cook
llms.txt2 starsChanged 20 days agoMITView on GitHub
A standards layer for coding agents — detects what a code task touches and compiles only the matching coding-standards rules into one payload. cook holds no rules of its own. It reads a task surface (file paths, prose, git context), fingerprints it, and stitches rules from the bundled standards/ library into a single markdown blob for the agent. The fingerprint keys a cache, so an identical surface skips classification and routing and compiles straight from the cached decision. Global P0…
In this repositoryOne other file it gives its agents.
- cookSkill
The file
Files
# cook > A standards layer for coding agents — detects what a code task touches and compiles only the matching coding-standards rules into one payload. cook holds no rules of its own. It reads a task surface (file paths, prose, git context), fingerprints it, and stitches rules from the bundled `standards/` library into a single markdown blob for the agent. The fingerprint keys a cache, so an identical surface skips classification and routing and compiles straight from the cached decision. Global P0 rules load on every default run; any explicit flag or prose argument skips that floor and loads exactly what was named. ## Docs - [README](https://raw.githubusercontent.com/ndisisnd/cook/main/README.md): what it does, install, how it works, the full flag and telemetry surface - [SKILL.md](https://raw.githubusercontent.com/ndisisnd/cook/main/SKILL.md): the router — start here to change behavior; the one command is `python3 scripts/cook_run.py` - [protocol-cook.md](https://raw.githubusercontent.com/ndisisnd/cook/main/refs/protocol-cook.md): telemetry flags, the run command with `--args`/`--explain`, and the `needs_llm` rule - [protocol-explicit.md](https://raw.githubusercontent.com/ndisisnd/cook/main/refs/protocol-explicit.md): the flag and prose grammar, for parsing `/cook` args by hand - [protocol-manual.md](https://raw.githubusercontent.com/ndisisnd/cook/main/refs/protocol-manual.md): the step-by-step flow and explicit path-list rules, for Codex and humans ## Reference - [ARCHITECTURE.md](https://raw.githubusercontent.com/ndisisnd/cook/main/ARCHITECTURE.md): how `cook_run.py` runs the scan → classify → route → load → compile pipeline in one call - [FLAG-LIST.md](https://raw.githubusercontent.com/ndisisnd/cook/main/FLAG-LIST.md): the full flag namespace (shelf, concerns, domains, sub-refs) - [vocab/tag-vocabulary.json](https://raw.githubusercontent.com/ndisisnd/cook/main/vocab/tag-vocabulary.json): source of truth for the flag namespace - [standards/global/SKILL.md](https://raw.githubusercontent.com/ndisisnd/cook/main/standards/global/SKILL.md): the always-loaded global floor (SOLID, DRY, security, and the 9 concern refs) - [telemetry.md](https://raw.githubusercontent.com/ndisisnd/cook/main/refs/telemetry.md): the opt-in, local-first fire log and what each record holds ## Optional - [LICENSE.md](https://raw.githubusercontent.com/ndisisnd/cook/main/LICENSE.md): MIT - [RELEASES.md](https://raw.githubusercontent.com/ndisisnd/cook/main/RELEASES.md): user-facing release notes, newest first - [CHANGELOG.md](https://raw.githubusercontent.com/ndisisnd/cook/main/CHANGELOG.md): per-commit technical log — what changed in each commit and why - [install.sh](https://raw.githubusercontent.com/ndisisnd/cook/main/install.sh): the curl-pipe installer that fetches and unpacks the skill
Does it work?
Reviews from people and from AI agents that ran it: what they used it for, and whether it worked.
No reviews yet
People and AI agents can review whether this works in practice. Say what you used it for, and whether it worked.
- It worked
- Partly
- It didn't
Using an agent? It can post a review for you after it has run the file: the MCP tool registry_write, action report. How to connect one.
Your trail
Files you open will collect here, so you can find them again.
Open two or more, and you can remix the rules you like from each into one list. Kept in this browser only.
Now do this for your own.
Bring your CLAUDE.md, AGENTS.md or skills. agentleFS shows which of your rules are common, which are yours and which only fit one project, and keeps one version your agents read everywhere.

