wiki-onboarding
Generates four audience-tailored onboarding guides in an onboarding/ folder — Contributor, Staff Engineer, Executive, and Product Manager
Install / Use
npx skills add microsoft/skills --skill wiki-onboardingInstalls into whichever agent you are using.
SKILL.md
Installable skill definition
Quality Score
Category
Content & MediaSupported Platforms
Our assessment of wiki-onboarding
wiki-onboarding scores 91/100 on our quality scale, 309th of 1,160 Content & Media skills we index (top 27%).
Its SKILL.md is 13 KB long, well organised into 20 sections with 1 code example: a thorough specification that gives an agent plenty to work with.
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 8 days ago, so wiki-onboarding 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 2026-10-02. It catches known dangerous patterns, not every risk — read a skill before letting an agent act on it.
wiki-onboarding compared with similar skills
All 4 of these similar skills score higher than wiki-onboarding; compare them before choosing.
| Skill | Score | Stars | Updated | Format |
|---|---|---|---|---|
| wiki-onboarding (this skill)by microsoft | 91 | 3.1k | 8d ago | SKILL.md |
| siyuanby siyuan-note | 100 | 46.6k | today | MCP Server |
| algorithmic-artby anthropics | 100 | 177.9k | 9d ago | SKILL.md |
| pptxby anthropics | 100 | 177.9k | 9d ago | SKILL.md |
| designby nextlevelbuilder | 100 | 130.2k | 11d ago | SKILL.md |
Frequently asked questions
- How do I install wiki-onboarding?
- Run
npx skills add microsoft/skills --skill wiki-onboarding. The install tabs above show the steps for each supported agent. - Which AI agents does wiki-onboarding 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-onboarding 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-onboarding still maintained?
- The repository was last updated 8 days ago, so wiki-onboarding is actively maintained.
Skill content
View source on GitHubname: wiki-onboarding description: Generates four audience-tailored onboarding guides in an onboarding/ folder — Contributor, Staff Engineer, Executive, and Product Manager. Use when the user wants onboarding documentation for a codebase. license: MIT metadata: author: Microsoft version: "1.0.0"
Wiki Onboarding Guide Generator
Generate four audience-tailored onboarding documents in an onboarding/ folder, each giving a different stakeholder exactly the understanding they need.
Source Repository Resolution (MUST DO FIRST)
Before generating any guides, 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
When to Activate
- User asks for onboarding docs or getting-started guides
- User runs
/deep-wiki:onboardcommand - User wants to help new team members understand a codebase
Output Structure
Generate an onboarding/ folder with these files:
onboarding/
├── index.md # Onboarding hub — links to all 4 guides with audience descriptions
├── contributor-guide.md # For new contributors (assumes Python or JS background)
├── staff-engineer-guide.md # For staff/principal engineers
├── executive-guide.md # For VP/director-level engineering leaders
└── product-manager-guide.md # For product managers and non-engineering stakeholders
index.md — Onboarding Hub
A landing page with:
- One-paragraph project summary
- Guide selector table:
| Guide | Audience | What You'll Learn | Time | |-------|----------|-------------------|------| | Contributor Guide | New contributors with Python/JS experience | Setup, first PR, codebase patterns | ~30 min | | Staff Engineer Guide | Staff/principal engineers | Architecture, design decisions, system boundaries | ~45 min | | Executive Guide | VP/directors of engineering | Capabilities, risks, team topology, investment thesis | ~20 min | | Product Manager Guide | Product managers | Features, user journeys, constraints, data model | ~20 min |
Language Detection
Scan the repository for build files to determine the primary language for code examples:
package.json/tsconfig.json→ TypeScript/JavaScript*.csproj/*.sln→ C# / .NETCargo.toml→ Rustpyproject.toml/setup.py/requirements.txt→ Pythongo.mod→ Gopom.xml/build.gradle→ Java
Guide 1: Contributor Guide
File: onboarding/contributor-guide.md
Audience: Engineers joining the project. Assumes proficiency in Python or JavaScript and general software engineering experience.
Length: 1000–2500 lines. Progressive — each section builds on the last.
Required Sections
Part I: Foundations (skip if repo uses Python or JS)
- {Primary Language} for Python/JS Engineers — Syntax comparison tables, async model, collections, type system, package management. Concrete code side-by-side, NOT abstract descriptions.
- {Primary Framework} Essentials — Compare to equivalent Python/JS frameworks (e.g., FastAPI, Express). Request pipeline, routing, DI, config.
Part II: This Codebase
3. What This Project Does — 2-3 sentence elevator pitch
4. Project Structure — Annotated directory tree (what lives where and why). Include graph TB architecture overview.
5. Core Concepts — Domain-specific terminology explained with code examples. Use erDiagram for data model.
6. Request Lifecycle — sequenceDiagram (with autonumber) tracing a typical request end-to-end.
7. Key Patterns — "If you want to add X, follow this pattern" templates with real code
Part III: Getting Productive
8. Prerequisites & Setup — Table: Tool, Version, Install Command. Step-by-step with expected output at each step.
9. Your First Task — End-to-end walkthrough of adding a simple feature
10. Development Workflow — Branch strategy, commit conventions, PR process. Use flowchart diagram.
11. Running Tests — All tests, single file, single test, coverage commands
12. Debugging Guide — Common issues table: Symptom, Cause, Fix
13. Common Pitfalls — Mistakes every new contributor makes and how to avoid them
Appendices
- Glossary (40+ terms)
- Key File Reference — Table: Path, Purpose, Why It Matters, Source
- Quick Reference Card — Cheat sheet of most-used commands and patterns
Rules
- All code examples in the detected primary language
- Every command must be copy-pasteable with expected output
- Minimum 5 Mermaid diagrams (architecture, ER, sequence, flowchart, state)
- Use Mermaid for workflow diagrams (dark-mode colors) — add
<!-- Sources: ... -->comment block after each - Ground all claims in actual code — cite using linked format
Guide 2: Staff Engineer Guide
File: onboarding/staff-engineer-guide.md
Audience: Staff/principal engineers who need the "why" behind every decision. Deep systems experience, may not know this repo's language.
Length: 800–1200 lines. Dense, opinionated, architectural.
Required Sections
- Executive Summary — What the system is in one dense paragraph. What it owns vs delegates.
- The Core Architectural Insight — The SINGLE most important concept. Include pseudocode in a DIFFERENT language from the repo.
- System Architecture — Full Mermaid
graph TBdiagram. Call out the "heart" of the system. - Domain Model — Mermaid
erDiagramof core entities. Data invariants table: Entity, Invariant, Enforced By, Source. - Key Abstractions & Interfaces —
classDiagramshowing load-bearing abstractions. - Request Lifecycle —
sequenceDiagram(withautonumber) showing typical request from entry to response. - State Transitions —
stateDiagram-v2for entities with meaningful lifecycle states. - Decision Log — Table: Decision, Alternatives Considered, Rationale, Source.
- Dependency Rationale — Table: Dependency, Purpose, What It Replaced, Source.
- Data Flow & State — How data moves through the system. Storage comparison table.
- Failure Modes & Error Handling —
flowchartfor error propagation paths. - Performance Characteristics — Bottlenecks, scaling limits, hot paths.
- Security Model — Auth, authorization, trust boundaries, data sensitivity.
- Testing Strategy — What's tested, what isn't, testing philosophy.
- Known Technical Debt — Table: Issue, Risk Level, Affected Files, Source.
- Where to Go Deep — Recommended reading order of source files, links to wiki sections.
Rules
- Use pseudocode in a different language to explain concepts
- Use comparison tables to map unfamiliar concepts (e.g.,
Task<T>=Awaitable[T]) - Dense prose with tables, NOT shallow bullet lists
- Every claim backed by linked citation
- Minimum 5 Mermaid diagrams (architecture, ER, class, sequence, state, flowchart)
- Each diagram followed by
<!-- Sources: ... -->comment block - Use tables aggressively — decisions, dependencies, debt should ALL be tables with Source columns
- Focus on WHY decisions were made, not just WHAT exists
Guide 3: Executive Guide
File: onboarding/executive-guide.md
Audience: VP/director of engineering. Needs capability overview, risk assessment, and investment context — NOT code-level details.
Length: 400–800 lines. Strategic, concise, decision-oriented.
Required Sections
- System Overview — What it does, who uses it, business value in 2-3 sentences
- Capability Map — Table: Capability, Status (Built/Partial/Planned), Maturity, Dependencies. What the system can and cannot do today.
- Architecture at a Glance — High-level Mermaid
graph LRdiagram. Services, data stores, external integrations — NO internal code details. Focus on deployment units and team boundaries. - Team Topology — Which team/person owns which components. Table: Component, Owner, Criticality, Bus Factor.
- Technology Investment Thesis — Why these technologies were chosen. Table: Technology, Purpose, Alternatives Considered, Risk Level.
- Risk Assessment — Table: Risk, Likelihood, Impact, Mitigation, Owner. Cover reliability, security, scalability, compliance.
- Cost & Scaling Model — How costs scale with usage. What the bottlenecks are. When the next scaling investment is needed.
- Dependency Map —
graph TBshowing critical external dependencies. Table: Dependency, Type (Service/Library/Platform), Risk if Unavailable. - Key Metrics & Observability — What's measured, what dashboards exist, alerting coverage. Table: Metric, Current Value, Target, Source.
- Roadmap Alignment — Engineering workstreams mapped to business priorities. What's in progress, what's planned, what's blocked.
- Technical Debt Summary — Top 5 debt items with business impact. Table: Issue, Business Impact, Effort to Fix, Priority.
- Recommendations — 3-5 actionable recommendations for the next quarter, prioritized by impact.
Rules
- NO code snippets — this guide is for engineering leaders, not coders
- Diagrams at service/team level, not class/function level
- Every claim backed by evidence — cite wiki sections, architecture docs, or source files
- Minimum 3 Mermaid diagrams (architecture overview, dependency map, capability/roadmap)
- Tables for every structured finding — this audience reads tables, not prose
- Business language — translate technical concepts into impact (reliability, velocity, cost, risk)
Guide 4: Product Manager Guide
File: onboarding/product-manager-guide.md
Audience: Product managers and non-engineering stakeholders. Needs to understand what the system does, what's possible, and where the boundaries are — NOT how it's built.
Length: 400–800 lines. User-centric, feature-focused, constraint-aware.
Required Sections
- What This System Does — 2-3 sentence elevator pitch in user-facing language (no jargon)
- User Journey Map — Mermaid
graph LRorjourneydiagram showing primary user flows through the system - Feature Capability Map — Table: Feature, Status (Live/Beta/Planned/Not Possible), User-Facing Behavior, Limitations. Comprehensive map of what's built and what's not.
- Data Model (Product View) — Simplified Mermaid
erDiagramshowing entities users interact with. Explain in business terms (e.g., "A Project has many Documents" not "FK relationship"). - Configuration & Feature Flags — Table: Flag/Config, What It Controls, Default, Who Can Change It. What can be toggled without engineering work.
- API Capabilities — What integrations are possible. Table: Capability, Endpoint/Method, Authentication, Rate Limits. Written for integration partners, not developers.
- Performance & SLAs — Response times, throughput limits, availability targets. Table: Operation, Expected Latency, Throughput Limit, Current SLA.
- Known Limitations & Constraints — Honest list of what the system can't do or does poorly. Table: Limitation, User Impact, Workaround, Planned Fix.
- Data & Privacy — What data is collected, where it's stored, retention policies, compliance status. Table: Data Type, Storage Location, Retention, Compliance.
- Glossary — Domain terms explained in plain language (not engineering jargon)
- FAQ — 10+ common questions a PM would ask, answered conc
Truncated for display — read the full file on GitHub.
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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.
