agentleFS
thenavidmthenavidm/skill-builder/skills/skill-learn/SKILL.md

skill-learn

Skill0 starsChanged 29 days agoMITView on GitHub

Applies a correction to every skill it touches, with a diff to approve for each and their evals run again. Use for "from now on, never X" or after correcting an output.

  • Installs packages

2 other projects use a version of this.

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The file

We split this skill into the rules it gives an agent

3 rules. About 0 are common, 2 are distinctive, and 1 is very specific to this project.

  • ≈0

    Common · estimate

    Many files like this have a rule of this kind.

  • ≈2

    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:

    Ask, with your recommendation:

    line 18
  2. Very specific:

    Read the description and steps of every skill where .agents/skill/setup.md says their skills live, and any plugin repositories they name.

    line 25
  3. Distinctive:

    Add a task to the skill that checks the new rule, so it stays proven.

    line 46

≈ “Common” is an estimate: at least 1 in 5 of the 350,495 skill 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
SKILL.md

Learn from a correction

A correction given once should reach every skill it applies to, and stay proven. This finds those skills, changes each with the person's yes, and runs their tests again so the lesson doesn't break something else.

The engine runs as npx -y @thenavidm/skill-builder@latest. Where skill-builder is installed (npm install -g @thenavidm/skill-builder), run skill-builder instead: it's the same engine, without the download.

1. State the lesson

Write it as one rule with its reason, in their words: "Links never go in the body of a post, because the platforms show posts with links to fewer people." Collect lessons from what they said in this conversation, from review notes (feedback.json), or from what they pasted. Several lessons go through these steps one at a time.

2. Rule or memory?

Ask, with your recommendation:

  • A rule for skills: about how a task is done ("dates as 10 November 2026"). It goes into the skills.
  • A general preference: about how they like to work with the AI ("explain before you change things"). It goes to their AI tool's memory or instructions file, not into skills.

3. Find every skill it touches

Read the description and steps of every skill where .agents/skill/setup.md says their skills live, and any plugin repositories they name. Sort them:

SureThe skill does the thing the rule is about
LikelyThe skill sometimes does it
NoUnrelated

Show the list and let them confirm which to change.

4. One change per skill, each approved

For each, have the skill-writer agent draft the change (or draft it yourself), then show the exact diff: where the rule goes and how it's worded for that skill. Change only what the rule needs. If a skill already has a rule that contradicts this one, ask which wins. Apply the ones they approve, and bump the skill's version in metadata (or the plugin's in package.json through skill-release).

5. Prove nothing broke

For each changed skill that has evals, run them and compare with before:

npx -y @thenavidm/skill-builder@latest eval <skill> --runs 3

Add a task to the skill that checks the new rule, so it stays proven. Report, per skill: changed, the before and after pass rate, and anything that got worse.

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.