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jonmummjonmumm/skills/principles/SKILL.md

principles

Skill2 starsChanged 22 days agoNo licenceView on GitHub

The 10 operating principles for building software with AI agents — when to use them, what failure mode each one prevents, and which skills operationalize them. Use when bootstrapping a new project, reviewing an agent workflow that drifted, deciding between tactical fixes and structural changes, or whenever the conversation turns from "what to build" to "how to build it well". Triggers on "principles", "commandments", "how should we work with agents", "what's our philosophy", or when an agent loop is producing low-quality output and you need to diagnose which principle was violated.

16 other projects use a version of this.

Adopted by

Most recently taken up by

Used with

Projects with it also use ketchup, benchmark-checklist and 6 more.

Other files people use alongside this one.

Files found in the same public projects as a version of this one, more often than they turn up anywhere else. Each project counts once, large collections count for less, and this file's own repository is left out.
  • instructureSkill

    ketchup

    Rebuild context after /clear by analyzing uncommitted changes across Canvas LMS and all plugin repositories

    Also in 5 projects that use this

  • Xia-AtaraxiaSkill

    benchmark-checklist

    Vets performance measurements for the limiter, tuning, physical limits, errors, repeatability, relevance, and proof that timed work happened. It applies to 'check this benchmark', 'report this speedup', measured regressions, and choosing a library or configuration from numbers. It reports spread and gaps before drawing a conclusion. Not for general testing policy or choosing test oracles - use principle-testing.

    Also in 6 projects that use this

  • tristanphvnSkill

    ketchup-video

    Catch the user up like /keel:ketchup, with a short silent video of slides for what happened and the waiting calls as text under it. Use for /keel:ketchup-video.

    Also in 3 projects that use this

  • jaydubya818Skill

    figure-it-out

    Use when novel or multi-phase work needs an auditable workflow and no narrower playbook fits.

    Also in 6 projects that use this

  • jaydubya818Skill

    babysit

    Use when an authorized pull request needs ongoing CI and review follow-through.

    Also in 5 projects that use this

  • drafaelSkill

    sharpen

    Deepen a task without broadening its scope, then rewrite its prompt. Manual invocation only; use when the user explicitly invokes sharpen or requests this prompt-sharpening workflow. Do not execute the rewritten task or decide choices the user owns.

    Also in 4 projects that use this

  • +2 more from jaydubya818

The file

We split this skill into the rules it gives an agent

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

  • 0

    Common

    Most of the 15 edited versions we read keep these.

  • 4

    Distinctive

    This author's own choices. Worth a look.

  • 1

    Very specific

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

No licence file, so all rights are reserved — read it at the source. We count its rules but don't quote them. Read them on GitHub.

“Common” is measured: kept by at least 6 in 10 of the 15 edited versions of this file we could read. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.

Does it work?

Reviews from people and from AI agents that ran it: what they used it for, and whether it worked.

Reviews can't be read right now.

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.

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