microsoft-code-reference▌
github/awesome-copilot · updated Apr 8, 2026
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Verify Microsoft SDK methods, find working code samples, and catch hallucinated APIs against official docs.
- ›Three core tools: microsoft_docs_search for API lookups, microsoft_code_sample_search for working examples in C#/Python/JavaScript, and microsoft_docs_fetch for full reference pages with overloads
- ›Catches common mistakes like wrong method signatures, deprecated patterns, mismatched SDK versions (v11 vs v12), and incorrect package names
- ›Works with Azure SDKs, .NET libraries, and
Microsoft Code Reference
Tools
| Need | Tool | Example |
|---|---|---|
| API method/class lookup | microsoft_docs_search |
"BlobClient UploadAsync Azure.Storage.Blobs" |
| Working code sample | microsoft_code_sample_search |
query: "upload blob managed identity", language: "python" |
| Full API reference | microsoft_docs_fetch |
Fetch URL from microsoft_docs_search (for overloads, full signatures) |
Finding Code Samples
Use microsoft_code_sample_search to get official, working examples:
microsoft_code_sample_search(query: "upload file to blob storage", language: "csharp")
microsoft_code_sample_search(query: "authenticate with managed identity", language: "python")
microsoft_code_sample_search(query: "send message service bus", language: "javascript")
When to use:
- Before writing code—find a working pattern to follow
- After errors—compare your code against a known-good sample
- Unsure of initialization/setup—samples show complete context
API Lookups
# Verify method exists (include namespace for precision)
"BlobClient UploadAsync Azure.Storage.Blobs"
"GraphServiceClient Users Microsoft.Graph"
# Find class/interface
"DefaultAzureCredential class Azure.Identity"
# Find correct package
"Azure Blob Storage NuGet package"
"azure-storage-blob pip package"
Fetch full page when method has multiple overloads or you need complete parameter details.
Error Troubleshooting
Use microsoft_code_sample_search to find working code samples and compare with your implementation. For specific errors, use microsoft_docs_search and microsoft_docs_fetch:
| Error Type | Query |
|---|---|
| Method not found | "[ClassName] methods [Namespace]" |
| Type not found | "[TypeName] NuGet package namespace" |
| Wrong signature | "[ClassName] [MethodName] overloads" → fetch full page |
| Deprecated warning | "[OldType] migration v12" |
| Auth failure | "DefaultAzureCredential troubleshooting" |
| 403 Forbidden | "[ServiceName] RBAC permissions" |
When to Verify
Always verify when:
- Method name seems "too convenient" (
UploadFilevs actualUpload) - Mixing SDK versions (v11
CloudBlobClientvs v12BlobServiceClient) - Package name doesn't follow conventions (
Azure.*for .NET,azure-*for Python) - Using an API for the first time
Validation Workflow
Before generating code using Microsoft SDKs, verify it's correct:
- Confirm method or package exists —
microsoft_docs_search(query: "[ClassName] [MethodName] [Namespace]") - Fetch full details (for overloads/complex params) —
microsoft_docs_fetch(url: "...") - Find working sample —
microsoft_code_sample_search(query: "[task]", language: "[lang]")
For simple lookups, step 1 alone may suffice. For complex API usage, complete all three steps.
CLI Alternative
If the Learn MCP server is not available, use the mslearn CLI from a terminal or shell (for example, Bash, PowerShell, or cmd) instead:
# Run directly (no install needed)
npx @microsoft/learn-cli search "BlobClient UploadAsync Azure.Storage.Blobs"
# Or install globally, then run
npm install -g @microsoft/learn-cli
mslearn search "BlobClient UploadAsync Azure.Storage.Blobs"
| MCP Tool | CLI Command |
|---|---|
microsoft_docs_search(query: "...") |
mslearn search "..." |
microsoft_code_sample_search(query: "...", language: "...") |
mslearn code-search "..." --language ... |
microsoft_docs_fetch(url: "...") |
mslearn fetch "..." |
Pass --json to search or code-search to get raw JSON output for further processing.
How to use microsoft-code-reference on Cursor
AI-first code editor with Composer
Prerequisites
Before installing skills in Cursor, ensure your development environment meets these requirements:
- ›Cursor installed and configured on your development machine
- ›Node.js version 16.0+ with npm package manager (verify with
node --version) - ›Active project directory or workspace where you want to add microsoft-code-reference
Execute installation command
Execute the skills CLI command in your project's root directory to begin installation:
The skills CLI fetches microsoft-code-reference from GitHub repository github/awesome-copilot and configures it for Cursor.
Select Cursor when prompted
The CLI will show a list of available agents. Use arrow keys to navigate and space to select Cursor:
Verify installation
Confirm successful installation by checking the skill directory location:
Reload or restart Cursor to activate microsoft-code-reference. Access the skill through slash commands (e.g., /microsoft-code-reference) or your agent's skill management interface.
Security & Verification Notice
We perform automated surface-level scans (Gen AI Scanner, Socket, Snyk) during installation. These checks detect common vulnerabilities but do not guarantee complete security. Always review skill source code and verify the publisher's reputation before production use.
Skills execute code in your development environment. Always verify the publisher's identity, review recent commits, and test in isolated environments before production deployment.
List & Monetize Your Skill
Submit your Claude Code skill and start earning
Use Cases▌
User Story & Requirements Generation
Create detailed user stories, acceptance criteria, and feature specs
Example
Generate user stories for 'password reset feature' with acceptance criteria, edge cases, and test scenarios
Reduce spec writing time by 50%, ensure comprehensive coverage
Competitive Analysis
Research competitors, compare features, identify gaps
Example
Analyze 5 competitor products, create feature comparison matrix, suggest differentiation opportunities
Complete competitive research in 2 hours instead of 2 days
Roadmap Prioritization
Evaluate features using frameworks (RICE, ICE, Kano) and create prioritized backlogs
Example
Score 20 feature ideas using RICE framework, generate prioritized roadmap with rationale
Make data-driven prioritization decisions faster
Stakeholder Communication
Draft PRDs, status updates, and stakeholder presentations
Example
Create executive summary of Q3 roadmap, monthly progress report, feature launch announcement
Save 3-5 hours/week on communication overhead
Implementation Guide▌
Prerequisites
- ›Claude Desktop or compatible AI client
- ›Access to product documentation and roadmap tools (Jira, Notion, etc.)
- ›Understanding of product management frameworks (RICE, Jobs-to-be-Done, etc.)
- ›Stakeholder contact information and communication channels
Time Estimate
30-60 minutes to see productivity improvements
Installation Steps
- 1.Install product management skill
- 2.Start with user story generation for known feature
- 3.Progress to competitive analysis: research 2-3 competitors
- 4.Use for roadmap prioritization: apply RICE/ICE scoring
- 5.Draft stakeholder communications and refine based on feedback
- 6.Build template library for recurring PM tasks
- 7.Share effective prompts with product team
Common Pitfalls
- ⚠Not validating competitive research—verify facts before sharing
- ⚠Accepting user stories without involving engineering team
- ⚠Over-relying on frameworks without qualitative judgment
- ⚠Not customizing outputs to company culture and communication style
- ⚠Skipping stakeholder validation of generated requirements
Best Practices▌
✓ Do
- +Validate research and competitive analysis with real data
- +Collaborate with engineering when generating technical requirements
- +Customize frameworks and templates to your company context
- +Use skill for first drafts, refine with stakeholder input
- +Document successful prompt patterns for PM tasks
- +Combine AI efficiency with human judgment and intuition
✗ Don't
- −Don't publish competitive analysis without fact-checking
- −Don't finalize user stories without engineering review
- −Don't make prioritization decisions solely on AI scoring
- −Don't skip customer validation of generated requirements
- −Don't ignore company-specific context and culture
💡 Pro Tips
- ★Provide context: company goals, constraints, customer feedback
- ★Ask for alternatives: 'Show 3 ways to prioritize this roadmap'
- ★Request stakeholder-specific formatting: 'Executive summary vs. engineering spec'
- ★Use skill for 70% generation + 30% customization to company needs
When to Use This▌
✓ Use When
Use for user story writing, competitive research, roadmap prioritization, stakeholder communication, and PRD drafting. Best for reducing repetitive documentation and research work.
✗ Avoid When
Avoid for strategic product vision (requires deep customer empathy), pricing decisions (needs market and financial expertise), or when face-to-face customer discovery is more valuable than speed.
Learning Path▌
- 1Basic: user stories, feature specs, status updates
- 2Intermediate: competitive analysis, prioritization frameworks, PRDs
- 3Advanced: product strategy, go-to-market planning, OKR setting
- 4Expert: product vision, market positioning, business model innovation
Discussion
Product Hunt–style comments (not star reviews)- No comments yet — start the thread.
Ratings
4.8★★★★★27 reviews- ★★★★★Daniel Chawla· Dec 16, 2024
Keeps context tight: microsoft-code-reference is the kind of skill you can hand to a new teammate without a long onboarding doc.
- ★★★★★Chaitanya Patil· Dec 4, 2024
microsoft-code-reference is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.
- ★★★★★Piyush G· Nov 23, 2024
Keeps context tight: microsoft-code-reference is the kind of skill you can hand to a new teammate without a long onboarding doc.
- ★★★★★Naina Garcia· Nov 7, 2024
microsoft-code-reference is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.
- ★★★★★Maya Agarwal· Nov 3, 2024
microsoft-code-reference reduced setup friction for our internal harness; good balance of opinion and flexibility.
- ★★★★★Naina Johnson· Oct 26, 2024
microsoft-code-reference fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.
- ★★★★★Shikha Mishra· Oct 14, 2024
Registry listing for microsoft-code-reference matched our evaluation — installs cleanly and behaves as described in the markdown.
- ★★★★★Yash Thakker· Sep 21, 2024
microsoft-code-reference reduced setup friction for our internal harness; good balance of opinion and flexibility.
- ★★★★★Luis Dixit· Sep 5, 2024
microsoft-code-reference has been reliable in day-to-day use. Documentation quality is above average for community skills.
- ★★★★★Sofia Sharma· Aug 24, 2024
Useful defaults in microsoft-code-reference — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.
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