agentleFS
Haifai-AIHaifai-AI/baby-whale/.agents/notes/AGENTS.md

baby-whale / notes

AGENTS.md1 starsChanged 45 days agoMITView on GitHub

Agent Notes are effectively RFCs written by agents: durable proposals and decision records that preserve rationale, alternatives, consequences, and required verification. Follow the documentation standard and the Agent Note rules. Every new Agent Note triggers a supersession check. Search the active tree for older notes covering the same decision or mechanism, classify any full or partial supersession with dsh-archive-agent-notes, and archive every qualifying implemented triplet in the same PR. Keep partial supersessions active and cross-linked. Files under archived/ are frozen…

We split this AGENTS.md into the rules it gives an agent

1 rule. About 0 are common, 0 are distinctive, and 1 is very specific to this project.

  • ≈0

    Common · estimate

    Many files like this have a rule of this kind.

  • ≈0

    Distinctive · estimate

    This author's own choices. Worth a look.

  • 1

    Very specific

    Tied to their project's names, files or tools. Probably skip.

  • Common
  • Distinctive
  • Very specific
  1. Very specific:

    Every new Agent Note triggers a supersession check: Search the active tree for older notes covering the same decision or mechanism, …

    line 5

≈ “Common” is an estimate: at least 1 in 5 of the 36,368 AGENTS.md files we read have a rule of the same kind, not the same words. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.

Keep what fits and drop the rest. Your version, ready for your agents.
Files
AGENTS.md

AGENTS.md — Agent Notes

Agent Notes are effectively RFCs written by agents: durable proposals and decision records that preserve rationale, alternatives, consequences, and required verification. Follow the documentation standard and the Agent Note rules.

Every new Agent Note triggers a supersession check. Search the active tree for older notes covering the same decision or mechanism, classify any full or partial supersession with dsh-archive-agent-notes, and archive every qualifying implemented triplet in the same PR. Keep partial supersessions active and cross-linked.

Files under archived/ are frozen historical snapshots: never edit them or treat them as current authority.

Download now (ZIP)

Trending

Steady: 0 new projects took it in the last 4 weeks, none the 4 weeks before.thin data

Week of Aug 30: 0 new projectsWeek of Sep 6: 0 new projectsWeek of Sep 13: 0 new projectsWeek of Sep 20: 0 new projectsWeek of Sep 27: 0 new projectsWeek of Oct 4: 0 new projectsWeek of Oct 11: 0 new projectsWeek of Oct 18: 0 new projects
Aug 2026Sep 2026Oct 2026
New projects taking a version of this file each week, over the 8 weeks our latest run read: only 0 in all, so this is a hint, not a trend.

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
What did you use it for? e.g. Reviewing pull requests in a Rails app

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.