platxa-skill-generator
Autonomous skill creator for Claude Code CLI. Use when the user asks to "create a skill", "generate a skill", or "build a new slash command". Uses multi-phase orchestrated workflow with Task tool subagents to research domains, design architecture, generate content, validate quality, and iteratively improve via eval infrastructure. Creates production-ready skills following the Agent Skills open standard and Claude Code extensions.
What this skill does
# Platxa Skill Generator
Create Claude Code skills autonomously using a multi-phase orchestrated workflow.
## Overview
This skill guides you through creating production-ready Claude Code skills by:
1. **Discovering** domain knowledge through web research and existing skill analysis
2. **Architecting** the skill structure based on type (Builder/Guide/Automation/Analyzer/Validator)
3. **Generating** SKILL.md content, scripts, and reference documentation
4. **Validating** against Anthropic's Agent Skills spec with quality scoring
The workflow uses Task tool subagents for each phase, ensuring deep expertise at every step.
## Workflow
### Phase 1: Initialize
```
User: /skill-generator
```
Ask the user for:
- Skill description (what should the skill do?)
- Target users (who will use this skill?)
### Phase 2: Discovery (Automatic)
Use Task tool with `subagent_type="Explore"` to:
1. Search web for domain best practices
2. Fetch relevant documentation
3. Analyze existing skills in `~/.claude/skills/` for patterns
4. Identify procedural knowledge (HOW) vs domain expertise (WHAT)
5. Determine what varies by project vs what's constant
**Sufficiency Check**: Evaluate if research is complete. Only ask user for clarification if gaps exist.
### Phase 3: Architecture
Based on discovery, determine:
- **Skill Type**: Builder, Guide, Automation, Analyzer, or Validator
- **Structure**: Which directories needed (scripts/, references/, assets/)
- **Token Budget**: SKILL.md < 500 lines, metadata ~100 tokens
Generate architecture blueprint JSON:
```json
{
"skill_type": "Builder",
"directories": ["scripts", "references"],
"skill_md_sections": ["Overview", "Workflow", "Examples", "Output Checklist"],
"scripts": [{"name": "validate.sh", "purpose": "Validate output"}],
"references": [{"name": "best-practices.md", "purpose": "Domain expertise"}]
}
```
### Phase 4: Generation
Create all skill files:
1. **SKILL.md** with valid YAML frontmatter
2. **scripts/** with executable helpers
3. **references/** with domain documentation
Use templates from `references/templates/` based on skill type.
### Phase 5: Validation
Run quality checks:
- [ ] SKILL.md exists with valid frontmatter
- [ ] Name is hyphen-case, ≤64 characters
- [ ] Description is ≤1024 characters
- [ ] Token budget within limits
- [ ] Scripts are executable and secure
- [ ] References provide real domain expertise
- [ ] Quality score ≥7.0/10 (`python3 scripts/score-skill.py <dir> --json`)
**Quality Score**: Run `score-skill.py` for 5-dimension assessment (spec compliance, content depth, example quality, structure, token efficiency). Must be ≥7.0/10 to pass.
**Evaluation Scaffold**: After passing validation, generate 3 eval scenarios (happy-path, edge-case, error-handling) in `evals/evals.json` for testing the skill's real-world behavior.
### Phase 6: Installation
Ask user for installation location:
- **User skill**: `~/.claude/skills/{skill-name}/`
- **Project skill**: `.claude/skills/{skill-name}/`
Copy files and verify installation.
## Examples
### Example 1: Creating a Code Documenter Skill
```
User: /skill-generator
Assistant: What skill would you like to create?
User: A skill that generates documentation for Python code
Assistant: [Runs Discovery subagent to research Python docstring standards...]
Assistant: [Creates architecture for "Automation" type skill...]
Assistant: [Generates py-documenter skill with SKILL.md, scripts/generate-docs.sh]
Assistant: Quality score: 8.2/10. Install to ~/.claude/skills/py-documenter? (y/n)
```
### Example 2: Creating a Security Analyzer Skill
```
User: /skill-generator
Assistant: What skill would you like to create?
User: A skill that scans code for security vulnerabilities
Assistant: [Discovers OWASP Top 10, SAST patterns, CVE databases...]
Assistant: [Creates "Analyzer" type skill with references/owasp-checklist.md]
Assistant: Quality score: 7.8/10. Ready to install.
```
## Output Checklist
When generating a skill, verify:
- [ ] SKILL.md has valid YAML frontmatter
- [ ] Name follows hyphen-case (e.g., `my-skill-name`)
- [ ] Name is ≤64 characters
- [ ] Description is ≤1024 characters
- [ ] `allowed-tools` lists only tools the skill needs
- [ ] Workflow section has clear steps
- [ ] Examples show realistic usage
- [ ] References contain actual domain expertise (not placeholders)
- [ ] Scripts are executable and tested
- [ ] Quality score ≥7.0/10
## Skill Types Reference
| Type | Purpose | Key Sections |
|------|---------|--------------|
| Builder | Create new things | Workflow, Templates, Output Checklist |
| Guide | Teach/explain | Steps, Examples, Best Practices |
| Automation | Automate tasks | Triggers, Scripts, Verification |
| Analyzer | Inspect/audit | Checklist, Metrics, Reports |
| Validator | Verify quality | Rules, Thresholds, Pass/Fail Criteria |Related in Design
contribute
IncludedLocal-only OSS contribution command center. Auto-refreshes the user's in-flight PR and issue state on invoke so conversations start with full context — no need to brief Claude on what's in flight. Helps the user find issues to contribute to on GitHub, builds per-repo dossiers of what each upstream expects (CLA, DCO, branch convention, AI policy, draft-first, review bots, issue templates), runs deterministic gates before any external action so AI-assisted contributions don't reach maintainers as slop. State is markdown-only: candidate files at ~/.contribute-system/candidates/, repo dossiers at ~/.contribute-system/research/, append-only event log at ~/.contribute-system/log.jsonl. No database, no cloud calls. Use when the user asks about their PRs / issues / contributions, wants to find new work to take on, claim an issue, build/refresh a repo's dossier, or draft a Design Issue or PR. Trigger with "/contribute", "what's my PR status", "find a contribution", "claim issue X", "draft a Design Issue for Y", "refresh dossier for Z".
architectural-analysis
IncludedUser-triggered deep architectural analysis of a codebase or scoped subtree across eight modes — information architecture, data flow, integration points, UI surfaces, interaction patterns, data model, control flow, and failure modes. This skill should be used when the user asks to "diagram this codebase," "map the architecture," "show the data flow," "give me an ERD," "trace control flow," "find the integration points," "verify the layout pattern," "audit the UX architecture," or any similar request whose primary deliverable is mermaid diagrams plus cited reports under docs/architecture/. Dispatches haiku/sonnet sub-agents in parallel for per-mode exploration, then verifies every citation mechanically before any node lands in a diagram. Not for one-off prose explanations of code (use code-explanation) or for high-level system design from scratch (use system-design).
mcp
IncludedModel Context Protocol (MCP) server development and tool management. Languages: Python, TypeScript. Capabilities: build MCP servers, integrate external APIs, discover/execute MCP tools, manage multi-server configs, design agent-centric tools. Actions: create, build, integrate, discover, execute, configure MCP servers/tools. Keywords: MCP, Model Context Protocol, MCP server, MCP tool, stdio transport, SSE transport, tool discovery, resource provider, prompt template, external API integration, Gemini CLI MCP, Claude MCP, agent tools, tool execution, server config. Use when: building MCP servers, integrating external APIs as MCP tools, discovering available MCP tools, executing MCP capabilities, configuring multi-server setups, designing tools for AI agents.
react-native-skia
IncludedDesign, build, debug, and optimise high-polish animated graphics in React Native or Expo using @shopify/react-native-skia, Reanimated, and Gesture Handler. Use when the user wants canvas-driven UI, shaders, paths, rich text, image filters, sprite fields, Skottie, video frames, snapshots, web CanvasKit setup, or performance tuning for custom motion-heavy elements such as loaders, hero art, cards, charts, progress indicators, particle systems, or gesture-driven surfaces. Also use when the user asks for fluid, glow, glass, blob, parallax, 60fps/120fps, or GPU-friendly animated effects in React Native, even if they do not explicitly say "Skia". Do not use for ordinary form/layout work with standard views.
plaid
IncludedProduct Led AI Development — guides founders from idea to launched product. Six capabilities: Idea (discover a product idea), Validate (pressure-test the idea against fatal flaws, problem reality, competition, and 2-week MVP feasibility), Plan (vision intake + document generation), Design (translate image references into a design.md spec), Launch (go-to-market strategy), and Build (roadmap execution). Use when someone says "PLAID", "plaid idea", "help me find an idea", "product idea", "idea from my business", "idea from my expertise", "plaid validate", "validate my idea", "pressure-test", "is this idea good", "find fatal flaws", "validate the problem", "plan a product", "define my vision", "generate a PRD", "product strategy", "plaid design", "design from image", "translate image to design", "create design.md", "extract design tokens", "plaid launch", "go-to-market", "launch plan", "GTM strategy", "launch playbook", "plaid build", "build the app", "start building", or "execute the roadmap".
nextjs-framer-motion-animations
IncludedAdds production-safe Motion for React or Framer Motion animations to Next.js apps, including reveal, hover and tap micro-interactions, whileInView, stagger, AnimatePresence, layout and layoutId transitions, reorder, scroll-linked UI, and lightweight route-content transitions. Use when the user asks to add, refactor, or debug Motion or Framer Motion in App Router or Pages Router codebases, especially around server/client boundaries, reduced motion, LazyMotion, bundle size, hydration, or route transitions. Avoid for GSAP-style timelines, WebGL or 3D scenes, heavy scroll storytelling, or CSS-only effects unless Motion is explicitly requested.