skill-writing

skill-writing

When to use

Use this skill when:

• Creating a new skill from scratch
• Improving an existing skill
• Reviewing skill quality
• Deciding what belongs in a skill vs a rule

Typical examples:

• "Create a skill for X"
• "This skill needs improvement"
• "Should this be a skill or a rule?"

Do not use this skill when:

• Writing rules (rules are constraints, not workflows)
• Writing commands (commands are direct invocations)

Goal

• Create executable skills, not documentation
• Ensure every skill answers: When? How? What output?
• Prevent common mistakes: too broad, too generic, missing validation

Preconditions

• Clear understanding of the intended task
• Distinction: rules = always apply, skills = triggered workflows
• Access to a skill template or existing reference skill

Decision matrix: What goes where?

Before creating anything, classify the content:

The critical test

Ask: "Does the model need this to do its job correctly?"

• If the model already knows it → Nothing
• If the model knows it but does it wrong in THIS project → Rule or Guideline
• If the model needs a multi-step workflow to get it right → Skill

Skills and commands share the .claude/skills/ namespace

Skills in .agent-src.uncondensed/skills/{name}/SKILL.md AND commands in .agent-src.uncondensed/commands/{name}.md both project into .claude/skills/ (see scripts/condense.ts → generate_claude_skills + generate_claude_commands). Claude treats the whole directory as native skills.

Implications for skill authors:

• If a same-name command already exists, the skill takes priority and the command is skipped (generate_claude_commands honors this). Don't reuse a command's slug for a skill unless the command should retire.
• Both artifacts compete on description for routing. A weak skill description is shadowed by a stronger same-domain command — and vice versa. Make trigger phrasing precise (§ 1b below).
• When the workflow has both a "user types /foo" path AND a "model picks this up from intent" path, author the skill first and let the command delegate (skills: frontmatter). Two artifacts with the same trigger surface fight each other in the router.

When "Nothing" is the right answer

Do NOT create a skill or rule for:

• Standard tool usage (jq, grep, docker exec, git commands)
• Framework basics the model already knows
• Single-command operations without decision logic
• Knowledge that belongs in a skill's procedure as a step, not as its own skill

Size and structure hints

→ See docs/guidelines/agent-infra/size-and-scope.md for full limits.

• Target: 300–900 words. Review for split above 1200 words. Strongly consider split above 1500 words.
• If multiple workflows exist → split into multiple skills
• If two skills overlap heavily → merge
• If a skill becomes "read the guideline" → it lost its purpose, restore the workflow

Procedure

0. Inspect, then run the Drafting Protocol

Before writing, inspect the landscape: grep .agent-src.uncondensed/skills/ and rules/ for duplicates or near-matches, and analyze 1–2 gold-standard peers (e.g. pest-testing, php-coder) to anchor shape and tone. If requirements are unclear or incomplete, stop and ask — do not assume.

Then run the Understand → Research → Draft sequence from the artifact-drafting-protocol rule. Skip only on explicit "just do it" bypass or trivial edits (typo, link, single-line clarification).

0b. Skill-growth gate (new skill only)

The skill count keeps climbing; nothing forces "should this be a new skill at all?". Before creating a new skill, answer these in the PR body — a new skill that cannot answer them is a merge / guideline / no-op in disguise:

1. Family — which capability family does it join? (engineering, product, …)
2. Capability — what does it do that no existing skill does? Name the gap.
3. Why not extend / merge — which nearest skill did you consider folding into, and why is a separate skill better?
4. Why not a guideline — is this executable workflow (skill) or reference material (guideline)? Guideline-shaped content does not become a skill.
5. Visibility tier — core or lab? Which pack?

Surface overlap before deciding — run ./scripts-run src/scripts/skill_overlap (or audit_skill_overlap) and read the nearest matches; a high-overlap hit is a merge signal, not a green light. This gate is the authoring-time companion to the capability-boundary matrix: the matrix governs packs, this governs the skills inside them.

1. Define the trigger

Write "When to use" first. This is the in-body trigger — it documents the workflow's entry conditions for anyone reading the skill.

Good: Use when creating Laravel middleware for request filtering

Bad: Use when working with Laravel

1b. Write a pushy frontmatter description

The description: field is what Claude reads at routing time. Polite or generic descriptions cause undertriggering. Normative source: skill-quality rule § Description Triggering.

Three rules: name 2+ triggers (domains, symptoms, user phrasing), end with ... even if they don't explicitly ask for \`., and stay **≤ 200 characters** (skill_linter.tswarnsdescription_too_longabove that). When trimming to fit, drop adjectives or the second example phrasing before you drop a trigger class or theeven if ...` tail.

Canonical before/after (2026-04-21 audit baseline):

# Bad (138 chars, polite, single trigger class):
description: "Use when writing Playwright E2E tests — browser automation,
  visual regression testing, Page Objects, fixtures, and reliable test
  patterns."

# Good (pushy, second trigger class, explicit tail):
description: "Use when writing Playwright E2E tests — locators, assertions,
  Page Objects, fixtures, CI, and flaky test prevention — even if the user
  doesn't say Playwright."

The good version routes correctly on "my E2E keeps flaking on CI" without naming Playwright. Run ./scripts-run src/scripts/audit_skill_descriptions after writing; if flagged too-short or no-trigger-prefix, rewrite before commit.

When iterating on phrasing with the user (e.g. "make this pushier", "will this ever fire"), delegate to the description-assist skill — it runs the approval-gated propose / pick loop with at most two rounds.

1c. Propose a trigger-eval stub (new skills only)

When creating a new skill, propose a stub .agent-src.uncondensed/skills/{name}/evals/triggers.json before writing the body. Draw the queries from Phase A of the drafting protocol (the user's "should trigger" and "must not trigger" answers).

Stub shape — 5 should-trigger + 5 should-not-trigger queries, first-person, single-sentence, no leakage of the skill name in the queries:

{
  "skill": "{name}",
  "description": "5 should-trigger + 5 should-not-trigger queries. No query mentions '{name}' directly. Near-misses share domain vocabulary without being the actual task.",
  "queries": [
    {"q": "<phrasing from user Phase A that MUST route here>", "trigger": true},
    {"q": "<another should-trigger phrasing>", "trigger": true},
    {"q": "<...3 more>", "trigger": true},
    {"q": "<near-miss sharing vocabulary but different task>", "trigger": false},
    {"q": "<another near-miss>", "trigger": false},
    {"q": "<...3 more>", "trigger": false}
  ]
}

Present the stub as a numbered-options prompt (per user-interaction):

> 1. Accept stub as drafted — commit alongside the skill
> 2. Edit queries before commit
> 3. Skip evals for now — create later

Nothing is committed without the user's pick. If the user picks skip, record it in the commit message (Eval stub: deferred). Peer examples for the expected format: php-coder/evals/triggers.json, eloquent/evals/triggers.json, skill-writing/evals/triggers.json.

Presence is CI-enforced for new skills: check_trigger_eval_presence fails any skill outside the shrink-only grandfather allowlist that lacks evals/triggers.json — skip therefore defers the queries' quality, never the file itself.

Rules / commands / guidelines do not get eval stubs — only skills route through the top-level catalogue.

2. Write the procedure

Use numbered, verifiable steps.

Good:

1. Check if middleware exists
2. Create with artisan command
3. Implement logic
4. Register in route or kernel

Bad:

1. Create middleware
2. Add logic

3. Add validation

End with concrete validation.

Good:

• Route returns expected status
• Appears in route list
• No static analysis errors

Bad:

• Vague statements like "see if outcome is correct" (no concrete command or assertion)

4. Add safe/unsafe example

Show minimal contrast.

Good:

• Typed middleware, correctly registered

Bad:

• Business logic inside middleware

5. Define output format

Control response structure.

Example:

1. Code snippet
2. Registration location
3. Gotcha (if relevant)

6. Validate against quality checklist

• K1: Description is a trigger ("Use when...")
• K2: Not over-defined
• K3: No obvious content
• K4: Contains gotchas
• K5: Has Output format (numbered, 2-4 deliverables)
• K6: Not pointer-only (executable without opening guidelines)
• K7: Created with analysis (not blind, expected behavior defined)
• Size: Within limits (see size-and-scope guideline)

7. Run + iterate evals (quantitative loop)

Triggers (evals/triggers.json) check routing. A separate evals/evals.json checks behavior — does the skill make the agent produce a better answer than baseline? Add this layer for any skill where the procedure has measurable output (commands, artifacts, structured text). Skip for evergreen heuristics with no falsifiable output (e.g. direct-answers, language-and-tone) unless the user asks for it.

Workspace layout (all under .gitignore):

.agent-src.uncondensed/skills/{name}/evals/
  triggers.json              # tracked — routing eval (§ 1c)
  evals.json                 # tracked — behavior eval definitions
  runs/                      # gitignored — per-iteration outputs
    {timestamp}-baseline/    # sub-agent run without the skill
    {timestamp}-with-skill/  # sub-agent run with the skill
    {timestamp}-benchmark.json

evals.json shape — 3–10 scenarios, each with prompt + grading rubric:

{
  "skill": "{name}",
  "scenarios": [
    {
      "id": "happy-path",
      "prompt": "<full user-shaped task that exercises the skill>",
      "assertions": [
        {"kind": "contains", "value": "<expected substring in output>"},
        {"kind": "file_exists", "path": "<artifact path the skill should create>"},
        {"kind": "rubric", "criterion": "<one-line judgement, e.g. 'output includes a numbered procedure'>"}
      ]
    }
  ]
}

contains / file_exists grade deterministically. rubric items grade via a fresh sub-agent reading the output against the criterion — keep each criterion to one falsifiable sentence.

Loop (orchestrated by scripts/run_skill_evals.ts):

1. Scaffold — ./scripts-run src/scripts/run_skill_evals scaffold {skill} creates runs/{timestamp}-{baseline,with-skill}/ and seeds each scenario's meta.json.
2. Baseline run — spawn one sub-agent per scenario without the skill loaded. Capture stdout + any artifacts into runs/{timestamp}-baseline/{scenario-id}/.
3. With-skill run — same scenarios, same sub-agent harness, with the skill loaded. Capture into runs/{timestamp}-with-skill/{scenario-id}/.
4. Grade — for each scenario, write a grade.json file with per-assertion pass/fail. Deterministic assertions auto-grade; rubric assertions need a grader sub-agent.
5. Aggregate — ./scripts-run src/scripts/run_skill_evals aggregate {skill} --run {timestamp} produces runs/{timestamp}-benchmark.json with pass-rate, timing, token deltas baseline-vs-with-skill.
6. Report — ./scripts-run src/scripts/run_skill_evals report {skill} --run {timestamp} prints the diff. Iterate on the skill body until with-skill outperforms baseline on every scenario.

The script ships with sub-agent spawning stubbed — the orchestration layer is per-environment (Claude Code, Augment, council). Implement the spawn function once for your environment, the rest of the loop (aggregate / report / scaffold) works out of the box.

Exit criterion — every scenario passes with-skill, at least one fails baseline (proves the skill earns its slot). Commit the evals.json alongside the skill; never commit runs/.

Neighbors:

• description-assist — iterate on the trigger phrasing
• skill-reviewer — structural 7-Killers audit
• lint-skills — static checks (frontmatter, sections, size)
• skill-improvement-pipeline — production-learning capture

Output format

1. Complete SKILL.md file
2. No explanations outside the file
3. Fully copyable
4. No empty sections

Core rules

• Skills are executable thinking processes
• Always include: When to use, Procedure, Output format, Gotchas, Do NOT
• Steps must be verifiable
• Validation must be concrete
• One skill = one job

Cross-references and paths

• Body links to guidelines / contracts use the verbatim relative form (../../docs/guidelines/<group>/<name>.md, ../../docs/contracts/<name>.md). The condense-time rewriter resolves them to depth-aware single-up form — do not pre-rewrite in source.
• Skills do not declare load_context: / load_context_eager:; those frontmatter keys are rule-only. If a skill needs to point at a context, link to it inline ([context-name](../../contexts/<area>/<file>.md)).
• Never write .agent-src.uncondensed/ in any skill body link or example — it ships into .augment/skills/ and breaks consumer resolution. See rule-writing § 3b for the canonical reference.

Execution metadata (optional)

Skills may declare an execution frontmatter block (type, handler, timeout_seconds, safety_mode, allowed_tools). Default is manual (instructional only). See docs/guidelines/agent-infra/runtime-layer.md for the full specification and assisted / automated semantics.

When to create a project-analysis-* skill

Only if the framework has its own lifecycle producing unique debugging patterns that project-analysis-core cannot explain (e.g. Laravel, Symfony, Express, React, Next.js). Not for Tailwind, CSS frameworks, utility libs, or simple state managers.

Gotchas

• Writing documentation instead of executable steps
• Skipping validation — every Procedure MUST end with a concrete verify step
• Including baseline knowledge the model already has
• Description too long or not a trigger
• Renaming a heading to "Procedure:" without numbered steps or ### sub-headings
• Always run ./scripts-run src/scripts/skill_linter before saving — 0 FAIL required

Frugality Standards

Apply the Frugality Charter to every skill you author.

Examples in this artifact:

• Per the charter's default-terse rule, the SKILL.md ## Procedure opens with the action ("Run the linter"), not "Let me walk you through…".
• Per the cheap-question check, only emit numbered-options output when consequences differ — never as a stylistic choice.
• Per the post-action summary suppression, the example output ships the artifact, not a wrapping ## Status / ## Summary block.

Pre-save self-check:

1. Does any procedure step open with "Let me", "Now I will", "Found it", "OK", or "Alright"?
2. Does the skill prescribe numbered-options output without a real consequence trade-off?
3. Does the example output include a post-action summary block?
4. Does the description carry filler ("comprehensive", "advanced", "powerful")?

Read-only-by-default scripts

A script shipped inside a skill (scripts/**) is side-effect-free by default — it inspects, computes, and prints; it does not mutate the filesystem. Any mutation (writing a file, deleting, rename/copy) must be gated behind an explicit flag named in this SKILL.md — --writable / --apply / --write / --output / --fix — so the default invocation is safe to run blind. A generator whose declared purpose is to write (it emits an artifact to a caller-supplied path) is allowlisted with a rationale in src/scripts/lint_skill_scripts_readonly_allowlist.json rather than carrying a redundant flag. lint_skill_scripts_readonly enforces this: an ungated, non-allowlisted write fails the build.

Description-optimizer loop (U1 — held-out, not vibes)

Descriptions are the trigger surface; tune them like a model, not like prose:

1. Draft 2-3 candidate descriptions for the skill.
2. Ensure evals/triggers.json has should- AND should-not-trigger queries (grow beyond the 5+5 stub when optimizing — more queries = a real test split).
3. Run the helper: npx tsx src/scripts/optimize_skill_description.ts --skill <id> --candidate "…" [--candidate "…"] [--live] — it splits the queries deterministically into train/held-out, scores every candidate (deterministic token-overlap proxy by default; --live = haiku judge, ~$0.001 per query·candidate), and picks the best held-out accuracy.
4. Adopt the pick ONLY if it beats the current description on the held-out split — a train-only win is overfitting to the queries you wrote.

Self-QA loop for output-producing skills (optional pattern)

For skills whose product is a rendered/structural artifact (decks, docs, diagrams, dashboards, generated UI): assume there are problems and have a fresh-eyes pass find them before handing back. The author-context is blind to its own omissions; a context-free verifier is not.

1. Produce the artifact.
2. Dispatch a fresh subagent (no authoring context) with ONLY the artifact + the acceptance criteria: "list every visual/structural defect; assume at least one exists."
3. Fix what it finds; re-run once. Two clean passes → done.

Worked example (deck skill): the author renders 12 slides; the fresh-eyes pass gets the PDF + "check overflow, contrast, orphaned bullets, broken images" — it flags a clipped title on slide 7 the author never re-read. One fix, one re-check, done.

Scope: complements verify-before-complete (which gates the completion claim); this pattern is HOW to get the fresh evidence for artifacts where no deterministic checker exists. Skip it when a real validator covers the surface (linter, schema, test) — deterministic checks beat judge passes.

Known-pitfalls section (optional pattern, tool skills)

Tool/integration skills teach the happy path; the recurring support burden is the silent failures — the ones that cost money, corrupt state, or fail with no error. For a high-support-burden tool skill, add a ## Known pitfalls section in this micro-format:

1. A Symptom → Root cause → Fix table. Each row starts from the observable symptom (what the user sees), not the internal cause — the user greps for the symptom, not the fix.

   Symptom	Root cause	Fix
   <what the user observes>	<why it happens>	<the concrete action>

2. Optionally, a quick-reference anti-pattern checklist (Anti-pattern · cost/impact · fix difficulty) for traps worth scanning before shipping — add it only when it does not restate the skill's existing ## Gotcha / ## Do NOT; the table is the load-bearing part.

Sourcing floor — real, not invented: every entry names a genuinely common failure (a high-vote community question, a documented incident class), never a hypothetical. ≤ 5 entries per skill. The value is a short, sourced, high-signal list; a long one is noise. A pitfall is a section on the existing tool skill, never a new skill per pitfall and never a generated grid (see size-enforcement § Per-tool pitfall content).

Do NOT

• Write documentation-style, pointer-only, or too-broad skills ("Laravel skill", "Django skill")
• Skip Procedure or use vague validation
• Exceed size limits (see docs/guidelines/agent-infra/size-and-scope.md)
• Duplicate rules
• Ship a skill script that mutates the filesystem on its default invocation — gate it behind a flag or allowlist it with a rationale

Encode usage policy in the description

Workflow sequencing, preconditions, ID/output provenance ("copy ids verbatim, never from memory"), a mandatory "why" intent field, and turn-end contracts belong INSIDE this artifact's description/frontmatter — where they fire at the decision point — not in always-on prose. See tool-description-as-policy.