agent-learner 0.3.18

Reusable self-learning engine for agent workflows

agent-learner

Reusable learning control plane for coding-agent workflows.

agent-learner helps you:

• capture learned rules from agent work
• keep project-local and global learning assets separate
• review candidates and promote useful rules
• use a dashboard UI for history, rules, and promotions

It is a learning system, not a unified wiki layer.

It is designed to layer onto existing agent environments rather than replace them.

Start here

If you want the shortest one-line setup, use one of these:

pipx install "agent-learner[web]" && agent-learner dashboard --project-root "$PWD" --open
npx @cafitac/agent-learner@latest dashboard --project-root "$PWD" --open

If you want a preflight check first, run doctor before dashboard.

The dashboard defaults to 127.0.0.1:8766 to avoid common local MCP/gateway ports such as 8765.

doctor tells you whether the dashboard can run now, what is missing, and the next command to use.

Choose your path

1. Published Python package

pipx install "agent-learner[web]" && agent-learner dashboard --project-root "$PWD" --open

2. npm / npx wrapper

npx @cafitac/agent-learner@latest dashboard --project-root "$PWD" --open

3. Source checkout

./bin/dashboard.sh doctor
./bin/dashboard.sh --open

4. Optional Docker path

docker compose up --build

Docker is optional convenience only. It is not the primary OSS install path.

Typical workflow

1. Install the Codex hook once at user scope or per project
2. Run doctor
3. Open the dashboard
4. Review rules, candidates, and history
5. Promote reusable learning assets to the global layer when appropriate

Core concepts

Project-local vs global learning

• project-local knowledge lives under <project>/.agent-learner/
• reusable shared knowledge lives under ~/.agent-learner/global/
• retrieval is local-first, then global
• Codex can be installed once at user scope while still writing learning assets per project
• external wiki/KB systems remain separate and are not part of the canonical learning lifecycle

Indexed retrieval and pruning

• rules are indexed into machine-readable metadata under .agent-learner/index/rules.json
• a human-readable summary is also written to .agent-learner/index/index.md
• retrieval uses the index first, then loads only the top matching rules
• approved rules are injected by default; needs_review and deprecated stay out unless explicitly requested
• use agent-learner rebuild-index --project-root "$PWD" if you want to force a full reindex after manual edits

Main runtime

The primary UI/runtime path is:

• FastAPI backend
• built React dashboard frontend

Static dashboard generation and stdlib-only serving still exist, but they are secondary paths.

Key commands

agent-learner doctor --project-root /path/to/repo
agent-learner dashboard --project-root /path/to/repo --open
agent-learner install-codex
agent-learner bootstrap --target /path/to/repo
agent-learner review-candidates --project-root /path/to/repo
agent-learner history --project-root /path/to/repo --latest-per-rule --last 10
agent-learner history-summary --project-root /path/to/repo --by adapter-decision
agent-learner overview --project-root /path/to/repo --format json
agent-learner rebuild-index --project-root /path/to/repo
agent-learner install-codex --target /path/to/repo
agent-learner update

Repository shape

• src/agent_learner/ — Python core
• frontend/ — React + Vite dashboard UI
• bin/ — shell / wrapper entrypoints
• tests/ — CLI, lifecycle, wrapper, and dashboard tests
• docs/ — install, architecture, release, and smoke docs

Docs

• Start here:

  • docs/install.md — install and run paths
  • docs/quickstart.md — shortest command sequences

• Release and publish:

  • docs/publish-smoke-checklist.md — post-publish smoke matrix
  • docs/release-process.md — tag order and release flow
  • docs/distribution.md — Python core vs npm wrapper strategy

• Architecture:

  • docs/architecture.md
  • docs/adapter-convergence.md
  • docs/scope-learning-system.md
  • docs/storage-independence-and-provenance.md

• docs/install.md

• docs/quickstart.md

• docs/architecture.md

• docs/adapter-convergence.md

• docs/scope-learning-system.md

• docs/storage-independence-and-provenance.md

• docs/distribution.md

• docs/publish-smoke-checklist.md

• docs/release-process.md

• docs/prerelease-checklist.md

Status

Current implemented areas:

• local/global learning split
• merged retrieval
• candidate/rule/history lifecycle
• dashboard UI
• global promotion and sync
• npm wrapper + source checkout helper

Release note

If you are validating a release, use:

python scripts/release/publish_smoke_check.py --json
python scripts/release/published_runtime_smoke.py --project-root /path/to/repo --json --skip-commands

Or from a source checkout:

./bin/publish-smoke.sh --json

Then follow docs/publish-smoke-checklist.md.

Wrapper convenience

Common wrapper aliases now work directly:

agent-learner install-codex --target "$PWD"
agent-learner install-claude --target "$PWD"
agent-learner rebuild-index --project-root "$PWD"
agent-learner bootstrap --target "$PWD"
agent-learner update
agent-learner completion zsh

Shell completion

Zsh:

echo 'source <(agent-learner completion zsh)' >> ~/.zshrc
source ~/.zshrc

Bash:

echo 'source <(agent-learner completion bash)' >> ~/.bashrc
source ~/.bashrc