wiki-architect
Analyzes code repositories and generates hierarchical documentation structures with onboarding guides. Use when the user wants to create a wiki, generate documentation, map a codebase structure, or understand a project's architecture at a high level.
Best use case
wiki-architect is best used when you need a repeatable AI agent workflow instead of a one-off prompt.
Analyzes code repositories and generates hierarchical documentation structures with onboarding guides. Use when the user wants to create a wiki, generate documentation, map a codebase structure, or understand a project's architecture at a high level.
Teams using wiki-architect should expect a more consistent output, faster repeated execution, less prompt rewriting.
When to use this skill
- You want a reusable workflow that can be run more than once with consistent structure.
When not to use this skill
- You only need a quick one-off answer and do not need a reusable workflow.
- You cannot install or maintain the underlying files, dependencies, or repository context.
Installation
Claude Code / Cursor / Codex
Manual Installation
- Download SKILL.md from GitHub
- Place it in
.claude/skills/wiki-architect/SKILL.mdinside your project - Restart your AI agent — it will auto-discover the skill
How wiki-architect Compares
| Feature / Agent | wiki-architect | Standard Approach |
|---|---|---|
| Platform Support | Not specified | Limited / Varies |
| Context Awareness | High | Baseline |
| Installation Complexity | Unknown | N/A |
Frequently Asked Questions
What does this skill do?
Analyzes code repositories and generates hierarchical documentation structures with onboarding guides. Use when the user wants to create a wiki, generate documentation, map a codebase structure, or understand a project's architecture at a high level.
Where can I find the source code?
You can find the source code on GitHub using the link provided at the top of the page.
SKILL.md Source
# Wiki Architect You are a documentation architect that produces structured wiki catalogues and onboarding guides from codebases. ## When to Activate - User asks to "create a wiki", "document this repo", "generate docs" - User wants to understand project structure or architecture - User asks for a table of contents or documentation plan - User asks for an onboarding guide or "zero to hero" path ## Procedure 1. **Scan** the repository file tree and README 2. **Detect** project type, languages, frameworks, architectural patterns, key technologies 3. **Identify** layers: presentation, business logic, data access, infrastructure 4. **Generate** a hierarchical JSON catalogue with: - **Onboarding**: Principal-Level Guide, Zero to Hero Guide - **Getting Started**: overview, setup, usage, quick reference - **Deep Dive**: architecture → subsystems → components → methods 5. **Cite** real files in every section prompt using `file_path:line_number` ## Onboarding Guide Architecture The catalogue MUST include an Onboarding section (always first, uncollapsed) containing: 1. **Principal-Level Guide** — For senior/principal ICs. Dense, opinionated. Includes: - The ONE core architectural insight with pseudocode in a different language - System architecture Mermaid diagram, domain model ER diagram - Design tradeoffs, strategic direction, "where to go deep" reading order 2. **Zero-to-Hero Learning Path** — For newcomers. Progressive depth: - Part I: Language/framework/technology foundations with cross-language comparisons - Part II: This codebase's architecture and domain model - Part III: Dev setup, testing, codebase navigation, contributing - Appendices: 40+ term glossary, key file reference ## Language Detection Detect primary language from file extensions and build files, then select a comparison language: - C#/Java/Go/TypeScript → Python as comparison - Python → JavaScript as comparison - Rust → C++ or Go as comparison ## Constraints - Max nesting depth: 4 levels - Max 8 children per section - Small repos (≤10 files): Getting Started only (skip Deep Dive, still include onboarding) - Every prompt must reference specific files - Derive all titles from actual repository content — never use generic placeholders ## Output JSON code block following the catalogue schema with `items[].children[]` structure, where each node has `title`, `name`, `prompt`, and `children` fields.
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