Writing Skills

Writing Skills

Build a skill a zero-context mid-level engineer or Sonnet-class model can load and execute correctly on the first try. Discoverable metadata, lean body, deterministic scripts. Ground truth only: verify every path/command against disk before writing it — a wrong runbook is worse than none.

Before you scaffold

Write a skill when the same instructions get pasted into chat repeatedly, or a CLAUDE.md section has grown into a procedure rather than a fact — a skill's body loads only when triggered, so it costs nothing until used. Don't write one for a single unrepeated task, or to store a fact with no procedure attached (that's a references/ note inside an existing skill, or CLAUDE.md itself, not a new skill).

Variables — instantiate before writing

Loading model — earn every token

Bulk lives in Level 3; SKILL.md is its table of contents. Full model + surface differences: references/architecture.md.

Procedure

- [ ] 1. <name>+<desc> pass validate_metadata.py
- [ ] 2. <dir>/<folders> scaffolded, name==dir
- [ ] 3. body written: imperative, <ref_depth>-deep refs, <<body_max> lines
- [ ] 4. every fragile step → a scripts/ CLI (args in, stdout/stderr out)
- [ ] 5. every references/checklist.md item passes

1 · Metadata — the highest-leverage field. <desc> is how a model picks this skill from 100+. State what it does, the concrete trigger phrases a user would say, and the negative trigger + which sibling to use instead. Gate it: python3 scripts/validate_metadata.py --name "<name>" --description "<desc>" --dir "<dir>" → SUCCESS proceeds; any NAME/DESC/STYLE/DIR/DISCOVERY line → fix that field only, re-run. Discovery patterns + worked examples: references/best-practices.md §Discovery. Restricting tools? add allowed-tools: (e.g. Read, Write, Bash(git status:*)).

2 · Scaffold. <dir>/{<folders>}, each one level deep. No README/INSTALLATION/CHANGELOG inside a skill — those are the tell of a human doc masquerading as one.

3 · Body. Start from assets/SKILL.template.md. Third-person imperative. Pick <freedom> per step: low → exact command + "do not modify"; medium → parameterized script; high → goal only, trust the model. Over <body_max> lines, or carrying a large schema? Move it to references/ and command the read at point of need ("Read references/api.md to pick the endpoint"), never deeper than <ref_depth> — a nested reference gets head-previewed and half-read. Picking a workflow shape (sequential steps, MCP-tool coordination, iterative refinement, decision-tree tool selection, embedded domain expertise): references/patterns.md.

4 · Scripts. One fragile task (regex, parsing, multi-step, safety-critical) per CLI. Takes args. Solves, never punts — handle the error in the script, don't fail to Claude. No magic constants. Specific stdout on success, specific stderr on failure so the agent self-corrects. State intent in the body: "Run x.py" (execute) vs "See x.py for the algorithm" (read).

5 · Audit. Every item in references/checklist.md. Quality-critical skill? Evaluation-first: run the task with no skill, capture the exact failure, then write only enough to close it — never pad docs against imagined needs. Three-tier test framework (triggering / functional / performance-comparison) and the under/over-triggering fix table: references/evaluation.md.

Claude Code frontmatter/runtime beyond the basics (context: fork, dynamic !command injection, string substitutions, skill stacking, nested/monorepo discovery, skillOverrides): references/claude-code-extensions.md.

When NOT to use

Not for README/user docs, library code, or MCP-server code. For a domain runbook, don't start from scratch — copy the closest sibling skill's shape.

Bootstrapping a whole library

Different job from the rest of this skill: an existing project has no skill library yet, and the ask is the whole set (10+ skills), not one. Discover-then-parallel-author-then-adversarial-review workflow: references/bootstrap-library.md.

Provenance and maintenance

Re-verify when the environment drifts:

• discovery roots: ls -d ~/.claude/skills <project>/.claude/skills 2>/dev/null
• validator still green on this skill: python3 scripts/validate_metadata.py --file SKILL.md --dir "$(pwd)"
• rule sources, distilled into references/ (never cited live from the gitignored staging dir they arrived in) — re-distill if these change, and re-check the live doc first since Anthropic's guides are versioned and this is a point-in-time snapshot:
  • references/best-practices.md, references/architecture.md, references/checklist.md, the "Before you scaffold" heuristic above: Anthropic's Agent Skills overview + authoring best practices, and the agentskills.io skill-creator spec, absorbed as of 2026-07-09.
  • references/claude-code-extensions.md: Anthropic's Extend Claude with skills doc, absorbed 2026-07-10.
  • references/evaluation.md: the testing chapter of a third-party PDF skill-authoring guide (unknown author/license — ideas only, no text retained verbatim) plus Anthropic's evaluation-driven-development section, absorbed 2026-07-10.
  • references/bootstrap-library.md: a one-shot "bootstrap a whole skill library" mega-prompt found alongside the PDF (unknown author/license — same idea-only treatment), absorbed 2026-07-10.
  • references/patterns.md: the "Patterns and troubleshooting" chapter of the same third-party PDF (idea-only, same treatment), absorbed 2026-07-10.
• This distillation is a snapshot, not a live mirror. For anything not covered here, or to confirm a rule still holds, read the source directly rather than assuming this file caught everything: Agent Skills overview · authoring best practices · Extend Claude with skills · agentskills.io.