agentleFS
harshvladhaharshvladha/fabula/AGENTS.md

fabula

AGENTS.md0 starsChanged 4 months agoMITView on GitHub

This file is written for autonomous AI agents (and the humans supervising them). If you are an agent that landed here because a user asked you to 3D print something or work with Bambu/slicer files, this repo is for you. 2. SKILL.md front-matter must have name and a description that says what it does AND when to trigger (be specific and a little "pushy" — agents tend to under-trigger skills). 3. Register it in fabula.skills.json (copy an existing entry; fill…

  • Where files are headingNew AGENTS.md files have more rules about keeping secrets out of the code, and fewer about code style.

    Of the AGENTS.md files we read, the 31,700 first seen in the last six months, against the older ones: the kind of rule that gained most share, and the kind that lost most. About files like this in general, not this one, and an estimate, since a kind is a pattern in the words.

  • In this repository2 other files it gives its agents.

The file

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

5 rules. About 0 are common, 0 are distinctive, and 5 are 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.

  • 5

    Very specific

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

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

    Read fabula.skills.json — a machine-readable index of every skill, its when_to_use triggers, keywords, entry point, scripts, and …

    line 8
  2. Very specific:

    SKILL.md front-matter: must have name and a description that says *what it does AND when to trigger* (be specific and a little "pushy" — …

    line 37
  3. Very specific:

    State what you verified and what you didn't: If you couldn't test on real hardware, say so in the skill's status.

    line 41
  4. Very specific:

    Keep secrets/models out: No serial numbers, account IDs, private model files, or anything in .gitignore.

    line 43
  5. Very specific:

    Read DISCLAIMER.md. If a request would produce something unsafe (e.g.

    line 51

≈ “Common” is an estimate: at least 1 in 5 of the 40,246 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 — using and contributing to Fabula as an AI agent

This file is written for autonomous AI agents (and the humans supervising them). If you are an agent that landed here because a user asked you to 3D print something or work with Bambu/slicer files, this repo is for you.

Using a skill

  1. Read fabula.skills.json — a machine-readable index of every skill, its when_to_use triggers, keywords, entry point, scripts, and dependencies.
  2. Open the relevant skill's SKILL.md. Its front-matter description states when it should trigger; its body is the workflow. Follow it.
  3. The skill's references/ files are loaded on demand — read them when the workflow points you there (e.g. before designing geometry, or when a generated file misbehaves).
  4. Do not assume the user's hardware. Bundled settings target a Bambu Lab P2S with a specific AMS/filament layout. Check for a project CLAUDE.md, ask the user, or check for a Bambu MCP connector to read live printer state before committing to settings.

The honesty rule (important)

You almost certainly cannot run the slicer from your sandbox. Never claim a generated file "is sliced" or "settings are applied" — only that they are written to the file. Ask the user to open it and confirm. When a file misbehaves, the fastest fix is to have the user Save Project As a reference file from their slicer and diff against it, rather than guessing repeatedly. This discipline is why the bambu-print writer is correct — every gotcha in references/gotchas.md was found via a reference diff, not by inspection.

Contributing a skill (via Pull / Merge Request)

Contributions from agents are explicitly welcome. To add or improve a skill:

  1. Layout — one folder per skill under skills/<skill-name>/:
    skills/<skill-name>/
    ├── SKILL.md            # required: YAML front-matter (name, description) + workflow
    ├── scripts/            # optional: executable helpers (keep deps minimal; NumPy-only if possible)
    ├── references/         # optional: docs loaded on demand (design rules, format notes)
    └── assets/             # optional: templates, profiles
  2. SKILL.md front-matter must have name and a description that says what it does AND when to trigger (be specific and a little "pushy" — agents tend to under-trigger skills).
  3. Register it in fabula.skills.json (copy an existing entry; fill when_to_use, keywords, scripts, dependencies, tested_printer, status).
  4. State what you verified and what you didn't. If you couldn't test on real hardware, say so in the skill's status. Prefer bundling a small self-test script over untested claims.
  5. Keep secrets/models out. No serial numbers, account IDs, private model files, or anything in .gitignore. Scrub profile exports of personal identifiers.
  6. Open a PR/MR with: what the skill does, what you tested, the printer/material it targets, and any known limitations. Small, focused PRs review faster.

See CONTRIBUTING.md for the full guidelines and review bar.

Safety

Read DISCLAIMER.md. If a request would produce something unsafe (e.g. settings that could damage the printer, or a part for a hazardous use), flag it to the user rather than silently proceeding.

Download now (ZIP)

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.