Local-first, multi-agent coding session archive. Discover, export, and baseline your AI coding sessions across Claude Code, Codex CLI, Gemini, DeepSeek, Grok, and VS Code agents (via the companion router extension).
The Python hub installs as
agent-session-hubon PyPI; the VS Code companion isavidullu.agent-session-routeron the Marketplace (code --install-extension avidullu.agent-session-router).
New here? → Getting Started (5-minute guide)
Agent-assisted setup? → Agent-Assisted Setup (give any capable agent a prompt; it sets up the archive on a new machine)
Questions? → FAQ
Want to contribute? → CONTRIBUTING.md
Note: This tool has been manually tested on Windows, WSL, and Ubuntu. macOS support is provided through the same code paths but has not been validated by the developer (who does not own a Mac). If you hit macOS-specific issues, please file a bug — PRs welcome!
| Agent | Platform | Via |
|---|---|---|
| Claude Code | Windows, macOS, Linux, WSL | Direct Python importer |
| Codex CLI | Windows, macOS, Linux | Direct Python importer |
| Gemini Antigravity | Windows, macOS | Direct Python importer |
| Grok | WSL, Linux | Direct Python importer |
| DeepSeek V4 | VS Code (all platforms) | Direct Python importer |
| GitHub Copilot Chat | VS Code (all platforms) | Router extension |
| Continue, Cline, Cody, Aider, Tabby | VS Code (all platforms) | Router extension |
Configure sources in sources.toml (copy from sources.example.toml). Platform-specific examples included for Windows, macOS, Linux, and WSL.
# Install
pip install agent-session-hub
# Discover sessions
agent-archive discover --write docs/DISCOVERY.md
# Export to Markdown
agent-archive export --all
# Check status
agent-archive statusSee Getting Started for full setup including the VS Code extension, PDF export, and daily automation.
Prefer to let an agent do the setup? See Agent-Assisted Setup — a carefully written prompt that lets Codex, Claude, Gemini, Grok, or another capable agent clone, install, discover, validate, and produce a first archive + structured setup report on a new machine.
Optional PDF output:
python .\tools\agent_archive.py export --all --pdfOptional raw backups:
python .\tools\agent_archive.py export --all --copy-rawRaw files land under raw/, which is ignored by Git unless you intentionally
force-add it.
discover --write docs\DISCOVERY.md refreshes the local source inventory:
- configured source roots, whether each root exists, and matching file counts;
- sample files per source;
- inventory-only sources such as Copilot/ZAI storage locations, even when they are not exportable transcript sources yet.
status prints archive freshness and convergence signals:
- indexed records, visible configured files, new files, and changed files;
- indexed records not visible from this machine, preserved from other machines;
- source counts and inferred origin environments.
export --all writes Markdown archive artifacts and updates the shared catalog:
archive/**/*.mdarchive/index.jsonlarchive/INDEX.md
export --all --pdf also writes archive/**/*.pdf when reportlab is
installed. The .[dev] install includes reportlab; to check a minimal
environment, run:
python -c "import reportlab; print('reportlab ok')"If PDF support is missing, Markdown export still works. The CLI will report that
PDF export requires reportlab.
Some configured sources are intentionally inventory-only. A message like this is expected unless transcript files exist in supported locations:
Skipped sources without extractors:
- copilot-vscode-windows-inventory (inventory)
- copilot-vscode-wsl-ubuntu-inventory (inventory)
- zai-vscode-wsl-ubuntu-inventory (inventory)
After a real export, review only the intended generated paths:
git status --short archive/ docs/DISCOVERY.mdStage explicit paths only. Do not commit sources.toml, raw/, or unrelated
files.
Run CI's gates locally, with CI's pinned toolchain, in a throwaway venv:
./scripts/local_ci.shThat runs ruff check, mypy, and the test suite with coverage — the same
commands as .github/workflows/ci.yml — and refuses to run at all if the script
has drifted from the workflow. Use --lint-only for a fast inner loop, but note
it is not the CI verdict.
scripts/pre-push is an opt-in git hook that runs the gates and aborts a push
that would go red. Install it once per clone:
ln -s ../../scripts/pre-push .git/hooks/pre-pushThe hook gates the commits being pushed, not whatever happens to be checked out.
Documentation-only pushes are skipped automatically; SKIP_LOCAL_CI=1 git push
and git push --no-verify are the explicit bypasses. Full details, including the
drift guard, the parity limits, and the Windows/WSL install path, are in
docs/LOCAL_CI.md.
To set this up on a new computer with Codex, Claude, Gemini, Grok, DeepSeek, or another capable local agent, give the agent this prompt from the machine you want to add:
Set up my private agent-sessions archive on this computer.
1. Clone or open the repo:
https://github.com/avidullu/agent-sessions
Pull with `git pull --ff-only` before reading files.
2. Install local tooling in a Python 3.11+ environment:
`python -m pip install -e ".[dev]"`
3. Validate the repo and report results. Use POSIX-style paths in the prompt;
PowerShell users may substitute `.\tools\...` and `docs\DISCOVERY.md` if
they prefer:
- `python -m pytest --cov=agent_sessions --cov-report=term-missing`
- `python -m ruff check .`
- `python -m mypy agent_sessions tools`
- optional/informational: `python tools/agent_archive.py baseline eval --dry-run`
4. Discover local agent stores:
- `python tools/agent_archive.py discover --write docs/DISCOVERY.md`
- `python tools/agent_archive.py status`
If defaults miss a local path, create or edit ignored `sources.toml`; do not
commit `sources.toml`.
5. Ask me which sync mode I want before enabling it:
- manual: export only when I ask
- scheduled: daily Task Scheduler/cron export
- triggered: filesystem watcher with debounce
Ask separately whether to generate PDFs.
6. If I approve the first sync, run:
`python tools/agent_archive.py export --all --pdf`
Then stage only `archive/` changes. Push directly only if I explicitly
approve this as a one-time archive sync; otherwise branch and open a PR.
7. Finish with a short setup report: validation status, agents discovered,
total indexed sessions, new/changed files, origin environments, sync mode,
and 1-2 promoted guardrails from `baseline/global/` or optional
`baseline suggest --dry-run` output that show the value.
Do not commit raw logs, `sources.toml`, unrelated files, or merge PRs without
explicit approval scoped to that PR or project.
The final setup report should be plain enough to review at a glance:
Repo validation:
- Tests/coverage:
- Ruff:
- Mypy:
- Baseline eval:
Local archive status:
- Agents/sources discovered:
- Indexed sessions:
- New files:
- Changed files:
- Origin environments:
Sync:
- Selected mode:
- PDF export:
- Last export/commit:
Value preview:
- Guardrail/pattern 1:
- Guardrail/pattern 2:
- Evidence breadcrumbs:
See docs/AUTOMATION.md for scheduled export details and docs/MULTI_MACHINE.md for how indexes converge across computers. For a step-by-step manual checklist, see docs/NEW_MACHINE_SETUP.md.
- Add a source entry in
config/default_sources.tomlor localsources.toml. - Add an extractor module under
agent_sessions/sources/. - Register it with
@register("<kind>"). - Run a dry export with
--source <kind> --limit 1 --dry-run.
The original promote/publish/calibrate closure proof is documented in docs/archives/BASELINE_LOOP_CLOSURE.md. The newer knowledge and replay tracker is complete in docs/archives/BASELINE_KNOWLEDGE_REPLAY_PLAN.md, with current health and follow-ups summarized in docs/archives/WORK_AUDIT_2026-07-08.md.
Useful health checks:
python .\tools\agent_archive.py baseline lint --dry-run
python .\tools\agent_archive.py baseline eval --dry-run
python .\tools\agent_archive.py baseline handoffs audit --dry-run
python .\tools\agent_archive.py baseline replay select --dry-runCreate or refresh the baseline scaffold:
python .\tools\agent_archive.py baseline scaffoldExpected output: missing baseline folders and templates are created under
baseline/, including calibration examples and proposal scaffolding. Existing
files are preserved.
Generate reviewable candidate predictions from the archive:
python .\tools\agent_archive.py baseline suggestExpected output: a dated candidate report appears under baseline/candidates/,
with a matching .predictions.json sidecar, and the prediction ledger under
baseline/metacognition/ is updated. Candidate reports are suggestions with
provenance and calibration hooks. Copy
baseline/calibration/feedback.example.toml to
baseline/calibration/feedback.toml to mark predictions as accepted, edited, or
rejected before the next run.
Summarize calibration feedback against the latest prediction sidecar:
python .\tools\agent_archive.py baseline calibrate --feedback baseline\calibration\feedback.tomlCreate a local evidence bundle for an authorized AI agent to draft proposals:
python .\tools\agent_archive.py baseline bundle --focus badminton-highlight-indexerThis repo owns durable export and baseline generation. Search, Claude-specific browsing, live capture, and runtime memory are delegated to external tools where they are already stronger. See docs/COMPOSE_STACK.md.
Daily export automation is documented in docs/AUTOMATION.md. Multi-machine indexing is documented in docs/MULTI_MACHINE.md.
This repo also hosts a Claude Code plugin marketplace (agent-sessions-tools).
Install the pr-review-loop PR-reviewer plugin from any session:
/plugin marketplace add avidullu/agent-sessions
/plugin install pr-review-loop@agent-sessions-toolsSee plugins/pr-review-loop/README.md.
Clone this private repo on another machine, follow
docs/NEW_MACHINE_SETUP.md, commit the new archive/
Markdown/PDF files, and push.
The archive index is merge-aware, so records from other machines remain in the
unified view when one machine exports only the local sources it can see.
If a machine has different usernames, WSL distribution names, or custom storage
paths, copy sources.example.toml to sources.toml and edit the roots. The
local sources.toml is ignored by Git.
See docs/ROADMAP.md for optional future importers and archive automation ideas.
The engineering-baseline idea is sketched in docs/ENGINEERING_BASELINE.md. The current implementation plan is tracked in docs/BASELINE_PLANNING.md.