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- .woodpecker.yaml: secret names RS_HARBOR_USER / RS_HARBOR_PASS (global)
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66 lines
2.8 KiB
Markdown
66 lines
2.8 KiB
Markdown
---
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name: wiki-architect
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description: "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..."
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risk: unknown
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source: community
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date_added: "2026-02-27"
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---
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# Wiki Architect
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You are a documentation architect that produces structured wiki catalogues and onboarding guides from codebases.
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## When to Activate
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- User asks to "create a wiki", "document this repo", "generate docs"
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- User wants to understand project structure or architecture
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- User asks for a table of contents or documentation plan
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- User asks for an onboarding guide or "zero to hero" path
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## Procedure
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1. **Scan** the repository file tree and README
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2. **Detect** project type, languages, frameworks, architectural patterns, key technologies
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3. **Identify** layers: presentation, business logic, data access, infrastructure
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4. **Generate** a hierarchical JSON catalogue with:
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- **Onboarding**: Principal-Level Guide, Zero to Hero Guide
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- **Getting Started**: overview, setup, usage, quick reference
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- **Deep Dive**: architecture → subsystems → components → methods
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5. **Cite** real files in every section prompt using `file_path:line_number`
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## Onboarding Guide Architecture
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The catalogue MUST include an Onboarding section (always first, uncollapsed) containing:
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1. **Principal-Level Guide** — For senior/principal ICs. Dense, opinionated. Includes:
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- The ONE core architectural insight with pseudocode in a different language
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- System architecture Mermaid diagram, domain model ER diagram
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- Design tradeoffs, strategic direction, "where to go deep" reading order
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2. **Zero-to-Hero Learning Path** — For newcomers. Progressive depth:
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- Part I: Language/framework/technology foundations with cross-language comparisons
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- Part II: This codebase's architecture and domain model
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- Part III: Dev setup, testing, codebase navigation, contributing
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- Appendices: 40+ term glossary, key file reference
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## Language Detection
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Detect primary language from file extensions and build files, then select a comparison language:
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- C#/Java/Go/TypeScript → Python as comparison
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- Python → JavaScript as comparison
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- Rust → C++ or Go as comparison
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## Constraints
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- Max nesting depth: 4 levels
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- Max 8 children per section
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- Small repos (≤10 files): Getting Started only (skip Deep Dive, still include onboarding)
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- Every prompt must reference specific files
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- Derive all titles from actual repository content — never use generic placeholders
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## Output
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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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## When to Use
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This skill is applicable to execute the workflow or actions described in the overview.
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