feat(wiring): canary + rules.injected + scipy Beta PPF + Beta LB gate

[Gradata]

Summary

Compound wiring PR from the 2026-04-15 autoresearch synthesis (.tmp/autoresearch-synthesis.md). Four recommendations from three independent audit reports collapse into five small, contained edits.

Closes wiring gaps:

• § Canary enrollment — _core.py:680 now calls promote_to_canary on every RULE graduation
• § Canary health sweep — end_session now checks each RULE-tier canary; promotes/rolls back per check_canary_health
• § rules.injected — emitted from brain.apply_brain_rules so SessionHistory.compute_effectiveness starts returning real data (subscriber existed, emitter didn't)
• § Bus passed into apply_rules / apply_rules_with_tree so rule_scoped_out actually fires in production

Algo-gaps shipped:

• § scipy-backed _beta_ppf_05 — closes small-sample bias in the ~40% of PATTERN-tier rules with α+β < 10
• § Beta LB gate (opt-in) — blocks RULE promotion unless Beta.ppf(0.05, α, β) ≥ 0.70 AND fire_count ≥ 5. Off by default to preserve v4 ablation calibration; flip via GRADATA_BETA_LB_GATE=1

Why one PR, not five

Three separate audit reports identified these as independent issues. Cross-referencing them shows they share change sites and the fixes compose:

• Canary + rule-to-hook wiring both live at _core.py:680 (GRADUATION emit point)
• rules.injected emission is the unlock for SessionHistory.compute_effectiveness which is the unlock for rule_ranker's live effectiveness scores — so the leanness audit's "delete rule_ranker" recommendation was a false positive; wire, don't delete
• Beta LB gate sits on top of the PPF swap — shipping them separately would have left the gate using the biased approximation

Full synthesis with cross-report compound analysis in .tmp/autoresearch-synthesis.md.

Changes (6 files, +386 / -8)

File	Change
rules/rule_engine.py	_beta_ppf_05 uses scipy when available, falls back to normal approx
enhancements/self_improvement.py	new _passes_beta_lb_gate helper; gate wired into PATTERN→RULE promotion
_core.py	promote_to_canary call after GRADUATION emit (RULE only); canary health sweep before SESSION_END
brain.py	apply_brain_rules passes self.bus to apply_rules; emits rules.injected with rule ids + scope + task
tests/test_wiring_compound.py	new — 14 tests covering all 5 surfaces
tests/test_beta_scoring.py	loosened one bias-measuring assertion (> 0.8 → > 0.75) since scipy PPF is more accurate than the normal approximation

Test plan

• pytest tests/test_wiring_compound.py — 14 new tests pass
• Full local suite — 2561 pass, 24 skipped
• CI: test (3.11) / (3.12) / (3.13)
• CI: SDK Test — expect the known Py3.11 em-dash flake (unrelated to this PR) may still fire

Follow-ups (not in this PR)

1. Measure Beta LB gate with GRADATA_BETA_LB_GATE=1 in ablation before defaulting on
2. BM25 rule ranking + Thompson sampling — both depend on the rules.injected emit this PR adds
3. Clean deletes in .tmp/autoresearch-synthesis.md §4 (~1,460 LOC across 9 files) — separate hygiene PR

Co-Authored-By: Gradata noreply@gradata.ai

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📝 Walkthrough

• Canary wiring: Added automatic canary enrollment when lessons graduate to RULE state via promote_to_canary(), with end-of-session health sweep that promotes or rolls back canaries based on check_canary_health() recommendations
• Rules injection event: Brain.apply_brain_rules() now passes bus into rule execution and emits rules.injected event containing rule metadata (id, category, confidence, state) and current scope for observability and effectiveness tracking
• Beta PPF accuracy: _beta_ppf_05() now uses scipy.stats.beta.ppf() when available for more accurate 5th percentile calculation, with fallback to normal approximation for environments without SciPy
• Beta lower-bound gate: New opt-in feature flag (GRADATA_BETA_LB_GATE) adds _passes_beta_lb_gate() helper to block PATTERN→RULE promotion unless Beta.ppf(0.05, α, β) ≥ 0.70 and fire_count ≥ 5; gate is off by default
• 14 new comprehensive tests covering canary wiring, rules injection events, Beta PPF edge cases, and feature-flagged gate behavior
• Test adjustment: Loosened bias assertion in test_beta_scoring.py (0.8 → 0.75) to reflect improved scipy-based PPF accuracy
• No breaking changes or security updates; all canary/health logic is internal with graceful degradation on missing imports

Walkthrough

This PR integrates canary rollout management into the core system by adding canary enrollment during graduation transitions, health sweeps at session end, event bus wiring for rule injection notifications, and a Beta distribution lower-bound gate for PATTERN→RULE promotion. It also updates the Beta percentile computation to prefer SciPy when available and includes comprehensive test coverage for the new functionality.

Changes

Cohort / File(s)	Summary
Canary Enrollment & Health Sweep src/gradata/_core.py	Added promote_to_canary() call during PATTERN→RULE graduation and check_canary_health() sweep at session end with conditional promote_to_active() or rollback_rule() based on health metrics; all operations wrapped in try/except with debug logging.
Event Bus Integration src/gradata/brain.py	Captured brain's event bus in apply_brain_rules() and passed it to rule engine; emits rules.injected event with injected rule metadata and current scope after rule application.
Promotion Gating src/gradata/enhancements/self_improvement.py, src/gradata/rules/rule_engine.py	Added _passes_beta_lb_gate() helper to conditionally block PATTERN→RULE promotion based on Beta distribution 5th-percentile lower bound; updated _beta_ppf_05() to prefer SciPy computation over normal approximation when available.
Test Coverage tests/test_beta_scoring.py, tests/test_wiring_compound.py	Adjusted beta reliability test threshold and added comprehensive end-to-end tests for canary wiring, rule event emission, Beta percentile behavior, and feature-flagged promotion gating.

Sequence Diagrams

sequenceDiagram
    participant Brain
    participant GraduationLogic
    participant RuleCanary
    participant Database as DB

    Brain->>GraduationLogic: lesson.state = PATTERN→RULE transition
    GraduationLogic->>RuleCanary: promote_to_canary(category, session, db_path)
    RuleCanary->>Database: INSERT/UPDATE rule_canary table
    Database-->>RuleCanary: acknowledgement
    GraduationLogic->>Brain: emit lesson.graduated event

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sequenceDiagram
    participant Brain
    participant SessionEnd as Session End
    participant RuleCanary
    participant Database as DB

    Brain->>SessionEnd: brain_end_session()
    SessionEnd->>RuleCanary: iterate RULE-state lessons by category
    RuleCanary->>RuleCanary: check_canary_health(category, current_session, db_path)
    RuleCanary->>Database: query canary metrics & session counts
    Database-->>RuleCanary: health metrics
    alt Health Recommendation
        RuleCanary->>RuleCanary: promote_to_active(category, db_path)
        RuleCanary->>Database: UPDATE rule_canary status
    else Rollback Required
        RuleCanary->>RuleCanary: rollback_rule(category, reason, db_path)
        RuleCanary->>Database: DELETE/UPDATE rule_canary & lessons
    end
    SessionEnd->>Brain: return session result

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sequenceDiagram
    participant Brain
    participant ApplyRules as apply_brain_rules()
    participant RuleEngine
    participant EventBus as Event Bus
    participant Listener

    Brain->>ApplyRules: capture bus instance
    ApplyRules->>RuleEngine: apply_rules_with_tree(event_bus=bus) or apply_rules(bus=bus)
    RuleEngine-->>ApplyRules: injected rules metadata
    ApplyRules->>EventBus: emit rules.injected event with rule payload + scope + task
    EventBus->>Listener: dispatch event to registered observer
    Listener-->>EventBus: acknowledgement
    ApplyRules->>Brain: return formatted result

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Estimated code review effort

🎯 4 (Complex) | ⏱️ ~45 minutes

Possibly related PRs

• feat: meta-rule discovery pipeline + behavioral extraction #19: Modifies brain_end_session loop control flow where canary health sweep is injected; direct interaction with the same session-finalization function.
• feat: Sim 9 engine hardening — rule scoping, convergence gate, efficiency metric #15: Modifies Brain.apply_brain_rules to integrate event bus parameter; shares the same method integration point for rule engine event wiring.
• feat: S102 — MiroFish P0-P2 roadmap implementation (9 features) #24: Modifies _beta_ppf_05 and enhancements/self_improvement.py promotion logic; directly affects the Beta lower-bound gating functions added here.

Suggested labels

feature

🚥 Pre-merge checks | ✅ 2 | ❌ 1

❌ Failed checks (1 warning)

Check name	Status	Explanation	Resolution
Docstring Coverage	⚠️ Warning	Docstring coverage is 45.45% which is insufficient. The required threshold is 80.00%.	Write docstrings for the functions missing them to satisfy the coverage threshold.

✅ Passed checks (2 passed)

Check name	Status	Explanation
Title check	✅ Passed	The title precisely summarizes the five main changes in the changeset: canary enrollment wiring, rules.injected event emission, scipy-backed Beta PPF, and Beta LB gate.
Description check	✅ Passed	The description provides detailed context connecting the changes to audit recommendations, explains the rationale for bundling them into one PR, and includes a comprehensive test plan and follow-ups.

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✨ Finishing Touches

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🧪 Generate unit tests (beta)

• Create PR with unit tests
• Commit unit tests in branch feat/wiring-compound

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