gh-basher83-lunar-claude-plugins-meta-meta-claude/skills/skill-factory/SKILL.md

---
name: skill-factory
description: >
  Research-backed skill creation workflow with automated firecrawl research gathering, multi-tier
  validation, and comprehensive auditing. Use when "create skills with research automation",
  "build research-backed skills", "validate skills end-to-end", "automate skill research and
  creation", needs 8-phase workflow from research through final audit, wants firecrawl-powered
  research combined with validation, or requires quality-assured skill creation following
  Anthropic specifications for Claude Code.
---

# Skill Factory

Comprehensive workflow orchestrator for creating high-quality Claude Code skills with automated research, content
review, and multi-tier validation.

## When to Use This Skill

Use skill-factory when:

- **Creating any new skill** - From initial idea to validated, production-ready skill
- **Research needed** - Automate gathering of documentation, examples, and best practices
- **Quality assurance required** - Ensure skills meet official specifications and best practices
- **Guided workflow preferred** - Step-by-step progression with clear checkpoints
- **Validation needed** - Runtime testing, integration checks, and comprehensive auditing

**Scope:** Creates skills for ANY purpose (not limited to meta-claude plugin):

- Infrastructure skills (terraform-best-practices, ansible-vault-security)
- Development skills (docker-compose-helper, git-workflow-automation)
- Domain-specific skills (brand-guidelines, conventional-git-commits)
- Any skill that extends Claude's capabilities

## Available Operations

The skill-factory provides 8 specialized commands for the create-review-validate lifecycle:

| Command | Purpose | Use When |
|---------|---------|----------|
| `/meta-claude:skill:research` | Gather domain knowledge using firecrawl API | Need automated web scraping for skill research |
| `/meta-claude:skill:format` | Clean and structure research materials | Have raw research needing markdown formatting |
| `/meta-claude:skill:create` | Generate SKILL.md with YAML frontmatter | Ready to create skill structure from research |
| `/meta-claude:skill:review-content` | Validate content quality and clarity | Need content review before compliance check |
| `/meta-claude:skill:review-compliance` | Run quick_validate.py on SKILL.md | Validate YAML frontmatter and naming conventions |
| `/meta-claude:skill:validate-runtime` | Test skill loading in Claude context | Verify skill loads without syntax errors |
| `/meta-claude:skill:validate-integration` | Check for conflicts with existing skills | Ensure no duplicate names or overlaps |
| `/meta-claude:skill:validate-audit` | Invoke claude-skill-auditor agent | Get comprehensive audit against Anthropic specs |

**Power user tip:** Commands work standalone or orchestrated. Use individual commands for targeted fixes,
or invoke the skill for full workflow automation.

**Visual learners:** See [workflows/visual-guide.md](workflows/visual-guide.md) for decision trees, state diagrams,
and workflow visualizations.

## Quick Decision Guide

### Full Workflow vs Individual Commands

**Creating new skill (full workflow):**

- With research → `skill-factory <skill-name> <research-path>`
- Without research → `skill-factory <skill-name>` (includes firecrawl research)
- From knowledge only → `skill-factory <skill-name>` → Select "Skip research"

**Using individual commands (power users):**

| Scenario | Command | Why |
|----------|---------|-----|
| Need web research for skill topic | `/meta-claude:skill:research <name> [sources]` | Automated firecrawl scraping |
| Have messy research files | `/meta-claude:skill:format <research-dir>` | Clean markdown formatting |
| Ready to generate SKILL.md | `/meta-claude:skill:create <name> <research-dir>` | Creates structure with YAML |
| Content unclear or incomplete | `/meta-claude:skill:review-content <skill-path>` | Quality gate before compliance |
| Check frontmatter syntax | `/meta-claude:skill:review-compliance <skill-path>` | Runs quick_validate.py |
| Skill won't load in Claude | `/meta-claude:skill:validate-runtime <skill-path>` | Tests actual loading |
| Worried about name conflicts | `/meta-claude:skill:validate-integration <skill-path>` | Checks existing skills |
| Want Anthropic spec audit | `/meta-claude:skill:validate-audit <skill-path>` | Runs claude-skill-auditor |

**When to use full workflow:** Creating new skills from scratch
**When to use individual commands:** Fixing specific issues, power user iteration

For full workflow details, see Quick Start section below.

## Quick Start

### Path 1: Research Already Gathered

If you have research materials ready:

```bash
# Research exists at docs/research/skills/<skill-name>/
skill-factory <skill-name> docs/research/skills/<skill-name>/
```

The skill will:

1. Format research materials
2. Create skill structure
3. Review content quality
4. Review technical compliance
5. Validate runtime loading
6. Validate integration
7. Run comprehensive audit
8. Present completion options

### Path 2: Research Needed

If starting from scratch:

```bash
# Let skill-factory handle research
skill-factory <skill-name>
```

The skill will ask about research sources and proceed through full workflow.

### Example Usage

```text
User: "Create a skill for CodeRabbit code review best practices"

skill-factory detects no research path provided, asks:

"Have you already gathered research for this skill?
[Yes - I have research at <path>]
[No - Help me gather research]
[Skip - I'll create from knowledge only]"

User: "No - Help me gather research"

skill-factory proceeds through Path 2:
1. Research skill domain
2. Format research materials
3. Create skill structure
... (continues through all phases)
```

## When This Skill Is Invoked

**Your role:** You are the skill-factory orchestrator. Your task is to guide the user through creating
a high-quality, validated skill using 8 primitive slash commands.

### Step 1: Entry Point Detection

Analyze the user's prompt to determine which workflow path to use:

**If research path is explicitly provided:**

```text
User: "skill-factory coderabbit docs/research/skills/coderabbit/"
→ Use Path 1 (skip research phase)
```

**If no research path is provided:**

Ask the user using AskUserQuestion:

```text
"Have you already gathered research for this skill?"

Options:
[Yes - I have research at a specific location]
[No - Help me gather research]
[Skip - I'll create from knowledge only]
```

**Based on user response:**

- **Yes** → Ask for research path, use Path 1
- **No** → Use Path 2 (include research phase)
- **Skip** → Use Path 1 without research (create from existing knowledge)

### Step 2: Initialize TodoWrite

Create a TodoWrite list based on the selected path:

**Path 2 (Full Workflow with Research):**

```javascript
TodoWrite([
  {"content": "Research skill domain", "status": "pending", "activeForm": "Researching skill domain"},
  {"content": "Format research materials", "status": "pending", "activeForm": "Formatting research materials"},
  {"content": "Create skill structure", "status": "pending", "activeForm": "Creating skill structure"},
  {"content": "Review content quality", "status": "pending", "activeForm": "Reviewing content quality"},
  {"content": "Review technical compliance", "status": "pending", "activeForm": "Reviewing technical compliance"},
  {"content": "Validate runtime loading", "status": "pending", "activeForm": "Validating runtime loading"},
  {"content": "Validate integration", "status": "pending", "activeForm": "Validating integration"},
  {"content": "Run comprehensive audit", "status": "pending", "activeForm": "Running comprehensive audit"},
  {"content": "Complete workflow", "status": "pending", "activeForm": "Completing workflow"}
])
```

**Path 1 (Research Exists or Skipped):**

Omit the first "Research skill domain" task. Start with "Format research materials" or
"Create skill structure" depending on whether research exists.

### Step 3: Execute Workflow Sequentially

For each phase in the workflow, follow this pattern:

#### 1. Mark phase as in_progress

Update the corresponding TodoWrite item to `in_progress` status.

#### 2. Check dependencies

Before running a command, verify prior phases completed:

- Review-compliance requires review-content to pass
- Validate-runtime requires review-compliance to pass
- Validate-integration requires validate-runtime to pass
- Validate-audit runs regardless (non-blocking feedback)

#### 3. Invoke command using SlashCommand tool

```text
/meta-claude:skill:research <skill-name> [sources]
/meta-claude:skill:format <research-dir>
/meta-claude:skill:create <skill-name> <research-dir>
/meta-claude:skill:review-content <skill-path>
/meta-claude:skill:review-compliance <skill-path>
/meta-claude:skill:validate-runtime <skill-path>
/meta-claude:skill:validate-integration <skill-path>
/meta-claude:skill:validate-audit <skill-path>
```

**IMPORTANT:** Wait for each command to complete before proceeding to the next phase.
Do not invoke multiple commands in parallel.

#### 4. Check command result

Each command returns success or failure with specific error details.

#### 5. Apply fix strategy if needed

The workflow uses a three-tier fix strategy:

- **Tier 1 (Simple):** Auto-fix formatting, frontmatter, markdown syntax
- **Tier 2 (Medium):** Guided fixes with user approval
- **Tier 3 (Complex):** Stop and report - requires manual fixes

**One-shot policy:** Each fix applied once, re-run once, then fail fast if still broken.

**For complete tier definitions, issue categorization, examples, and fix workflows:**
See [references/error-handling.md](references/error-handling.md)

#### 6. Mark phase completed

Update TodoWrite item to `completed` status.

#### 7. Continue to next phase

Proceed to the next workflow phase, or exit if fail-fast triggered.

### Step 4: Completion

When all phases pass successfully:

**Present completion summary:**

```text
✅ Skill created and validated successfully!

Location: <skill-output-path>/

Research materials: docs/research/skills/<skill-name>/
```

**Ask about artifact cleanup:**

```text
Keep research materials? [Keep/Remove] (default: Keep)
```

**Present next steps using AskUserQuestion:**

```text
Next steps - choose an option:
[Test the skill now - Try invoking it in a new conversation]
[Create PR - Submit skill to repository]
[Add to plugin.json - Integrate with plugin manifest]
[Done - Exit workflow]
```

**Execute user's choice:**

- **Test** → Guide user to test skill invocation
- **Create PR** → Create git branch, commit, push, open PR
- **Add to plugin.json** → Update manifest, validate structure
- **Done** → Clean exit

### Key Execution Principles

**Sequential Execution:** Do not run commands in parallel. Wait for each phase to complete before proceeding.

**Context Window Protection:** You are orchestrating commands, not sub-agents. Your context window is safe
because you're invoking slash commands sequentially, not spawning multiple agents.

**State Management:** TodoWrite provides real-time progress visibility. Update it at every phase
transition.

**Fail Fast:** When Tier 3 issues occur or user declines fixes, exit immediately with clear guidance.
Don't attempt complex recovery.

**Dependency Enforcement:** Never skip dependency checks. Review phases are sequential, validation
phases are tiered.

**One-shot Fixes:** Apply each fix once, re-run once, then fail if still broken. This prevents infinite loops.

**User Communication:** Report progress clearly. Show which phase is running, what the result was,
and what's happening next.

## Workflow Architecture

Two paths based on research availability: Path 1 (research exists) and Path 2 (research needed).
TodoWrite tracks progress through 7-8 phases. Entry point detection uses prompt analysis and AskUserQuestion.

**Details:** See [references/workflow-architecture.md](references/workflow-architecture.md)

## Workflow Execution

Sequential phase invocation pattern: mark in_progress → check dependencies → invoke command →
check result → apply fixes → mark completed → continue. Dependencies enforced (review sequential,
validation tiered). Commands invoked via SlashCommand tool with wait-for-completion pattern.

**Details:** See [references/workflow-execution.md](references/workflow-execution.md)

## Success Completion

When all phases pass successfully:

```text
✅ Skill created and validated successfully!

Location: <skill-output-path>/

Research materials: docs/research/skills/<skill-name>/
Keep research materials? [Keep/Remove] (default: Keep)
```

**Artifact Cleanup:**

Ask user about research materials:

- **Keep** (default): Preserves research for future iterations, builds knowledge base
- **Remove**: Cleans up workspace, research can be re-gathered if needed

**Next Steps:**

Present options to user:

```text
Next steps - choose an option:
  [1] Test the skill now - Try invoking it in a new conversation
  [2] Create PR - Submit skill to repository
  [3] Add to plugin.json - Integrate with plugin manifest (if applicable)
  [4] Done - Exit workflow

What would you like to do?
```

**User Actions:**

1. **Test the skill now** → Guide user to test skill invocation
2. **Create PR** → Create git branch, commit, push, open PR
3. **Add to plugin.json** → Update manifest, validate structure (for plugin skills)
4. **Done** → Clean exit

Execute the user's choice, then exit cleanly.

## Examples

The skill-factory workflow supports various scenarios:

1. **Path 2 (Full Workflow):** Creating skills from scratch with automated research gathering
2. **Path 1 (Existing Research):** Creating skills when research materials already exist
3. **Guided Fix Workflow:** Applying Tier 2 fixes with user approval
4. **Fail-Fast Pattern:** Handling Tier 3 complex issues with immediate exit

**Detailed Examples:** See [references/workflow-examples.md](references/workflow-examples.md) for complete walkthrough
scenarios showing TodoWrite state transitions, command invocations, error handling, and success paths.

## Design Principles

Six core principles: (1) Primitives First (slash commands foundation), (2) KISS State Management (TodoWrite only),
(3) Fail Fast (no complex recovery), (4) Context-Aware Entry (prompt analysis), (5) Composable & Testable
(standalone or orchestrated), (6) Quality Gates (sequential dependencies).

**Details:** See [references/design-principles.md](references/design-principles.md)

## Implementation Notes

### Delegation Architecture

skill-factory extends the proven skill-creator skill by adding:

- **Pre-creation phases:** Research gathering and formatting
- **Post-creation phases:** Content review and validation
- **Quality gates:** Compliance checking, runtime testing, integration validation

**Delegation to existing tools:**

- **skill-creator skill** → Core creation workflow (Understand → Plan → Initialize → Edit → Package)
- **quick_validate.py** → Compliance validation (frontmatter, naming, structure)
- **claude-skill-auditor agent** → Comprehensive audit

This separation maintains the stability of skill-creator while adding research-backed, validated skill creation
with quality gates.

### Progressive Disclosure

This skill provides:

1. **Quick Start** - Fast path for common use cases
2. **Workflow Architecture** - Understanding the orchestration model
3. **Detailed Phase Documentation** - Deep dive into each phase
4. **Error Handling** - Comprehensive fix strategies
5. **Examples** - Real-world scenarios

Load sections as needed for your use case.

## Troubleshooting

Common issues: research phase failures (check FIRECRAWL_API_KEY), content review loops (Tier 3 issues need
redesign), compliance validation (run quick_validate.py manually), integration conflicts (check duplicate names).

**Details:** See [references/troubleshooting.md](references/troubleshooting.md)

## Success Metrics

You know skill-factory succeeds when:

1. **Time to create skill:** Reduced from hours to minutes
2. **Skill quality:** 100% compliance with official specs on first validation
3. **User satisfaction:** Beginners create high-quality skills without deep knowledge
4. **Maintainability:** Primitives are independently testable and reusable
5. **Workflow clarity:** Users understand current phase and next steps at all times

## Related Resources

- **skill-creator skill** - Core skill creation workflow (delegated by skill-factory)
- **multi-agent-composition skill** - Architectural patterns and composition rules
- **Primitive commands** - Individual slash commands under `/skill-*` namespace
- **quick_validate.py** - Compliance validation script
- **claude-skill-auditor agent** - Comprehensive skill audit agent