.github/plugins/deep-wiki/skills/wiki-onboarding/SKILL.md
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.
npx skillsauth add microsoft/skills wiki-onboardingInstall this skill globally with one command. Works with Claude Code, Cursor, and Windsurf.
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Generate four audience-tailored onboarding documents in an onboarding/ folder, each giving a different stakeholder exactly the understanding they need.
Before generating any guides, you MUST determine the source repository context:
git remote get-url origin to detect if a remote existsREPO_URL, use linked citations: [file:line](REPO_URL/blob/BRANCH/file#Lline)(file_path:line_number)git rev-parse --abbrev-ref HEAD/deep-wiki:onboard commandGenerate 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 HubA landing page with:
| 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 |
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 → JavaFile: 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.
Part I: Foundations (skip if repo uses Python or JS)
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
<!-- Sources: ... --> comment block after eachFile: 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.
graph TB diagram. Call out the "heart" of the system.erDiagram of core entities. Data invariants table: Entity, Invariant, Enforced By, Source.classDiagram showing load-bearing abstractions.sequenceDiagram (with autonumber) showing typical request from entry to response.stateDiagram-v2 for entities with meaningful lifecycle states.flowchart for error propagation paths.Task<T> = Awaitable[T])<!-- Sources: ... --> comment blockFile: 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.
graph LR diagram. Services, data stores, external integrations — NO internal code details. Focus on deployment units and team boundaries.graph TB showing critical external dependencies. Table: Dependency, Type (Service/Library/Platform), Risk if Unavailable.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.
graph LR or journey diagram showing primary user flows through the systemerDiagram showing entities users interact with. Explain in business terms (e.g., "A Project has many Documents" not "FK relationship").ALL diagrams must use dark-mode colors:
#2d333b, borders: #6d5dfc, text: #e6edf3#161b22, borders: #30363d#8b949estyle directives, use dark fills with ,color:#e6edf3<br/> in Mermaid labels (use <br> or line breaks)After generating each guide, verify:
List<T>) outside code fences — wrap in backtickstools
KQL language expertise for writing correct, efficient Kusto Query Language queries. Covers syntax gotchas, join patterns, dynamic types, datetime pitfalls, regex patterns, serialization, memory management, result-size discipline, and advanced functions (geo, vector, graph). USE THIS SKILL whenever writing, debugging, or reviewing KQL queries — even simple ones — because the gotchas section prevents the most common errors that waste tool calls and cause expensive retry cascades. Trigger on: KQL, Kusto, ADX, Azure Data Explorer, Fabric Real-Time Intelligence, EventHouse, Log Analytics, log analysis, data exploration, time series, anomaly detection, summarize, where clause, join, extend, project, let statement, parse operator, extract function, any mention of pipe-forward query syntax.
development
Deploy, evaluate, and manage Foundry agents end-to-end: Docker build, ACR push, hosted/prompt agent create, container start, batch eval, prompt optimization, prompt optimizer workflows, agent.yaml, dataset curation from traces. USE FOR: deploy agent to Foundry, hosted agent, create agent, invoke agent, evaluate agent, run batch eval, optimize prompt, improve prompt, prompt optimization, prompt optimizer, improve agent instructions, optimize agent instructions, optimize system prompt, deploy model, Foundry project, RBAC, role assignment, permissions, quota, capacity, region, troubleshoot agent, deployment failure, create dataset from traces, dataset versioning, eval trending, create AI Services, Cognitive Services, create Foundry resource, provision resource, knowledge index, agent monitoring, customize deployment, onboard, availability. DO NOT USE FOR: Azure Functions, App Service, general Azure deploy (use azure-deploy), general Azure prep (use azure-prepare).
testing
Pre-deployment validation for Azure readiness. Run deep checks on configuration, infrastructure (Bicep or Terraform), RBAC role assignments, managed identity permissions, and prerequisites before deploying. WHEN: validate my app, check deployment readiness, run preflight checks, verify configuration, check if ready to deploy, validate azure.yaml, validate Bicep, test before deploying, troubleshoot deployment errors, validate Azure Functions, validate function app, validate serverless deployment, verify RBAC roles, check role assignments, review managed identity permissions, what-if analysis, validate Container Apps deployment.
testing
Check/manage Azure quotas and usage across providers. For deployment planning, capacity validation, region selection. WHEN: "check quotas", "service limits", "current usage", "request quota increase", "quota exceeded", "validate capacity", "regional availability", "provisioning limits", "vCPU limit", "how many vCPUs available in my subscription".