Skill builder

Skill Builder

Turn a plain-English description into a production-ready skill compatible with every agent that implements the Agent Skills open standard (32+ tools, December 2025).

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Invocation

/skill-builder "compress images before committing"
/skill-builder "remind the model to always write tests first" --type reference
/skill-builder "scaffold a FastAPI project" --type workflow --repo
/skill-builder "make the model speak formally" --type mode --repo
/skill-builder --audit skills/my-skill/SKILL.md
/skill-builder --audit skills/my-skill/SKILL.md --fix

Arg	Default	Values
description	required (unless --audit)	plain English, what the skill does
--type	auto-detect	workflow, mode, tool, reference, agent
--repo	off	also scaffold a full marketplace-ready repo
--audit	off	path to existing SKILL.md — audit instead of create
--fix	off	with --audit: also output corrected SKILL.md

---

Phase 0 — Route

If --audit flag present: skip to Phase A — Audit.

Otherwise: continue to Phase 1.

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Phase 1 — Classify

Load references/skill-types.md.

Determine skill type from description:

Signal	Type
"every time", "always", "mode", "persistently"	mode
"create", "scaffold", "build", "pipeline", "generate"	workflow
"compress", "format", "convert", "run X on Y", "transform"	tool
"remind", "context for", "know about", "rules for"	reference
"act as", "autonomous", "manage the whole", "firm", "company"	agent

If --type provided, skip detection. If ambiguous, ask ONE question:

"Is this (a) a persistent mode that changes every response, (b) a one-shot action on a specific target, or (c) a multi-step workflow producing artifacts?"

Wait for answer. Never ask more than one question total. Decide the rest.

---

Phase 2 — Gather Requirements

Load references/skill-anatomy.md.

Ask at most 2 more questions total (across all phases). If description already answers, skip:

1. Trigger: does the user type /skill-name to invoke, or should it activate automatically?
2. Output: what does it produce — files on disk, changed model behavior, a report, or nothing?

Derive:

• SKILL_NAME — kebab-case, matches ^[a-z0-9]+(-[a-z0-9]+)*$, 1–64 chars
• TRIGGER — user-invocable (typed) or auto (always-on, requires SessionStart hook)
• OUTPUTS — files / behavior change / report / none
• NEEDS_HOOKS — true if mode or auto-trigger
• NEEDS_REFERENCES — true if skill needs domain knowledge loaded lazily
• NEEDS_SCRIPTS — true if skill runs bash/python tools

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Phase 3 — Domain Research (if NEEDS_REFERENCES)

Before writing any reference files, research the domain to get verified facts. Skip this phase if NEEDS_REFERENCES is false.

Step 1 — Identify research targets. From description, extract tool/library names, APIs, frameworks, flags, method signatures, config schemas.

Step 2 — WebSearch official docs. For each target:

WebSearch: "{tool-name} official documentation CLI flags"
WebSearch: "{api-name} API reference {relevant-endpoint}"

Prioritize: official docs > spec documents > recent release notes.

Step 3 — Extract and verify. Only keep: exact flag names + values, method signatures, error codes, version constraints. Never include unverified Stack Overflow answers.

Step 4 — Build reference stubs. One file per domain: references/{domain-slug}.md with verified flags/methods, error→fix table, input/output examples, TOC if >100 lines.

---

Phase 4 — Generate SKILL.md

Frontmatter

---
name: {SKILL_NAME}
description: >
  {LINE_1_WHAT_IT_DOES_VERB_OBJECT_MAX_80_CHARS}
  {LINE_2_HOW_INVOKED}
  {LINE_3_KEY_OUTPUT_OR_BEHAVIOR}
license: MIT
user-invocable: {true_OR_false}
argument-hint: '{ARGUMENT_HINT}'
when_to_use: >
  {WHEN_TO_USE}
---

Add optional fields only when relevant: model, effort, context, paths, allowed-tools, metadata. See references/skill-anatomy.md for full field reference.

Body structure by skill type

Load references/skill-types.md for full patterns:

• workflow: Invocation → Phase 0…N → Report → Token Efficiency → Open-Weight Rules
• mode: Activation → Persistence → Rules → Intensity → Auto-Clarity → Boundaries
• tool: Trigger → Process (numbered) → Output → Error Handling
• reference: Purpose → When to Apply → {Domains} → Never Do
• agent: Prime Directive → Mode Detection → Phases → Prohibited → Success Criteria

Quality rules

• First sentence: action-oriented ("Produce X"), not "This skill..."
• Every section actionable — no vague guidance
• Code templates for any generated code
• Error tables for external tool calls
• Reference loads at the phase that needs them (lazy)
• All {TEMPLATE_VARIABLES} substituted — never leave placeholders
• Keep SKILL.md under 5000 tokens

---

Phase 5 — Generate References (if NEEDS_REFERENCES)

For each domain area identified in Phase 3:

1. Name: references/{domain-slug}.md
2. Structure: TOC → headings → tables → code blocks, minimal prose
3. Error→fix tables for external tools
4. Input/output example pairs
5. Add load instruction in SKILL.md: Load references/{name}.md before {action}.

Rules: verified facts only, tables over prose, one-level-deep (no chained includes), TOC if >100 lines.

---

Phase 6 — Generate Hooks (if NEEDS_HOOKS)

Load references/hook-templates.md for full templates.

Mode skills only. Generate: hooks/package.json, hooks/activate.js, hooks/tracker.js. Use safeWriteFlag pattern verbatim. ALL filesystem ops must silent-fail.

---

Phase 7 — Scaffold Repo (if --repo)

Load references/scaffold-templates.md, references/agent-rules.md, and references/install-paths.md.

Generate full repo in {SKILL_NAME}/ directory. See references/scaffold-templates.md for complete file list and content templates.

---

Phase 8 — Report

## Skill Built: {SKILL_NAME}

**Type**: {SKILL_TYPE}
**Hooks**: {yes — SessionStart + UserPromptSubmit | no}
**References**: {list filenames or "none"}
**Repo scaffold**: {yes — {SKILL_NAME}/ | no}

### Files created
{list every file path}

### Install
bash install.sh

### Test
/{SKILL_NAME} {example invocation}

---

Phase A — Audit (only when --audit flag present)

Load references/skill-anatomy.md.

Step 1 — Read target. Read SKILL.md at --audit path. If missing, stop and tell user.

Step 2 — Extract metadata. Parse frontmatter: name, description, license, type (infer from body). Estimate token count.

Step 3 — Run quality checklist. Check every item in references/skill-anatomy.md Quality Checklist. Record each failure:

[FAIL] {checklist-item}
  Found:    {what's there}
  Expected: {what should be}
  Fix:      {exact change}

Also check: body matches required sections for type, no raw {VARIABLE} placeholders, SKILL.md under 5000 tokens, reference files have TOC if >100 lines, domain facts verified not guessed.

Step 4 — Report. Output: type detected, size (ok or OVER BUDGET), failures list, warnings list, passed count.

Step 5 — If --fix. Output corrected SKILL.md — fix failures only, don't rewrite passing sections. Run Phase 3 first if domain research needed.

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Token Efficiency Rules

• Ask 3 questions max total (Phase 1 + Phase 2)
• Load skill-types.md once at Phase 1, keep active
• Load hook-templates.md only at Phase 6
• Load scaffold-templates.md, agent-rules.md, install-paths.md only at Phase 7
• Run Phase 3 domain research only if NEEDS_REFERENCES
• Generate all files in one pass — no file-by-file back-and-forth

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Open-Weight Model Rules

• Substitute ALL {TEMPLATE_VARIABLES} — never output raw placeholders
• Every generated SKILL.md self-contained — no dangling @ includes in skill body
• JSON: valid, no comments, no trailing commas
• YAML: valid, correct indentation, quote special chars
• Hook JS: use safeWriteFlag pattern verbatim
• name must match ^[a-z0-9]+(-[a-z0-9]+)*$ — validate before writing
• description must be ≤1024 chars — count before writing