Meta-Skill Creator
SKILL.md
General Description
This skill is the main orchestrator (Architect) and the user's sole interaction point. Responsible for the entire document-to-skill automation workflow. Progressive disclosure: the agent first reads the description to determine triggering; if relevant, loads the main instructions; calls sub-agents for complex steps.
Workflow Steps
Step 1: Collect Raw Materials
- Create temporary directory
temp-skills/temp-jsonsto store the generatedall-analyses.jsonandmeta-blueprint.json - Based on user-provided documentation directory (e.g., /vercel-ai-sdk/docs), if no relevant directory is found, do not use search tools; first confirm the directory file address with the user.
- If total documentation files exceed 40, stop immediately and reply: "I detected {{actual_count}} files—over the 40-file limit, which dilutes context and hurts SKILL.md quality. Please split into smaller batches (≤15 files each);
- Collect all
.mdoriginal documentation files, usecpto copy totemp-skills/referencesdirectory - For each document in the references directory, call a separate instance of <doc_analyzer_agent> in parallel, but strictly limit each agent to read and analyze only its assigned single file.
- Generate
all-analyses.json(summary JSON including summary, toc, key_apis, etc.) - Use
mvto rename the temporary directorytemp-skills/to:[new-skill-name]/(using the user's final confirmed skill name)
Step 2: Generate Plan (Planning Phase)
- Present
all-analyses.jsonsummary to the user - Based on analysis results, generate multiple skill plan options for user selection:
- Option A: Complete SDK Skill - Large comprehensive skill containing all modules
- Option B: Core Functionality Skill - Streamlined skill focusing on most commonly used APIs
- Option C: Modular Skill Set - Multiple small skills split by functional domain
- For each option provide:
- Skill description and intended use
- Expected file structure
- Main functionality coverage
- Recommended usage scenarios
- User selects an option or requests hybrid customization
Step 3: Design Blueprint (User Collaboration)
- Based on user-selected plan, collect detailed configuration:
- Skill name (final confirmation)
- Skill description (following third-person standard)
- Module planning ("divide core.md into 'core' module")
- Routing logic ("queries containing useChat route to 'ui' module")
- Cross-module patterns ("define a complete 'Core + UI' workflow")
- Progressive disclosure strategy (what content goes into references/)
- Generate
meta-blueprint.json(blueprint JSON) - Users generally won't directly view JSON files, so generate a summary for user confirmation; if user is unsatisfied, prompt for iteration
- Example
meta-blueprint.json:{ "skill_name": "vercel-ai-sdk", "skill_description": "This skill should be used when users need to work with Vercel AI SDK for building AI-powered applications. It provides comprehensive guidance on core APIs, streaming, provider integration, and UI components.", "output_directory": "skills/vercel-ai-sdk/", "modules": { "core": { "source_docs": ["core.md"] }, "ui": { "source_docs": ["ui.md"] } }, "routing_logic": [ { "pattern": "useChat", "route_to": "ui" }, { "pattern": "generateText", "route_to": "core" } ], "progressive_disclosure": { "level1_metadata": true, "level2_skill_md": true, "level3_references": ["api-specs.md", "examples.md"] } }
Step 4: Execute Build
- Call <skill_synthesizer_agent>, passing
meta-blueprint.json,all-analyses.jsonandoriginal_docs - Receive file list (e.g., [{path: 'SKILL.md', content: '...'} etc.])
- Create streamlined skill structure in specified directory:
skills/[skill-name]/ ├── SKILL.md └── references/
Step 5: Deliver Content
- Generate streamlined files in
[skill-name]/directory:- Main SKILL.md file (following progressive disclosure and Anthropic standards)
- Only create
scripts/orassets/directories when needed and with explicit user consent - Validate output (check routing coverage of key_apis, YAML format, etc.)
- Report generation results and usage recommendations to user
Sub-Agent Calls
- Use <doc_analyzer_agent> to analyze individual documents.
- Use <skill_synthesizer_agent> to render final output.
SKILL.md Generation Standards (Progressive Disclosure)
Level 1: Metadata (Always Loaded)
- name: Use kebab-case format (e.g., vercel-ai-sdk)
- description: Third-person description, clearly stating usage scenarios ("This skill should be used when...")
- Core Principles: Be specific and clear, avoid vague descriptions, ensure lightweight context
Level 2: SKILL.md Main Body (Loaded When Skill is Triggered)
- Writing Style: Use imperative mood/infinitive form, avoid second person
- Streamlined Structure:
- Skill overview and core purpose
- Main workflows and key functions
- Resource reference guidelines (clearly specify when to use original documents in references/)
- Common usage patterns (only the most critical ones)
Level 3: On-demand Loading Resources (references/)
- Core Principle: Resource documentation in the final SKILL.md file is located in the working directory's
references/, do not regenerate content, save context - Loading Strategy: Clearly indicate in SKILL.md when to reference original documents
YAML Front Matter Standards
---
name: skill-name-here
description: This skill should be used when [specific scenario]. It provides [key functionality] for [user goal].
---
Skill Content Structure Template
---
name: [skill-name-here]
description: This skill should be used when [specific scenario]. It provides [key functionality] for [user goal].
---
# [Skill Name]
## Core Functionality
[2-3 sentences summarizing the main functionality provided by the skill]
## When to Use
[Reuse content from description, maintain consistency]
## Workflow
1. [First step specific operation]
2. [Second step specific operation]
3. [When to reference original documents in references/]
## Resource References
- For detailed documentation: `references/[original-doc-name].md`
- Guide users to read original documents for detailed information, avoid regenerating content
Language-restricted
- Always think and act step-by-step in English.
- If code, files, or any output is generated, it must be in English (comments, variable names) unless the user specifically asks for another language.
- Do not confirm or mention this language restriction unless the user directly asks about it.
Error Handling and Validation
- Document Processing: If there are too many documents, process in batches
- Blueprint Validation: If blueprint is invalid, iterate design steps
- File Structure Validation: Ensure generated directory structure complies with skill standards
- YAML Validation: Ensure frontmatter format is correct
- Progressive Disclosure Validation: Ensure content layering is reasonable, avoid SKILL.md being too bloated
Output Quality Checklist (Optimized Version)
- Output directory is
[skill-name]/ - SKILL.md contains correct YAML frontmatter
- description uses third person ("This skill should be used when...")
- Original documents have been copied to references/ directory using
cp - Streamlined directory structure (SKILL.md + references/ + temp-jsons/, avoid generating unnecessary other files)
- All resource reference paths point to original documents
- Routing logic covers key APIs
- Skill name uses kebab-case format
- Follow progressive disclosure principles (Level 1: ~100 words, Level 2: <5k words, Level 3: on-demand loading)