doc-style
Skill8 starsChanged 9 days agoMITView on GitHub
Use when writing, reviewing or auditing a README, skill, specification, project page or launch material that must stay concise and evidence-backed, including "audit docs" and "prune AI self-talk".
2 other projects use a version of this.
Adopted by
Most recently taken up by
- joaoajmatos/zetheir own version, first seen Oct 15, 2026
- mongdang/giroktheir own version, first seen Oct 1, 2026
Other versions2 projects use a version of this.
Word for word · 0
None found.
Edited · 0
None found.
Wrote their own version · 2
- joaoajmatos/ze★ 2same name
- mongdang/girok★ 2same 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.
In this repository17 other files it gives its agents.
- app-controlSkill
- artifactSkill
- clean-systemSkill
- contribution-checklistSkill
- debuggingSkill
- experiment-workflowSkill
- first-principlesSkill
- latex-authoringSkill
- logoSkill
- multi-agentSkill
- product-designSkill
- project-docsSkill
- reference-driven-productSkill
- specSkill
- tddSkill
- test-auditSkill
- word-farsi-docxSkill
The file
We split this skill into the rules it gives an agent
6 rules. About 0 are common, 3 are distinctive, and 3 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.
3
Very specific
Tied to their project's names, files or tools. Probably skip.
- Common
- Distinctive
- Very specific
- Distinctive: line 12
Keep the author's voice. Use facts and short, direct sentences.
- Distinctive: line 15
Put the evidence beside the claim it supports.
- Very specific: line 16
Prefer a pointer (file:line, a link) to a copy.
- Distinctive: line 33
Before you finish, check: the opening states the real product and its maturity.
- Very specific: line 53
run IDs, hashes and verification prose outside reports/ or commit messages.
- Very specific: line 56
Keep current limitations, skipped checks, known risks and useful handoffs.
≈ “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
Documentation style
Part 1 applies to every document. Parts 2 and 3 apply to public READMEs and project pages. A file with a required schema (a SKILL.md, a spec) keeps its schema. Agent docs (AGENTS.md, ES.md) follow project-docs; sentences follow writing-style.
1. Every document
- Keep the author's voice. Use facts and short, direct sentences; no marketing words.
- Claim nothing the repository cannot prove: no feature, result, benchmark, release, user count or stability level without evidence.
- Name the true state: "planned", "under acceptance" or "experimental".
- Put the evidence beside the claim it supports.
- Prefer a pointer (
file:line, a link) to a copy; copies go stale.
2. Public README or project page
The first screen answers four questions: what is it, who is it for, what painful problem does it remove, what proof can the reader inspect now (a demo, screenshot, passing workflow, benchmark, release or command). Do not open with history, philosophy or a feature list.
Sections, in this order:
- Intro: two or three sentences: what it is, who it serves, why it exists. A good hook is a falsifiable claim ("A coding agent should not forget why it is changing your code."), and the next sentence says how the project acts on it.
- Quick start: install (one command), run (one command), expected result. Long walkthroughs go below.
- The problem: the concrete failure in today's workflow, shown as "without this" against "with this".
- How it works: a one-page manual of mechanics and limits; a small diagram if it helps. Deep references go to the project's docs home (GitHub Pages is one option) and are linked by topic.
- Current state: four separate lists: verified, under acceptance, planned, unsupported. Link the source of truth.
- What sets it apart: design choices and tradeoffs checked against the repository and real alternatives. Invent no novelty.
- Evidence: what the tests, workflows and benchmarks cover, and what a passing badge does and does not prove. If there is none, say so and name the smallest useful test.
- Next: near-term work backed by the task tracker only.
Before you finish, check: the opening states the real product and its maturity; Quick start comes before deep detail; every major claim can be verified; the reader knows what to do next; one sentence could serve as the public description.
3. Distribution
Derive every channel from the README; change the opening, never the facts.
- GitHub description: one factual sentence.
- Launch post: problem, result, proof, link.
- Technical post: one design decision, its tradeoff, its evidence.
- Community post: ask for feedback on one open problem; no bare link.
- Demo script: the failure, the project in use, the visible improvement.
4. Audit
To audit docs or prune AI self-talk, search the *.md and *.html files for TODO, not done, AI note and no cost, and group findings by file.
Remove:
- notes the agent left for itself, including notes on abandoned attempts;
- progress logs,
TODOs and status tables for work that is finished, dropped or refactored; - run IDs, hashes and verification prose outside
reports/or commit messages; - price or free-tier claims without a source and a date.
Keep current limitations, skipped checks, known risks and useful handoffs. A review request produces findings; a cleanup request produces the edits, with no second ask. When a plain diff cannot show a visual change, write a side-by-side HTML diff to /tmp.
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.

