skill-compete
Skill0 starsChanged 29 days agoMITView on GitHub
Builds a better version of someone else's skill or plugin from scratch and proves it on the same tasks, with nothing copied. Use for "beat this skill". Not for testing your own (skill-eval).
- Installs packages
In this repository19 other files it gives its agents.
- AGENTS.mdAGENTS.md
- CLAUDE.mdCLAUDE.md
- skill-benchSkill
- skill-checkSkill
- skill-createSkill
- skill-descriptionSkill
- skill-evalSkill
- skill-factsSkill
- skill-improveSkill
- skill-learnSkill
- skill-packageSkill
- skill-planSkill
- skill-pluginSkill
- skill-publishSkill
- skill-releaseSkill
- skill-repoSkill
- skillSkill
- skill-tidySkill
- skill-tokensSkill
The file
We split this skill into the rules it gives an agent
3 rules. About 0 are common, 3 are distinctive, and 0 are very specific to this project.
≈0
Common · estimate
Many files like this have a rule of this kind.
≈3
Distinctive · estimate
This author's own choices. Worth a look.
0
Very specific
Tied to their project's names, files or tools. Probably skip.
- Common
- Distinctive
- Very specific
- Distinctive: line 8
Read theirs, build ours from scratch, measure both the same way.
- Distinctive: line 24
Run the engine on it, since numbers are fairer than impressions:
- Distinctive: line 37
Write the tasks once, covering what both promise, with real inputs.
≈ “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.
Files
Beat a skill
Read theirs, build ours from scratch, measure both the same way. Better means better on the same tasks with the numbers to show it, not longer.
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. Get it and read its licence
From GitHub, a skills directory, their disk, or pasted text. Read the licence before anything else and tell them what it allows: reading it to learn is always fine; reusing its code needs a licence that permits it and a credit; copying its text is never what we do, whatever the licence.
2. Take it apart
The skill-architect agent can do this teardown in a fresh context.
- What it does, step by step.
- What it does well: list every strength. Ours must match each one or beat it, or the comparison isn't honest.
- Where it stops: tools it doesn't work in, steps it skips, claims it doesn't test.
Run the engine on it, since numbers are fairer than impressions:
npx -y @thenavidm/skill-builder@latest check <theirs>
npx -y @thenavidm/skill-builder@latest tokens <theirs>3. Build ours
With skill-create, from the job, not from their text. Close the window with their skill before writing, so the words are ours.
4. The same tasks, both skills
Write the tasks once, covering what both promise, with real inputs. Run each skill on them in the same tools:
npx -y @thenavidm/skill-builder@latest eval <ours> --runs 3
npx -y @thenavidm/skill-builder@latest eval <theirs> --runs 3Add trigger on the same prompts if triggering matters, and bench if they use several tools. Have the skill-grader agent grade every run. A blind comparison helps when assertions can't capture quality: give the skill-comparator agent the two outputs for each task, unlabelled. Where an AI tool can't run headless, the skill-executor agent runs each task in a fresh context instead.
5. Prove it's ours
npx -y @thenavidm/skill-builder@latest overlap <ours> <theirs>It lists every run of eight or more words the two share. Rewrite any in our own words and run it again until there are none.
6. Report
A table: each strength of theirs and where ours has it; where ours goes further; the numbers for both on the same tasks; the overlap result. Say plainly where theirs still wins.
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
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.

