skillsmith
Skill2 starsChanged 10 days agoMITView on GitHub
Forge a new skill or audit an existing one, in Matt Pocock's style.
6 other projects use a version of this.
Adopted by
Most recently taken up by
- ong6/skillstheir own version, first seen Nov 5, 2026
- RHSTheSecond/skillsmiththeir own version, first seen Nov 1, 2026
- marcosmodly/skillsmiththeir own version, first seen Oct 20, 2026
- rikilamadrid/lorekeepertheir own version, first seen Oct 13, 2026
- rikilamadrid/pathfindertheir own version, first seen Sep 30, 2026
- daronthedragon/skillsmiththeir own version, first seen Aug 19, 2026
Other versions6 projects use a version of this.
Word for word · 0
None found.
Edited · 0
None found.
Wrote their own version · 6
- daronthedragon/skillsmith★ 2same name
- rikilamadrid/lorekeeper★ 1same name
- rikilamadrid/pathfinder★ 1same name
- marcosmodly/skillsmith★ 0same name
- ong6/skills★ 0same name
- RHSTheSecond/skillsmith★ 0same name
How matches are found. Word for word: the exact same text. Edited: shares passages with this file (“99% same” means 99% of its five-word phrases also appear here; 10% or more counts). Their own version: similar meaning, or, weakest, the same name. We can’t tell which project had it first. Projects are counted among the 200 most-starred candidates, and mentions are links to the repository we found, up to 50 per site, so both counts are a floor.
The file
We split this skill into the rules it gives an agent
7 rules. 0 are common, 4 are distinctive, and 3 are very specific to this project.
0
Common
Most of the 6 edited versions we read keep these.
4
Distinctive
This author's own choices. Worth a look.
3
Very specific
Tied to their project's names, files or tools. Probably skip.
- Common
- Distinctive
- Very specific
- Very specific: line 12
Read references/style.md before either branch — it is the standard every question, derivation, and audit below measures against.
- Distinctive: line 60
Done when: all three rounds are resolved or the user says proceed.
- Very specific: line 72
Write the full draft, then prune it against style.md:
- Distinctive: line 74
Run the no-op test on every sentence: would the agent behave this way anyway?
- Distinctive: line 78
Done when: every remaining sentence changes agent behaviour, and every step ends on a checkable completion criterion.
- Very specific: line 90
Read the target skill in full — SKILL.md and every file it points to — plus references/audit-rubric.md.
- Distinctive: line 102
Done when: every rubric row is marked clear or flagged — the audit accounts for the whole rubric, it doesn't stop at "found some issues."
“Common” is measured: kept by at least 6 in 10 of the 6 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.
Files
Skillsmith
Forge skills the way Matt Pocock does: grill first, write second. A skill is forged from decisions the user makes, not prose the agent improvises — the interview is the anvil, the draft is what comes off it.
Read references/style.md before either branch — it is the standard every question, derivation, and audit below measures against.
Branch selector
- The argument is a path to an existing
SKILL.md, or names a skill that exists on disk → Audit branch. - The argument describes something new (or is empty) → Forge branch.
- Genuinely unclear which → ask, one line.
Forge branch — create a new skill
Step 1 — Look up the facts
Facts are looked up; only decisions are asked. Before any question, gather from the environment:
- The target repo's skill conventions: where skills live, frontmatter shape,
references/layout. Read one or two existing skills as exemplars. - Name collisions: existing skills whose name or triggers overlap the idea.
- Prior art: an existing skill that already covers part of the idea (reuse beats rewrite).
Done when: you can state the target directory, the frontmatter fields the repo uses, and any collision — without asking the user any of it.
Step 2 — Grill (3 rounds, hard cap)
Interview the user in rounds. Each round asks every question whose prerequisites are settled, all at once, numbered, each with your recommended answer. Wait for the answers before the next round. A question that depends on another question still open belongs to a later round. Adaptive follow-ups join the next round; after round 3, stop.
Format each question as:
❓ **Q1** - **<question title>**: <question body, including the choices>
➡️ <your recommended answer>Round 1
- Purpose + leading word — what the skill does in one sentence, and the single pretrained concept that anchors it (forge, triage, fog of war). Propose a candidate.
- Invocation — model-invoked (agent can fire it; description costs context load every turn) or user-invoked (zero context load; the user's memory pays cognitive load). Recommend user-invoked unless the agent or another skill must reach it autonomously.
Round 2 (depends on the purpose)
- Branches — the genuinely distinct ways the skill gets used. Each branch earns a trigger and shapes disclosure.
- Content shape + completion criteria — steps, reference, or a mix; and for each step, what checkable condition means done. Push for exhaustive criteria ("every X accounted for"), never vibes ("looks good").
Round 3
- Wildcard — whatever the answers above left genuinely unresolved, plus follow-ups from rounds 1 and 2. If the skill teaches a human, spend this round on the ZPD set in
style.md§7 (mission, fluency vs storage, retrieval/spacing).
Done when: all three rounds are resolved or the user says proceed. Decisions the user declined to make fall to your recommendations — say so in the draft review.
Step 3 — Derive
Settle the remaining design yourself, from the answers:
- Disclosure — inline in
SKILL.mdwhat every branch needs; push behind areferences/pointer what only some branches reach. - Description — model-invoked: front-load the leading word, one trigger per branch, zero synonym padding. User-invoked: one human-facing line.
- Difficulty calibration — reference sections frictionless (glossary, co-location, leading words); steps demanding (completion criteria that force legwork).
Step 4 — Draft + self-prune
Write the full draft, then prune it against style.md:
- Run the no-op test on every sentence: would the agent behave this way anyway? Delete the sentence, keep no residue.
- Reframe every prohibition as the positive behaviour; keep a bare "don't" only as a hard guardrail with an "instead" beside it.
- Hunt leading-word collapses: any triad or restated quality becomes one pretrained word.
Done when: every remaining sentence changes agent behaviour, and every step ends on a checkable completion criterion.
Step 5 — Draft review
Present the complete draft plus one line of rationale per derived decision (disclosure placement, description, calibration). The user corrects here — edits, not another interview. Write the files only on their confirmation, following the conventions found in Step 1.
Audit branch — improve an existing skill
Step 1 — Read
Read the target skill in full — SKILL.md and every file it points to — plus references/audit-rubric.md.
Done when: SKILL.md and every file it points to have been read, plus the rubric.
Step 2 — Audit
Walk every rubric row against the skill. Report findings ranked most-damaging first:
[failure mode] path:line — what's wrong → proposed fixDone when: every rubric row is marked clear or flagged — the audit accounts for the whole rubric, it doesn't stop at "found some issues."
Step 3 — Pick + grill
The user picks which findings to fix. Grill only where a fix is a genuine decision (which leading word, whether to split a skill) — usually 0–2 questions, asked together in one round in the Step 2 format, recommended answer each.
Step 4 — Apply
Apply the picked fixes and show a summary of what changed per finding.
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.

