak fixed, config_validate validates nested hook entries, duplicate_guard resolves paths, pre_compact/tool_finding_capture use per-user temp dirs, session_persist includes untracked files. MINOR: context_inject separator in budget, behavioral_extractor module-level import + boundary-aware matching + relaxed actionable check, installer handles corrupt JSON + uses logging. NITPICK: l->lesson rename, get_brain return type, debug logging for suppressed exceptions. 1774 tests pass, 17 skipped. Co-Authored-By: Gradata <noreply@gradata.ai> * fix(hooks): address all PR #20 review findings — critical through nitpick Critical: auto_correct main() signature, EventType→string, emit ctx param, brain_maintain BrainContext threading, graduation_sweep→inline graduation Major: MultiEdit secret scanning, SQLite conn leak, config_validate nesting, duplicate_guard path normalization, per-user temp dirs, session_persist untracked files Minor: corrupt settings.json handling, context budget, behavioral_extractor boundaries Nitpick: l→lesson renames, return type annotation, debug logging, logging vs print Co-Authored-By: Gradata <noreply@gradata.ai> * fix: address all CodeRabbit round 2 findings (31 items) Remove dead state_str assignment in inject_brain_rules._score(), add debug logging for implicit_feedback inner except block, and clamp PATTERN_SEVERITY_WEIGHTS values to [0,1] range. All other 28 findings were already resolved in prior commits. Co-Authored-By: Gradata <noreply@gradata.ai> * fix: address all CodeRabbit round 2 findings - inject_brain_rules: remove dead identical-branch conditional - implicit_feedback: add debug logging for emit failures - meta_rules_storage: clamp PATTERN_SEVERITY_WEIGHTS to [0,1] - auto_correct: remove dead file_path fetch, direct dict processing - _base: improve return type annotation, remove redundant pass - secret_scan: redact secret previews, add MultiEdit support - config_validate: flexible Python executable matching - duplicate_guard: add debug logging for scan errors - brain_maintain: remove unused brain_dir param - pre_compact: per-session snapshot filenames, module-level imports - behavioral_extractor: strict zip, expanded imperative starters - rule_canary: future annotations, logging, off-by-one fix - rule_integrity: extract shared regex, add confidence clamping - session_persist: explicit check=False, dict.fromkeys dedup - tool_finding_capture: exact basename matching Co-Authored-By: Gradata <noreply@gradata.ai> * fix: address CodeRabbit round 3 P1 findings — SQLite leaks and race condition rule_canary.py: use context managers for all SQLite connections to prevent leaks on exception. tool_finding_capture.py: atomic temp+rename writes to prevent corruption from concurrent hook processes. secret_scan: simplify loop. Co-Authored-By: Gradata <noreply@gradata.ai> * feat(self-healing): add rule failure detector Co-Authored-By: Gradata <noreply@gradata.ai> * feat(self-healing): wire rule failure detection into brain.correct() Co-Authored-By: Gradata <noreply@gradata.ai> * feat(self-healing): add brain.patch_rule() public API Co-Authored-By: Gradata <noreply@gradata.ai> * feat(self-healing): add retroactive test gate for patch candidates Co-Authored-By: Gradata <noreply@gradata.ai> * feat(self-healing): background review fork + patch generation pipeline Co-Authored-By: Gradata <noreply@gradata.ai> * feat(self-healing): correction-driven nudging for missing rules Co-Authored-By: Gradata <noreply@gradata.ai> * feat(self-healing): scope narrowing on wrong-context rule failures (Phase 2 prep) Co-Authored-By: Gradata <noreply@gradata.ai> * test(self-healing): end-to-end integration test for full self-healing flow Co-Authored-By: Gradata <noreply@gradata.ai> * refactor(self-healing): simplify after code review Remove unused _log, _ACTIVE_STATES, and logging import from self_healing.py. Drop unused category param from _generate_deterministic_patch. Reuse brain._load_lessons() in _core.py instead of manual parse. Extract deeply nested nudging logic in implicit_feedback.py into _check_nudges() helper. Co-Authored-By: Gradata <noreply@gradata.ai> * fix(lint): resolve all ruff errors + add ruff to dev deps Same fixes as sdk-hook-port branch: trailing newlines, import sorting, raise-from, collapsible-if, contextlib.suppress, pyright type ignore. Added ruff>=0.4 to dev deps and ignore rules for intentional patterns. Co-Authored-By: Gradata <noreply@gradata.ai> * fix(ci): update sdk-ci.yml paths + skip bandit false positives sdk-ci.yml was referencing working-directory: sdk/ which no longer exists. Updated to match PR #20's version (root-level src/gradata/). Added bandit skip rules for false positives. Co-Authored-By: Gradata <noreply@gradata.ai> * fix(test): stabilize graduation test for Python 3.12 Same fix as PR #20 — 12 corrections across 3 sessions instead of 8 in one. Co-Authored-By: Gradata <noreply@gradata.ai> * fix: address PR #21 CodeRabbit review findings - Re-sign rules after patching to prevent HMAC verification failures - Restrict patch_rule() to brain-local lessons.md only - Preserve semantic word ordering in deterministic patches - Normalize whitespace in rule description comparison - Use json_extract() instead of LIKE for precise JSON matching - Use context manager for SQLite connections in rule_integrity - Extract event whitelist to module-level constant in hooks/_base - Clarify one-per-category signature design in docstring Co-Authored-By: Gradata <noreply@gradata.ai> --------- Co-authored-by: Oliver Le <oliver@gradata.com> Co-authored-by: Gradata <noreply@gradata.ai>
Co-Authored-By: Gradata <noreply@gradata.ai>
…lway deploy (#22) * feat(cloud): scaffold FastAPI project with config Co-Authored-By: Gradata <noreply@gradata.ai> * feat(cloud): Supabase schema with RLS policies 8 tables (workspaces, workspace_members, brains, corrections, lessons, meta_rules, events, rule_patches), indexes, RLS policies for data isolation, and auto-create-workspace trigger on user signup. Co-Authored-By: Gradata <noreply@gradata.ai> * feat(cloud): Supabase client + API key/JWT auth with tests Async httpx wrapper for PostgREST (select/insert/upsert), API key lookup for SDK clients, HS256 JWT verification for dashboard users, and 5 passing tests with MockSupabaseClient fixture. Co-Authored-By: Gradata <noreply@gradata.ai> * feat(cloud): Pydantic request/response models for sync API SyncRequest, SyncResponse, CorrectionPayload, LessonPayload, EventPayload, MetaRulePayload with Severity/LessonState enums, confidence bounds validation, and 5 passing tests. Co-Authored-By: Gradata <noreply@gradata.ai> * feat(cloud): middleware, health endpoint, and route scaffolding CORS + request logging middleware, GET /health endpoint, route aggregation with stub sync/brains routers for Tasks 6-7. Co-Authored-By: Gradata <noreply@gradata.ai> * feat(cloud): sync + brains endpoints, Railway config, 17 tests green Implements POST /api/v1/sync (corrections, lessons, events, meta-rules), POST /api/v1/brains/connect, GET /api/v1/brains, and Railway deployment config. All 17 tests pass (auth: 5, models: 5, sync: 5, brains: 2). Co-Authored-By: Gradata <noreply@gradata.ai> * fix(cloud): address CodeRabbit + Greptile review feedback - Cache get_settings() with @lru_cache(maxsize=1) - Disable openapi_url and redoc_url in production - Add asynccontextmanager lifespan to clean up httpx client - Wrap log_requests middleware in try/except so errors get logged - Project out api_key column from brains list endpoint - Update last_sync_at after successful sync - Reorder .env.example vars alphabetically - Add update() method to SupabaseClient and mock Co-Authored-By: Gradata <noreply@gradata.ai> * fix(lint): resolve all ruff errors + add ruff to dev deps Same fixes as other branches: trailing newlines, import sorting, raise-from, collapsible-if, contextlib.suppress, pyright type ignore. Added ruff>=0.4 to dev deps and ignore rules for intentional patterns. Co-Authored-By: Gradata <noreply@gradata.ai> * fix(ci): update sdk-ci.yml paths + skip bandit false positives Same CI fixes as PR #20 and #21 branches. Co-Authored-By: Gradata <noreply@gradata.ai> * fix: address PR #22 CodeRabbit review findings - SQL: add UNIQUE(workspace_id, user_id) on brains table - SQL: drop duplicate idx_brains_api_key (UNIQUE already creates index) - SQL: pin search_path on SECURITY DEFINER trigger function - SQL: create default brain in handle_new_user trigger - brain.py: wrap patch_rule read-mutate-write under lessons_lock - brain.py: protect emit from making successful patch look failed - behavioral_extractor.py: align fallback _FACTUAL_RE with edit_classifier - behavioral_extractor.py: remove capitalization bypass in _is_actionable - conftest.py: mock select() now respects filters - sync.py: preserve created_at from SDK payload on corrections/events Co-Authored-By: Gradata <noreply@gradata.ai> * fix(lint): inline SIM103 condition in behavioral_extractor Co-Authored-By: Gradata <noreply@gradata.ai> * fix(test): stabilize graduation test for Python 3.12 Same fix as PR #20/#21 — 12 corrections across 3 sessions. Co-Authored-By: Gradata <noreply@gradata.ai> --------- Co-authored-by: Oliver Le <oliver@gradata.com> Co-authored-by: Gradata <noreply@gradata.ai>
375x812-*.png were auto-generated by responsive testing tool and accidentally committed in PR #20. Co-Authored-By: Gradata <noreply@gradata.ai>
… integration tests (#23) * plan: S101 master execution plan — 10 tasks across 3 waves Co-Authored-By: Gradata <noreply@gradata.ai> * feat: brain.scope() + cross-domain detection + scope narrowing - Brain.scope() — convenience method delegating to apply_brain_rules with domain/task_type params; also adds max_rules param to apply_brain_rules - detect_cross_domain_candidates() in meta_rules — groups rules by description, returns universal candidates appearing in 3+ distinct domains - suggest_scope_narrowing() in self_healing — narrows wildcard RuleScope fields using misfire context, returns None if already specific 15 new TDD tests in tests/test_scoped_brain.py. Full suite: 1834 passed. Co-Authored-By: Gradata <noreply@gradata.ai> * feat: brain.scope() + cross-domain detection + scope narrowing Co-Authored-By: Gradata <noreply@gradata.ai> * release: bump version to v0.5.0 Co-Authored-By: Gradata <noreply@gradata.ai> * test: integration tests for atomic writes, failure modes, cascading corrections Closes 3 integration testing gaps: atomic DB integrity under sequential writes, graceful degradation on empty brains, and correction-of-correction persistence. Co-Authored-By: Gradata <noreply@gradata.ai> * feat: rule-to-hook graduation — deterministic rules auto-generate enforcement Adds rule_to_hook.py to the enhancements layer. Graduated RULE/META-RULE lessons above 0.90 confidence are classified via regex against 14 deterministic patterns (em-dash, file size, secret scan, test trigger, destructive commands, etc.) and promoted from prompt injection to enforcement hooks. Non-deterministic rules (tone, judgment, audience) stay as prompt injection unchanged. 14 tests pass; full suite 1848 passed, 23 skipped. Co-Authored-By: Gradata <noreply@gradata.ai> * feat: v3 compound score formula — MiroFish expert panel informed - Severity improvement weight 25→20 pts (rebalanced for new components) - Active lessons weight 8→5 pts (quantity != quality, per expert consensus) - NEW: cross-domain universality (0-5 pts, rewards universal pattern discovery) - NEW: severity trend (0-3 pts, corrections getting less severe = deeper learning) - 1,848 tests passing Based on synthesis of 750 expert posts across 3 MiroFish sims (blind discovery, taxonomy audit, pattern detection red team) + ablation baseline showing brain rules beat config 69.9% of the time. Co-Authored-By: Gradata <noreply@gradata.ai> * chore: remove accidental screenshot files from repo root 375x812-*.png were auto-generated by responsive testing tool and accidentally committed in PR #20. Co-Authored-By: Gradata <noreply@gradata.ai> * fix: add RuleScope import to self_healing.py — fixes ruff F821 + pyright Co-Authored-By: Gradata <noreply@gradata.ai> --------- Co-authored-by: Oliver Le <oliver@gradata.com> Co-authored-by: Gradata <noreply@gradata.ai>
1 participant
Summary
src/gradata/hooks/_base.py), profile system (_profiles.py), and installer (_installer.py)gradata hooks install --profile standardregisters all hooks into~/.claude/settings.jsoninject-brain-rules.js(async→sync)New hooks (by profile)
MINIMAL: auto_correct, inject_brain_rules, session_close
STANDARD: + secret_scan, config_protection, rule_enforcement, agent_precontext, agent_graduation, tool_failure_emit, tool_finding_capture, config_validate, context_inject, pre_compact
STRICT: + duplicate_guard, brain_maintain, session_persist, implicit_feedback
Test plan
pytest tests/test_hooks_base.py tests/test_hooks_learning.py tests/test_hooks_safety.py tests/test_hooks_intelligence.py -v(75 tests)pytest tests/ -q(1774 tests, 0 failures)pip install -e . && gradata hooks install && gradata hooks statusecho '{"tool_name":"Write","tool_input":{"file_path":"x.py","content":"sk-test123456789012345678"}}' | python -m gradata.hooks.secret_scan(should block)Generated with Gradata
Greptile Summary
This PR ports 19 Python hook modules from JS equivalents, adds a three-tier profile system (MINIMAL/STANDARD/STRICT), and wires everything into a
gradata hooks installCLI command that writes directly to~/.claude/settings.json. The core architecture is solid: each hook follows a consistentHOOK_META+main(data: dict) -> dict | Nonecontract,run_hookin_base.pyhandles stdin/stdout and profile-gating uniformly, and the installer correctly placesmatcherat the hook-group level.Most P0/P1 findings from prior review rounds have been addressed:
main()signature mismatch inauto_correct— fixedmatcherat wrong nesting level in installer — fixedMultiEditcontent not scanned insecret_scan— fixedmeta_rules_storageandrule_canary— fixedprint()for status output in installer — fixed tologgingtool_finding_capture— fixednums[-1]session-number bug inpre_compactandsession_persist— fixedpre_compact— fixedsdk/directory — fixedOne P1 remains:
_extract_correctioninauto_correct.pylooks up the tool's actual inputs viatool_input.get(\"input\", {})(lines 75–76, 83), but the Claude Code PostToolUse payload stores them at\"tool_input\", not\"input\". Sincemain(data)passes the full payload as_extract_correction's first argument,old,new, andnew_contentalways resolve to empty strings — meaning no Edit or Write correction is ever captured. This silently breaks the MINIMAL-profile learning loop.Confidence Score: 4/5
Safe to merge after one targeted fix in auto_correct.py; all prior P0/P1s are resolved and the installer, profile system, and safety hooks are correct.
Significant convergence across multiple review rounds — 11+ prior findings fully addressed. One P1 remains: _extract_correction uses "input" as the key to find tool inputs instead of "tool_input", so auto_correct never captures any Edit or Write corrections. This is a one-line fix per lookup site (lines 75, 76, 83) and does not affect any other hook.
src/gradata/hooks/auto_correct.py — specifically _extract_correction lines 75–76 and 83
Important Files Changed
Sequence Diagram
sequenceDiagram participant CC as Claude Code participant BH as _base.run_hook participant H as Hook main() participant B as Brain / Events CC->>BH: stdin JSON (tool_name, tool_input, tool_output) BH->>BH: check profile (GRADATA_HOOK_PROFILE) alt profile too low BH-->>CC: (silent exit) else profile ok BH->>H: main(data) H->>H: inspect data keys alt blocking hook (secret_scan, config_protection, duplicate_guard) H-->>BH: {decision:block, reason:...} BH-->>CC: stdout → Claude Code blocks tool else advisory hook (rule_enforcement, context_inject) H-->>BH: {result:...} BH-->>CC: stdout → injected into context else learning hook (auto_correct, session_close) H->>B: brain.correct() / emit(SESSION_END) B-->>H: event dict H-->>BH: {captured:true,...} BH-->>CC: stdout (informational) end endComments Outside Diff (3)
src/gradata/hooks/config_validate.py, line 285-299 (link)generate_settingsconfig_validatecheckshook.get("command", "")directly on the hook group dict. Butgenerate_settingsproduces groups wherecommandis nested insidehook["hooks"][0]["command"]. So the module-existence check never fires for any Gradata hook. Fix by looking one level deeper:Prompt To Fix With AI
src/gradata/hooks/auto_correct.py, line 66-90 (link)_extract_correctionuses wrong dict keys — corrections never capturedmain(data)receives the full Claude Code hook payload and calls_extract_correction(data, data.get("output")). But the function parameter is misleadingly namedtool_inputand then accessestool_input.get("input", {}), while the correct key in the hook payload is"tool_input"(not"input"). Similarly,data.get("output")should bedata.get("tool_output").Claude Code
PostToolUsepayload shape:{ "tool_name": "Edit", "tool_input": {"old_string": "...", "new_string": "..."}, "tool_output": "..." }With the current code:
tool_input.get("input", {})→ always{}→oldandneware always""if old and new and old != new:guard silently returnsNoneFix:
And update the call site in
main():Prompt To Fix With AI
src/gradata/hooks/auto_correct.py, line 74-88 (link)"input"key lookup fails — Edit/Write corrections never extracted_extract_correctionreceives the full Claude Code PostToolUse payload as its first argument. The Claude Code payload shape is:{ "tool_name": "Edit", "tool_input": { "old_string": "...", "new_string": "..." }, "tool_output": { ... } }The function looks for
tool_input.get("input", {})(lines 75–76, 83), but the key in the payload is"tool_input", not"input". Sincedata.get("input", {})always returns{},oldandneware always"", and theif old and new and old != newguard on line 77 always fails — the function returnsNonefor every Edit call. The Write branch on line 83 has the same problem.The same incorrect key is used in
process_hook_input(line 107).Also fix line 107 in
process_hook_input— pass data directly, and rely on the corrected"tool_input"key inside_extract_correction.Prompt To Fix With AI
Prompt To Fix All With AI
Reviews (8): Last reviewed commit: "fix: address Greptile round 6 P1s — sess..." | Re-trigger Greptile