lamarck
A production self-evolving system for agent skills, driven by real invocations.
Free
Works with the AI Agents you already use
Claude Code
Cursor
Codex CLI
Muse
Dots+22 moreClaude CodeCursorCodex CLIMuseDots
OpenClaw
Manus
Grok
Grok Bot+18 agentslamarck
Example session with this skill installed
/lamarck audit my-deploy-skill
- Read your context and instructions
- Compiled the lamarck
Summary
Two separate calls of my-deploy-skill missed the same step. Both ran a deploy command while the git working tree was dirty. The evidence gate is open. No file has been edited yet.
Evidence
| Check | Result |
|---|---|
| Same kind of gap | 2 separate calls |
| Trust tier for this skill | evolve (asks you before any edit) |
| Default for skills you have not listed | observe (log only, no edits) |
| Where the evidence lives | local ledger only (data/ledger.jsonl) |
Proposed edit
Insert one condition in that skill's SKILL.md: if git status shows a dirty tree, stop and list the dirty paths before any deploy command.
The proposal is one insertion. Replay cases harvested from both calls are attached. The background worker will replay them before the edit is kept.
Next steps
- Apply now. The worker edits the skill, replays the cases, and writes one line to data/inbox.md.
- Suggestion only. Save suggestions/my-deploy-skill.md and leave the skill file unchanged.
- Reject. The reason is stored in data/rejected.md so this proposal is not repeated unless new evidence appears.
lamarck itself is not on the auto tier. A plugin or a synced skill would only get a suggestion. It would not be edited in place.
Connects securely to your tools. The creator never sees your data.
About this skill
lamarck is a production self-evolving system for agent skills. Install it once. Every installed skill keeps a record of real invocations, and it changes only when an evidence gate opens.
It is not a one-shot optimizer for one hand-picked skill. Adapters for Claude Code, Codex, Cursor, and pi write one local ledger. Telemetry stays on your machine. License: MIT. Source: https://github.com/newdee/lamarck-skill
What it does
- Logs every skill call and stamps it with that skill file's content hash.
- Runs a short evaluation at the end of a turn. You choose every turn, manual only, or a batch (default: 5).
- Turns one user correction into a rubric entry for that skill.
- Proposes a small edit only after two separate calls show the same kind of gap.
- Asks you to apply the edit, keep it as a suggestion, or reject it. Auto-apply is opt-in, and a failed replay rolls the edit back. lamarck itself never runs on auto.
- Prunes instructions that go unused.
How it works
- A hook appends each call to data/pending.jsonl.
- A stop hook runs the evaluation. Verdicts go to data/ledger.jsonl. Replay cases come from real traces.
- When the gate opens, you get three choices. If you apply, a background job edits the skill, replays the cases, writes the ledger, and notifies you.
- If the new version does worse than the old one, lamarck proposes a rollback.
Install
npx lamarck-skill
Requires Node.js 18+ and git. The installer wires Claude Code hooks, then runs a self-test. Codex, Cursor, and pi use the adapters shipped in the package.
Why the gate matters
Edits stay small, need your approval, and can be reverted. Plugins and synced skills are never edited in place. A skill with a long clean streak drops to spot-checks instead of being rewritten every turn.
How to use
Skills on Agensi run inside your AI agent. Copy the prompt, paste it into your agent, and it connects to Agensi and installs this skill for you. If a payment is needed, your agent shows it to you first.
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Requires
Node.js
github
macOS