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Get Started Free →Create new agent skills with proper structure, progressive disclosure, and bundled resources. Use when user wants to create, write, build, or author a new skill.
.claude/skills/alirezarezvani-write-a-skill/SKILL.md| Test case | Without → With | Effect | Δ tokens | Δ turns |
|---|---|---|---|---|
| case-04 | ✗→✓ | ▲ Improved | 219% | 0% |
| case-05 | ✗→✓ | ▲ Improved | 58% | 0% |
| case-06 | ✗→✓ | ▲ Improved | 50% | 0% |
| case-07 | ✗→✓ | ▲ Improved | 32% | 0% |
| case-09 | ✗→✓ | ▲ Improved | -2% | 0% |
> Derived from Matt Pocock's write-a-skill (MIT). Matt's voice and 3-phase workflow preserved verbatim. Additions: validation tools + references + cs- wrapper (see Tooling + Companions below).
skill-name/
├── SKILL.md # Main instructions (required)
├── REFERENCE.md # Detailed docs (if needed)
├── EXAMPLES.md # Usage examples (if needed)
└── scripts/ # Utility scripts (if needed)
└── helper.jsmd--- name: skill-name description: Brief description of capability. Use when [specific triggers]. --- # Skill Name ## Quick start [Minimal working example] ## Workflows [Step-by-step processes with checklists for complex tasks] ## Advanced features [Link to separate files: See [REFERENCE.md](REFERENCE.md)]
The description is the only thing your agent sees when deciding which skill to load. It's surfaced in the system prompt alongside all other installed skills. Your agent reads these descriptions and picks the relevant skill based on the user's request.
Goal: Give your agent just enough info to know:
Format:
Good example:
Extract text and tables from PDF files, fill forms, merge documents. Use when working with PDF files or when user mentions PDFs, forms, or document extraction.Bad example:
Helps with documents.The bad example gives your agent no way to distinguish this from other document skills.
Add utility scripts when:
Scripts save tokens and improve reliability vs generated code.
Split into separate files when:
After drafting, verify:
Validation tools + cs- wrapper sit alongside this skill. Run all 6 review-checklist items programmatically:
python scripts/skill_review_checklist_runner.py path/to/skill-folderSee references/companion_tooling.md for the tool catalogue, cs-skill-author persona agent, and /cs:write-a-skill slash command.
This skill authors from expertise you already have. When the source is a book, a docs folder, a standard, or a pile of specs, use engineering/book-to-skill instead — it compiles the document into a knowledge-base skill (core frameworks + on-demand chapters + glossary + patterns + cheatsheet) and can package the result as a plugin.
/cs:book-to-skill <path|folder|glob> [skill-name] # compile the source
/cs:book-to-plugin <compiled-skill-dir> # wrap it as a pluginRule of thumb: author first, compile second. A hand-written skill states what you want the agent to do; a compiled book skill is the reference it consults while doing it. If you have both, they are two skills, not one.
Version: 1.0.0 Derived: Matt Pocock (MIT) + this repo's wrapper
| Case | Status | Duration (ms) | Turns | Tokens | Tool calls | ||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Without | With | Δ | Without | With | Δ | Without | With | Δ | Without | With | Δ | ||
case-01 | fail→fail | 9,272 | 5,760 | -38% | 1 | 1 | 0% | 1,422 | 1,905 | +34% | 0 | 0 | — |
case-02 | fail→fail | 18,479 | 6,425 | -65% | 1 | 1 | 0% | 3,027 | 2,017 | -33% | 0 | 0 | — |
case-03 | fail→fail | 17,159 | 7,659 | -55% | 1 | 1 | 0% | 2,691 | 2,215 | -18% | 0 | 0 | — |
case-04 | fail→pass | 3,435 | 3,540 | +3% | 1 | 1 | 0% | 529 | 1,690 | +219% | 0 | 0 | — |
case-05 | fail→pass | 10,140 | 7,668 | -24% | 1 | 1 | 0% | 1,439 | 2,270 | +58% | 0 | 0 | — |
case-06 | fail→pass | 6,768 | 3,226 | -52% | 1 | 1 | 0% | 1,070 | 1,600 | +50% | 0 | 0 | — |
case-07 | fail→pass | 11,941 | 6,993 | -41% | 1 | 1 | 0% | 1,713 | 2,260 | +32% | 0 | 0 | — |
case-08 | pass→pass | 16,318 | 11,596 | -29% | 1 | 1 | 0% | 2,688 | 2,939 | +9% | 0 | 0 | — |
case-09 | fail→pass | 15,916 | 7,306 | -54% | 1 | 1 | 0% | 2,305 | 2,267 | -2% | 0 | 0 | — |
case-10 | pass→pass | 5,420 | 4,971 | -8% | 1 | 1 | 0% | 844 | 1,879 | +123% | 0 | 0 | — |
case-11 | pass→pass | 10,560 | 3,017 | -71% | 1 | 1 | 0% | 1,604 | 1,525 | -5% | 0 | 0 | — |
case-12 | fail→pass | 14,151 | 8,175 | -42% | 1 | 1 | 0% | 2,159 | 2,451 | +14% | 0 | 0 | — |
case-13 | pass→pass | 10,129 | 3,897 | -62% | 1 | 1 | 0% | 1,491 | 1,667 | +12% | 0 | 0 | — |
case-14 | pass→pass | 7,917 | 4,022 | -49% | 1 | 1 | 0% | 1,146 | 1,657 | +45% | 0 | 0 | — |
case-15 | fail→pass | 22,790 | 2,188 | -90% | 1 | 1 | 0% | 3,428 | 1,409 | -59% | 0 | 0 | — |
case-16 | fail→pass | 8,638 | 3,229 | -63% | 1 | 1 | 0% | 1,302 | 1,549 | +19% | 0 | 0 | — |
case-17 | fail→pass | 13,981 | 7,142 | -49% | 1 | 1 | 0% | 2,048 | 2,283 | +11% | 0 | 0 | — |
case-18 | fail→fail | 7,810 | 3,054 | -61% | 1 | 1 | 0% | 1,239 | 1,571 | +27% | 0 | 0 | — |
case-19 | fail→fail | 6,769 | 2,343 | -65% | 1 | 1 | 0% | 1,002 | 1,405 | +40% | 0 | 0 | — |
case-20 | fail→pass | 12,985 | 4,055 | -69% | 1 | 1 | 0% | 2,033 | 1,811 | -11% | 0 | 0 | — |
case-21 | fail→pass | 9,070 | 2,381 | -74% | 1 | 1 | 0% | 1,382 | 1,504 | +9% | 0 | 0 | — |
case-22 | pass→pass | 9,658 | 8,601 | -11% | 1 | 1 | 0% | 1,829 | 2,693 | +47% | 0 | 0 | — |
DecimalAI ran this skill against gemini-3.6-flash twice over the same eval suite — once with the skill loaded and once without — and compared the two runs case by case. 22 cases were attempted. The headline lift of +50 percentage points is the difference between those two pass rates over the 22 comparable cases.
Without the skill loaded, the model failed this case. With it loaded, the same prompt on the same model passed. This is one improved case from the latest verified run; every case, including any that regressed, is in the table above.
| Model | Method | Date | Lift |
|---|---|---|---|
| gemini-3.6-flash | verified | 8/11/2026 | +36% |
Other measured skills in the registry, with their headline benchmark lift.