context-autopilot

Context Autopilot

Automated context collection for coding agents. Mines your real agent sessions — every instruction you repeated, every correction you made, every tool call you rejected — and distills them into CLAUDE.md / AGENTS.md rules you approve.

Part of The Context Layer.

$ npx context-autopilot scan

Scanned 3 session(s) for ~/projects/my-app
Found 26 signal(s):

  [CORRECTION] ×2 across 2 session(s)  (score 9)
      "There are still so many buttons that dont work, like the publish…"
  [REPEATED] ×4 across 3 session(s)  (score 10)
      "Do not reference the legacy directory. Only work within…"

$ npx context-autopilot distill

[1/8] Perform click-and-type tests before reporting UI work complete  (confidence: high)
    + Before declaring any screen done, click every button and verify it works.
    evidence:
      · 2026-06-27 — "There are still so many buttons that dont work…"

$ npx context-autopilot apply

Why

Every session starts blank, so you re-teach your agent the same conventions — and when you forget, it repeats the same mistakes. Hand-writing context files works but nobody keeps them current. And naive auto-generation is worse: research on LLM-generated context files found they reduce task success and raise cost, because repo scans produce generic filler.

Context Autopilot takes a third path: evidence. Your session history is a literal record of what the agent got wrong and what you said to fix it. Autopilot mines that record and only proposes rules your own words support — each one shipped with the quotes that justify it.

How it works

• Observe — ctxlayer scan parses your local Claude Code transcripts (~/.claude/projects) and extracts three signal types: instructions repeated across sessions, corrections after the agent went wrong, and rejected tool calls. Runs 100% locally.
• Distill — ctxlayer distill sends the signals (not your history) through Claude — via your existing claude CLI, no API key needed — and gets back imperative, project-specific rules with evidence and confidence ratings.
• Approve — ctxlayer apply walks you through each proposal. Accepted rules land in a managed block:

<!-- ctxlayer:begin -->
## Learned conventions (Context Autopilot)

- **Staff login cannot access admin view** — When authenticated as staff, the admin role toggle must be hidden or disabled.
<!-- ctxlayer:end -->

Hand-written content is never touched; re-runs update the block idempotently. Rules are written to both CLAUDE.md and AGENTS.md, so Claude Code, Cursor, Copilot, Codex, and every AGENTS.md-aware agent benefits.

Install

npm install -g context-autopilot   # or use npx, no install

Commands

Command	What it does
ctxlayer projects	List projects with observable session history
ctxlayer scan	Mine signals from this project's sessions
ctxlayer distill	Distill signals into proposals (.ctxlayer/proposals.json)
ctxlayer apply	Review proposals interactively; write accepted ones
ctxlayer export	Export distilled entries as Agent Operating Procedure JSON

Options: --project <path>, --model <model>, --min-score <n>, --yes, --json.

Claude Code plugin

/plugin marketplace add chiragbachani/context-autopilot
/plugin install context-autopilot@the-context-layer

Then ask Claude to "update project context from my session history."

MCP server

{
  "mcpServers": {
    "context-autopilot": {
      "command": "npx",
      "args": ["-y", "-p", "context-autopilot", "ctxlayer-mcp"]
    }
  }
}

Exposes list_observable_projects, scan_context_signals, and distill_context_proposals.

Privacy

Everything runs on your machine. Transcripts are parsed locally; only the extracted signals (short quotes of your own instructions) are sent to the model you already use for coding. Nothing is uploaded anywhere else, ever.

Roadmap

Coding agents are chapter one. The engine is source-agnostic — it distills observations of work into Agent Operating Procedures (AOPs):

• Now: Claude Code transcripts → CLAUDE.md / AGENTS.md
• Next: Cursor session logs; staleness detection (flag rules the repo has outgrown); team-shared context
• Later: browser-workflow observation → AOPs for web tasks; ambient capture — until agents absorb the work you repeat, without you ever "building an agent"

License

MIT © The Context Layer