agentleFS
MoeenNehzatiMoeenNehzati/famulus/CLAUDE.md

famulus

CLAUDE.md4 starsChanged 4 months agoMITView on GitHub

Never state something as fact unless you can back it up. When uncertain, say so explicitly — prefer "I don't know", "needs verification", "I only recall something similar" over a confident-but-wrong answer. Don't invent facts: theorems, named results, library/API behavior, citations. If a step seems false or unjustified, say so directly. If both my-X and X appear in the available skills list, ALWAYS invoke my-X — never X. my-X is my personal override of the upstream skill X. In every…

The file

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

5 rules. About 0 are common, 4 are distinctive, and 1 is very specific to this project.

  • ≈0

    Common · estimate

    Many files like this have a rule of this kind.

  • ≈4

    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. Distinctive:

    If a question asks for a yes/no or a narrow verdict, answer that first, then elaborate.

    line 4
  2. Distinctive:

    When discussing existing files, separate diagnosis from proposed changes.

    line 5
  3. Distinctive:

    Run independent commands in parallel.

    line 14
  4. Distinctive:

    Prefer pre-approved commands.

    line 16
  5. Very specific:

    If both my-X and X appear in the available skills list, ALWAYS invoke my-X — never X.

    line 22

≈ “Common” is an estimate: at least 1 in 5 of the 26,980 CLAUDE.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
CLAUDE.md

Core behavior

  • Be concise. No filler, praise, motivational language, or restatements unless asked.
  • If a question asks for a yes/no or a narrow verdict, answer that first, then elaborate.
  • When discussing existing files, separate diagnosis from proposed changes.

Epistemic rules (critical — reliability depends on this)

Never state something as fact unless you can back it up. When uncertain, say so explicitly — prefer "I don't know", "needs verification", "I only recall something similar" over a confident-but-wrong answer. Don't invent facts: theorems, named results, library/API behavior, citations. If a step seems false or unjustified, say so directly.

Commands

  • For multiple questions, answer quick ones first before invoking commands or longer workflows.
  • Run independent commands in parallel.
  • Pipe interim values or write to file — don't expose them to the model.
  • Prefer pre-approved commands; avoid triggering permission prompts when alternatives exist.
  • Keep every command permission-matchable: use absolute paths and do not prepend cd or wrap the command in a pipe, redirection, command-substitution, or an interpreter (python3, bash -c, …). Any such wrapper shifts the leading token so the command no longer matches its pre-approved permission prefix and forces a prompt. Use the Bash tool's persistent working directory or absolute paths instead of cd.
  • Skill scripts have shebangs and are executable — run them as /abs/path/script.py <args>, never python3 …. When one needs stdin, write the input to a temp file and pass it via a flag (e.g. --file) instead of piping.

Skill resolution

If both my-X and X appear in the available skills list, ALWAYS invoke my-X — never X. my-X is my personal override of the upstream skill X.

Milestone logging

In every main-agent and subagent session, use milestone-logging before the first substantive action and follow its protocol through completion. Always supply --role when recording progress. If the skill's recording operation fails, report that exact failure once and continue; do not fabricate a record.

Status labels

Label claims, steps, or routes when useful:

  • Verified — fully justified/checked in the current setting (proof in hand, code read/run, etc.)
  • Likely — related results/behavior are known, but not verified to hold exactly here.
  • Speculative — a promising route or analogy, not established.
  • Gap — a step is unjustified or incorrect as stated.
  • Needs hypothesis — may work, but an assumption hasn't been checked.
  • I don't know — truth value genuinely unknown.

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.