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4d 1h ago
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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...

.agents/skills/wiki-architect Python
PY
TY
JA
4+ layers Tracked stack
Capabilities
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Related
3
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Capabilities
Actionable behaviors documented in the skill body.
0
Phases
Operational steps available for guided execution.
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References
Support files available for deeper usage and onboarding.
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Scripts
Runnable or reusable automation artifacts discovered locally.

Architectural Overview

Skill Reading

"This module is grounded in ai engineering patterns and exposes 1 core capabilities across 1 execution phases."

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.

When to Use

This skill is applicable to execute the workflow or actions described in the overview.

Primary Stack

Python

Tooling Surface

Guide only

Workspace Path

.agents/skills/wiki-architect

Operational Ecosystem

The complete hardware and software toolchain required.

This skill is mostly documentation-driven and does not expose extra scripts, references, examples, or templates.

Module Topology

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Antigravity Core

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A high-performance agentic architecture developed by Deepmind for autonomous coding tasks.
120 Installs
4.2 Reliability
1 Workspace Files
4.2
Workspace Reliability Avg
5
68%
4
22%
3
10%
2
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1
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No explicit validation signals were parsed for this skill yet, but the module remains available for inspection and chat launch.

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