evolving-skill-creator: создание и автоматизация скиллов

--- name: evolving-skill-creator description: Guide for creating evolving skills - detailed workflow plans that capture what you'll do, what tools you'll create, and learnings from execution. Use this when starting a new task that could benefit from a reusable workflow. --- # Evolving Skill Creator Create **evolving skills** - detailed workflow plans that become reusable through iteration. ## What is an Evolving Skill? An evolving skill is a workflow plan that: 1. Documents specific steps to accomplish a goal 2. Lists Python scripts you'll create as reusable tools 3. Captures learnings after execution for future improvement Unlike static skills, evolving skills are refined through use. ## Directory Structure ``` tasks/evolving_skill/ ├── SKILL.md # Your workflow plan └── scripts/ # Python tools you create during execution ├── scrape_data.py └── generate_output.py ``` ## SKILL.md Format **IMPORTANT: YAML Frontmatter is Required** Every evolving skill MUST start with YAML frontmatter containing `name` and `description`. These fields are critical for skill discovery - they determine how the skill is identified when loaded in future sessions. ```yaml --- name: descriptive-skill-name # REQUIRED - used for identification description: Clear explanation of what this workflow does and when to use it # REQUIRED - used for discovery --- # Task Name ## Overview Brief description of the problem this skill solves. ## Workflow Detailed numbered steps: 1. First step - be specific 2. Second step - include commands/tools to use 3. ... ## Tools to Create Python scripts you'll write. Document BEFORE writing them: ### scripts/example_tool.py - **Purpose**: What it does - **Inputs**: What it takes (args, files, etc.) - **Outputs**: What it produces - **Dependencies**: Required packages ## Tools to Use (Discover what's available, list ones you'll use) - servers/name: MCP server tools - custom_tools/name: Python tool implementations ## Skills - skill_name: how it will help ## Packages - package_name (pip install package_name) ## Expected Outputs - Files this workflow produces - Formats and locations ## Learnings (Add after execution) ### What Worked Well - ... ### What Didn't Work - ... ### Tips for Future Use - ... ``` ## Tools to Create Section This is the key differentiator. When your workflow involves writing Python scripts, document them upfront: ```markdown ## Tools to Create ### scripts/fetch_artist_data.py - **Purpose**: Crawl Wikipedia and extract artist biographical data - **Inputs**: artist_name (str), output_path (str) - **Outputs**: JSON file with structured bio data - **Dependencies**: crawl4ai, json ### scripts/build_site.py - **Purpose**: Generate static HTML from artist data - **Inputs**: data_path (str), theme (str), output_dir (str) - **Outputs**: Complete website in output_dir/ - **Dependencies**: jinja2 ``` After execution, the actual scripts live in `scripts/` and can be reused. ## Creating an Evolving Skill 1. **Create directory**: `mkdir -p tasks/evolving_skill` 2. **Write SKILL.md** with proper YAML frontmatter first: - `name`: Use a descriptive, reusable name (e.g., `artist-website-builder`, not `bob-dylan-site`) - `description`: Explain what the workflow does and when to use it 3. **Execute workflow** following your plan 4. **Create scripts** as documented in Tools to Create 5. **Update SKILL.md** with Learnings after completion ### Naming Guidelines Choose names that describe the **type of task**, not the specific instance: - **Good**: `artist-website-builder`, `data-scraper-to-static-site`, `pdf-report-generator` - **Bad**: `bob-dylan-project`, `session-12345`, `my-task` The name should make it clear what the skill does when discovered in future sessions. ## Updating After Execution After completing your work: 1. **Refine Workflow** - Update steps based on what actually worked 2. **Move scripts** - Ensure working scripts are in `scripts/` 3. **Add Learnings** - Document what worked, what didn't, tips ## Example: Complete Evolving Skill ```yaml --- name: artist-website-builder description: Build static biographical websites for artists by scraping public sources and generating themed HTML. --- # Artist Website Builder ## Overview Create professional artist websites by gathering biographical data and generating themed static HTML. ## Workflow 1. Research artist - gather name variations, active years 2. Scrape data using scripts/fetch_artist_data.py 3. Review and clean extracted data 4. Generate site using scripts/build_site.py with "minimalist-dark" theme 5. Review in browser, check mobile responsiveness 6. Iterate on styling if needed ## Tools to Create ### scripts/fetch_artist_data.py - **Purpose**: Crawl Wikipedia and extract artist biographical data - **Inputs**: artist_name (str) - **Outputs**: artist_data.json - **Dependencies**: crawl4ai ### scripts/build_site.py - **Purpose**: Generate static HTML from artist data - **Inputs**: artist_data.json, theme_name - **Outputs**: Complete website in output/ - **Dependencies**: jinja2 ## Tools to Use - servers/context7: fetching crawl4ai and jinja2 documentation - servers/browser: capturing site previews for review - custom_tools/image_optimizer: compressing generated assets ## Skills - web-scraping-patterns: structuring the crawl4ai approach ## Packages - crawl4ai (pip install crawl4ai) - jinja2 (pip install jinja2) ## Expected Outputs - output/index.html - output/discography.html - output/assets/ ## Learnings ### What Worked Well - Wikipedia infoboxes have consistent structure - crawl4ai async mode is 3x faster than sync - "minimalist-dark" theme works best for musicians ### What Didn't Work - AllMusic requires JS rendering - use Discogs API instead - Initial theme had poor mobile layout ### Tips for Future Use - Always check robots.txt before scraping - Cache scraped data - re-running is slow - Test on mobile early ``` ## Key Principles 1. **Be specific** - Workflow steps should be actionable, not vague 2. **Document tools upfront** - Plan scripts before writing them 3. **Test like a user** - Verify artifacts through interaction, not just observation (click buttons, play games, navigate pages, run with edge cases, etc) 4. **Update with learnings** - The skill improves through use 5. **Keep scripts reusable** - Design tools to work in similar future tasks