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 Cursor sessions 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
Commands
ctxlayer projects | List projects with observable session history (Claude Code + Cursor) |
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 stale | Find context-file references the repo has outgrown — missing files, removed npm scripts. Exits 1 on findings, so it drops straight into CI |
ctxlayer export | Export distilled entries as Agent Operating Procedure JSON |
Options: --project <path>, --source claude-code|cursor|all, --model <model>, --min-score <n>, --yes, --json.
Cursor session mining reads Cursor's local SQLite storage via Node's built-in node:sqlite (Node 22+; on older Node the Cursor source is skipped gracefully).
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, distill_context_proposals, and find_stale_context.
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 + Cursor sessions → CLAUDE.md / AGENTS.md; staleness detection (
ctxlayer stale)
- Next: team-shared context; a GitHub Action for context linting in CI
- 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