| name | skill-generator |
| description | Generates a SKILL.md from documentation URLs, markdown files, or raw text — extracts patterns, rules, examples, and anti-patterns automatically. Trigger: When user wants to create a skill from docs, says "generate skill from", "skill from docs", "convert docs to skill", or provides a URL/file to turn into a skill.
|
| metadata | {"author":"javi-ai","version":"1.0","tags":["skills","generation","documentation","automation"],"category":"workflow"} |
| allowed-tools | Read, Write, Bash, Glob, Grep, WebFetch, WebSearch |
Skill Generator
Create production-ready SKILL.md files from any documentation source.
Purpose
Manually writing skills from documentation is tedious and error-prone. This skill automates extraction of patterns, rules, examples, and anti-patterns from docs into a properly formatted SKILL.md following the Agent Skills spec.
When to Activate
- User provides a documentation URL and wants a skill from it
- User provides a markdown file path to convert into a skill
- User pastes raw text and asks to generate a skill
- User says "generate skill from", "skill from docs", "create skill from URL"
Do NOT activate when:
- User wants to manually write a skill (use
skill-creator instead)
- The source is not documentation (e.g., a code file — analyze differently)
- A skill for the technology already exists (check
own/skills/ first)
Input Modes
| Mode | Input | How to Acquire |
|---|
| URL | https://docs.example.com/guide | Use WebFetch to retrieve content |
| File path | /path/to/docs.md or relative path | Use Read to load content |
| Raw text | Pasted documentation text | Use directly from user message |
Step 0: Validate Input
1. If URL → WebFetch the page. If fetch fails, report error and stop.
2. If file path → Read the file. If not found, report error and stop.
3. If raw text → Use directly.
4. If input exceeds 50,000 chars → summarize sections, don't load everything.
Extraction Pipeline
Step 1: Identify the Technology
From the source content, extract:
| Field | How to Find |
|---|
| Name | Title, H1, package name, library name |
| Version | Version numbers, "v4", "latest", changelog headers |
| Category | Framework, library, tool, platform, API |
| Language | Programming language(s) used |
Step 2: Extract Patterns
Scan the documentation for these pattern types:
| Pattern Type | Signals in Docs | Priority |
|---|
| Critical rules | "MUST", "NEVER", "ALWAYS", "required", "breaking change" | HIGH |
| Best practices | "recommended", "best practice", "prefer", "should" | HIGH |
| Configuration | Config files, env vars, setup steps | MEDIUM |
| API patterns | Function signatures, method chains, hooks | MEDIUM |
| Anti-patterns | "don't", "avoid", "deprecated", "common mistake" | HIGH |
| Migration notes | "changed in", "breaking", "upgrade from", "renamed" | HIGH |
| Code examples | Code blocks, snippets, usage examples | MEDIUM |
Step 3: Classify and Prioritize
1. Group findings by: Critical Rules > Patterns > Examples > Configuration
2. Deduplicate — merge overlapping rules
3. Prioritize by impact:
- Breaking changes / migration traps → top of Critical Rules
- Common mistakes / anti-patterns → immediately after
- Best practices → Core Patterns section
- Code examples → keep only the most illustrative 3-5
4. Discard: installation steps, changelog noise, contributor guides
Step 4: Structure the Output
Apply the format from _conventions/AGENT_SKILLS_SPEC.md:
---
name: {extracted-name}
description: >
{One sentence: what the technology is and what the skill covers}.
Trigger: When {conditions based on technology usage}.
metadata:
author: javi-ai
version: "1.0"
tags: [{technology}, {language}, {category}]
category: {detected category}
---
## Purpose
{What this skill helps the AI do correctly with this technology.}
## When to Activate
- {Condition 1 — e.g., "When writing React components"}
- {Condition 2}
- {Condition 3}
## Critical Rules
1. {Most important rule — e.g., breaking change from previous version}
2. {Second most important rule}
3. {Continue...}
## Core Patterns
### {Pattern Group 1}
{Table or concise explanation}
### {Pattern Group 2}
{Table or concise explanation}
## Anti-Patterns
| Don't | Do Instead | Why |
|-------|-----------|-----|
| {bad pattern} | {good pattern} | {explanation} |
## Code Examples
{Minimal, focused examples — max 5}
## Resources
- **Source**: {URL or file path of the documentation used}
Step 5: Validate Output
Before writing the file, verify:
Step 6: Write and Report
1. Determine skill name from technology (lowercase, hyphens)
2. Check own/skills/{name}/ doesn't already exist
3. Create own/skills/{name}/SKILL.md with generated content
4. Report to user:
- Skill name and path
- Number of rules/patterns extracted
- Any gaps (e.g., "docs had no anti-patterns listed")
- Suggest manual review for accuracy
Multi-Page Documentation
When docs span multiple pages:
1. Start with the main/overview page
2. Follow links to: Getting Started, API Reference, Migration Guide
3. Prioritize: Migration Guide > API Reference > Getting Started > Tutorials
4. Cap at 5 pages maximum — extract patterns, don't read everything
5. If the technology has a "Cheat Sheet" or "Quick Reference" page, prioritize that
Critical Rules
- ALWAYS preserve the source URL/path in the Resources section — provenance matters
- NEVER include installation steps in the skill — those change constantly and belong in docs
- ALWAYS check for existing skills before generating — don't create duplicates
- Prioritize breaking changes and migration traps — those cause the most AI errors
- Keep code examples under 20 lines each — skills are instructions, not tutorials
- ALWAYS suggest manual review — AI extraction is imperfect, human verification catches hallucinated rules
