wiki-architect
Analyzes code repositories and generates hierarchical documentation structures with onboarding guides
Install / Use
npx skills add microsoft/skills --skill wiki-architectInstalls into whichever agent you are using.
SKILL.md
Installable skill definition
Quality Score
Category
Content & MediaSupported Platforms
Our assessment of wiki-architect
wiki-architect scores 80/100 on our quality scale, 690th of 923 Content & Media skills we index.
Its SKILL.md is 3.9 KB long, well organised into 8 sections and no code examples: a solid amount of guidance for an agent.
With 3,051 GitHub stars, it is one of the more widely adopted skills in the catalogue.
Maintenance, license and trust
- The repository was last updated 6 days ago, so wiki-architect is actively maintained.
- It is released under the MIT license, a permissive license that allows use, modification and commercial use with attribution.
- Its trust signals score 100/100, with no cautions. These come from repository metadata, not a code audit — read the skill file before letting an agent act on it.
Safety scan
No issues foundOur scan of the whole file found no instruction hijacking, hidden characters, credential access, data exfiltration or destructive commands.
Automated pattern scan on 2026-09-30. It catches known dangerous patterns, not every risk — read a skill before letting an agent act on it.
wiki-architect compared with similar skills
All 4 of these similar skills score higher than wiki-architect; compare them before choosing.
| Skill | Score | Stars | Updated | Format |
|---|---|---|---|---|
| wiki-architect (this skill)by microsoft | 80 | 3.1k | 6d ago | SKILL.md |
| siyuanby siyuan-note | 100 | 46.6k | today | MCP Server |
| algorithmic-artby anthropics | 100 | 177.9k | 7d ago | SKILL.md |
| pptxby anthropics | 100 | 177.9k | 7d ago | SKILL.md |
| designby nextlevelbuilder | 100 | 130.2k | 8d ago | SKILL.md |
Frequently asked questions
- How do I install wiki-architect?
- Run
npx skills add microsoft/skills --skill wiki-architect. The install tabs above show the steps for each supported agent. - Which AI agents does wiki-architect work with?
- It is written for Universal, as a SKILL.md file. Other agents that read the same format can often use it too.
- Is wiki-architect safe to use?
- Our scan of the whole file found no instruction hijacking, hidden characters, credential access, data exfiltration or destructive commands. It is MIT-licensed and scores 100/100 on trust signals. Skills are instructions an agent will follow, so read the file before installing it and do not approve commands you do not understand.
- Is wiki-architect still maintained?
- The repository was last updated 6 days ago, so wiki-architect is actively maintained.
Skill content
View source on GitHubname: wiki-architect 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 understand a project's architecture at a high level. license: MIT metadata: author: Microsoft version: "1.0.0"
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
Source Repository Resolution (MUST DO FIRST)
Before any analysis, you MUST determine the source repository context:
- Check for git remote: Run
git remote get-url originto detect if a remote exists - Ask the user: "Is this a local-only repository, or do you have a source repository URL (e.g., GitHub, Azure DevOps)?"
- Remote URL provided → store as
REPO_URL, use linked citations:[file:line](REPO_URL/blob/BRANCH/file#Lline) - Local-only → use local citations:
(file_path:line_number)
- Remote URL provided → store as
- Determine default branch: Run
git rev-parse --abbrev-ref HEAD - Do NOT proceed until source repo context is resolved
Procedure
- Resolve source repo (see above — MUST be first)
- 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: Contributor Guide, Staff Engineer Guide, Executive Guide, Product Manager Guide (in
onboarding/folder) - Getting Started: overview, setup, usage, quick reference
- Deep Dive: architecture → subsystems → components → methods
- Onboarding: Contributor Guide, Staff Engineer Guide, Executive Guide, Product Manager Guide (in
- Cite real files in every section prompt using linked or local citation format
Onboarding Guide Architecture
The catalogue MUST include an Onboarding section (always first, uncollapsed) containing:
-
Contributor Guide — For new contributors (assumes Python/JS). 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
-
Staff Engineer Guide — For staff/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, decision log, dependency rationale, "where to go deep" reading order
-
Executive Guide — For VP/director-level leaders. NO code snippets. Includes:
- Capability map, risk assessment, technology investment thesis
- Cost/scaling model, dependency map, actionable recommendations
-
Product Manager Guide — For PMs. ZERO engineering jargon. Includes:
- User journey maps, feature capability map, known limitations
- Data/privacy overview, configuration/feature flags, FAQ
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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Languages
Trust signals
From repository metadata: license, adoption, age and documentation. Not a code audit — see the Safety scan above for what the skill file itself contains.
