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...
SKILL.md
Full skill instructions
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
- Scan the repository file tree and README
- Detect project type, languages, frameworks, architectural patterns, key technologies
- Identify layers: presentation, business logic, data access, infrastructure
- 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
- 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:
-
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
-
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.
When to Use
This skill is applicable to execute the workflow or actions described in the overview.
<!-- AGI-INTEGRATION-START -->
AGI Framework Integration
Adapted for @techwavedev/agi-agent-kit Original source: antigravity-awesome-skills
Memory-First Protocol
Retrieve prior documentation structure and content to maintain consistency. Cache generated docs to avoid regenerating unchanged sections.
# Check for prior documentation context before starting
python3 execution/memory_manager.py auto --query "documentation patterns and prior content for Wiki Architect"
Storing Results
After completing work, store documentation decisions for future sessions:
python3 execution/memory_manager.py store \
--content "Documentation: API reference generated from OpenAPI spec, deployment guide updated with new env vars" \
--type technical --project <project> \
--tags wiki-architect documentation
Multi-Agent Collaboration
Share documentation changes with all agents so they reference the latest guides and APIs.
python3 execution/cross_agent_context.py store \
--agent "<your-agent>" \
--action "Documentation updated — API reference, deployment guide, and CHANGELOG all current" \
--project <project>
Agent Team: Documentation
This skill pairs with documentation_team — dispatched automatically after any code change to keep docs in sync.
