typespec-create-agent▌
github/awesome-copilot · updated Apr 8, 2026
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Generate a complete TypeSpec declarative agent for Microsoft 365 Copilot with instructions, capabilities, and conversation starters.
- ›Produces a main.tsp file with agent declaration, instructions, conversation starters, and capability definitions following Microsoft's TypeSpec M365 Copilot schema
- ›Supports 10 capability types including WebSearch, OneDriveAndSharePoint, TeamsMessages, Email, People, CodeInterpreter, GraphicArt, GraphConnectors, Dataverse, and Meetings with optional scoping
Create TypeSpec Declarative Agent
Create a complete TypeSpec declarative agent for Microsoft 365 Copilot with the following structure:
Requirements
Generate a main.tsp file with:
-
Agent Declaration
- Use
@agentdecorator with a descriptive name and description - Name should be 100 characters or less
- Description should be 1,000 characters or less
- Use
-
Instructions
- Use
@instructionsdecorator with clear behavioral guidelines - Define the agent's role, expertise, and personality
- Specify what the agent should and shouldn't do
- Keep under 8,000 characters
- Use
-
Conversation Starters
- Include 2-4
@conversationStarterdecorators - Each with a title and example query
- Make them diverse and showcase different capabilities
- Include 2-4
-
Capabilities (based on user needs)
WebSearch- for web content with optional site scopingOneDriveAndSharePoint- for document access with URL filteringTeamsMessages- for Teams channel/chat accessEmail- for email access with folder filteringPeople- for organization people searchCodeInterpreter- for Python code executionGraphicArt- for image generationGraphConnectors- for Copilot connector contentDataverse- for Dataverse data accessMeetings- for meeting content access
Template Structure
import "@typespec/http";
import "@typespec/openapi3";
import "@microsoft/typespec-m365-copilot";
using TypeSpec.Http;
using TypeSpec.M365.Copilot.Agents;
@agent({
name: "[Agent Name]",
description: "[Agent Description]"
})
@instructions("""
[Detailed instructions about agent behavior, role, and guidelines]
""")
@conversationStarter(#{
title: "[Starter Title 1]",
text: "[Example query 1]"
})
@conversationStarter(#{
title: "[Starter Title 2]",
text: "[Example query 2]"
})
namespace [AgentName] {
// Add capabilities as operations here
op capabilityName is AgentCapabilities.[CapabilityType]<[Parameters]>;
}
Best Practices
- Use descriptive, role-based agent names (e.g., "Customer Support Assistant", "Research Helper")
- Write instructions in second person ("You are...")
- Be specific about the agent's expertise and limitations
- Include diverse conversation starters that showcase different features
- Only include capabilities the agent actually needs
- Scope capabilities (URLs, folders, etc.) when possible for better performance
- Use triple-quoted strings for multi-line instructions
Examples
Ask the user:
- What is the agent's purpose and role?
- What capabilities does it need?
- What knowledge sources should it access?
- What are typical user interactions?
Then generate the complete TypeSpec agent definition.
How to use typespec-create-agent 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 typespec-create-agent
Execute installation command
Execute the skills CLI command in your project's root directory to begin installation:
The skills CLI fetches typespec-create-agent 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 typespec-create-agent. Access the skill through slash commands (e.g., /typespec-create-agent) 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.
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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
4.6★★★★★53 reviews- ★★★★★Amelia Chen· Dec 16, 2024
typespec-create-agent is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.
- ★★★★★Neel Jackson· Dec 16, 2024
Solid pick for teams standardizing on skills: typespec-create-agent is focused, and the summary matches what you get after install.
- ★★★★★Xiao Harris· Dec 12, 2024
typespec-create-agent fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.
- ★★★★★James Srinivasan· Dec 12, 2024
typespec-create-agent has been reliable in day-to-day use. Documentation quality is above average for community skills.
- ★★★★★Aditi Robinson· Dec 4, 2024
Keeps context tight: typespec-create-agent is the kind of skill you can hand to a new teammate without a long onboarding doc.
- ★★★★★Aanya Liu· Nov 23, 2024
typespec-create-agent has been reliable in day-to-day use. Documentation quality is above average for community skills.
- ★★★★★Ishan Ramirez· Nov 7, 2024
Solid pick for teams standardizing on skills: typespec-create-agent is focused, and the summary matches what you get after install.
- ★★★★★Sofia Tandon· Nov 7, 2024
typespec-create-agent is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.
- ★★★★★Alexander Flores· Nov 3, 2024
Keeps context tight: typespec-create-agent is the kind of skill you can hand to a new teammate without a long onboarding doc.
- ★★★★★Ishan Abbas· Oct 26, 2024
typespec-create-agent has been reliable in day-to-day use. Documentation quality is above average for community skills.
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