Programmatic agent runtime for embedding Copilot's agentic workflows in applications across Python, TypeScript, Go, and .NET.
Works with
Exposes the same production-tested engine behind Copilot CLI with support for streaming responses, custom tool definitions, and multi-turn conversations
Supports four language runtimes (Node.js 18+, Python 3.8+, Go 1.21+, .NET 8.0+) with consistent APIs across all platforms
Enables integration with MCP servers for pre-built tools, custom agent personas with sp
AI-first code editor with Composer
Before installing skills in Cursor, ensure your development environment meets these requirements:
node --versioncopilot-sdkExecute the skills CLI command in your project's root directory to begin installation:
Fetches copilot-sdk from github/awesome-copilot and configures it for Cursor.
The CLI shows a list of agents. Use arrow keys and space to select Cursor:
Confirm successful installation by checking the skill directory location:
Restart Cursor to activate copilot-sdk. Access via /copilot-sdk in your agent's command palette.
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 environment. Always review source, verify the publisher, and test in isolation before production.
Submit your Claude Code skill and start earning
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
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
Evaluate features using frameworks (RICE, ICE, Kano) and create prioritized backlogs
Example
Score 20 feature ideas using RICE framework, generate prioritized roadmap with rationale
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Embed Copilot's agentic workflows in any application using Python, TypeScript, Go, or .NET.
The GitHub Copilot SDK exposes the same engine behind Copilot CLI: a production-tested agent runtime you can invoke programmatically. No need to build your own orchestration - you define agent behavior, Copilot handles planning, tool invocation, file edits, and more.
Verify CLI: copilot --version
mkdir copilot-demo && cd copilot-demo
npm init -y --init-type module
npm install @github/copilot-sdk tsx
pip install github-copilot-sdk
mkdir copilot-demo && cd copilot-demo
go mod init copilot-demo
go get github.com/github/copilot-sdk/go
dotnet new console -n CopilotDemo && cd CopilotDemo
dotnet add package GitHub.Copilot.SDK
import { CopilotClient, approveAll } from "@github/copilot-sdk";
const client = new CopilotClient();
const session = await client.createSession({
onPermissionRequest: approveAll,
model: "gpt-4.1",
});
const response = await session.sendAndWait({ prompt: "What is 2 + 2?" });
console.log(response?.data.content);
await client.stop();
process.exit(0);
Run: npx tsx index.ts
import asyncio
from copilot import CopilotClient, PermissionHandler
async def main():
client = CopilotClient()
await client.start()
session = await client.create_session({
"on_permission_request": PermissionHandler.approve_all,
"model": "gpt-4.1",
})
response = await session.send_and_wait({"prompt": "What is 2 + 2?"})
print(response.data.content)
await client.stop()
asyncio.run(main())
package main
import (
"fmt"
"log"
"os"
copilot "github.com/github/copilot-sdk/go"
)
func main() {
client := copilot.NewClient(nil)
if err := client.Start(); err != nil {
log.Fatal(err)
}
defer client.Stop()
session, err := client.CreateSession(&copilot.SessionConfig{
OnPermissionRequest: copilot.PermissionHandler.ApproveAll,
Model: "gpt-4.1",
})
if err != nil {
log.Fatal(err)
}
response, err := session.SendAndWait(copilot.MessageOptions{Prompt: "What is 2 + 2?"}, 0)
if err != nil {
log.Fatal(err)
}
fmt.Println(*response.Data.Content)
os.Exit(0)
}
using GitHub.Copilot.SDK;
await using var client = new CopilotClient();
await using var session = await client.CreateSessionAsync(new SessionConfig
{
OnPermissionRequest = PermissionHandler.ApproveAll,
Model = "gpt-4.1",
});
var response = await session.SendAndWaitAsync(new MessageOptions { Prompt = "What is 2 + 2?" });
Console.WriteLine(response?.Data.Content);
Run: dotnet run
Enable real-time output for better UX:
import { CopilotClient, approveAll, SessionEvent } from "@github/copilot-sdk";
const client = new CopilotClient();
const session = await client.createSession({
onPermissionRequest: approveAll,
model: "gpt-4.1",
streaming: true,
});
session.on((event: SessionEvent) => {
if (event.type === "assistant.message_delta") {
process.stdout.write(event.data.deltaContent);
}
if (event.type === "session.idle") {
console.log(); // New line when done
}
});
await session.sendAndWait({ prompt: "Tell me a short joke" });
await client.stop();
process.exit(0);
import asyncio
import sys
from copilot import CopilotClient, PermissionHandler
from copilot.generated.session_events import SessionEventType
async def main():
client = CopilotClient()
await client.start()
✓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
Steps
- 1Install product management skill
- 2Start with user story generation for known feature
- 3Progress to competitive analysis: research 2-3 competitors
- 4Use for roadmap prioritization: apply RICE/ICE scoring
- 5Draft stakeholder communications and refine based on feedback
- 6Build template library for recurring PM tasks
- 7Share 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
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Productivitysame categoryReviews
4.7★★★★★56 reviews- VValentina Flores★★★★★Dec 28, 2024
I recommend copilot-sdk for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.
- SSakura Zhang★★★★★Dec 24, 2024
copilot-sdk reduced setup friction for our internal harness; good balance of opinion and flexibility.
- DDhruvi Jain★★★★★Dec 4, 2024
We added copilot-sdk from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.
- OOshnikdeep★★★★★Nov 23, 2024
copilot-sdk fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.
- MMichael Torres★★★★★Nov 19, 2024
Useful defaults in copilot-sdk — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.
- AAva Yang★★★★★Nov 15, 2024
copilot-sdk has been reliable in day-to-day use. Documentation quality is above average for community skills.
- GGanesh Mohane★★★★★Oct 14, 2024
copilot-sdk is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.
- DDiya Okafor★★★★★Oct 10, 2024
copilot-sdk has been reliable in day-to-day use. Documentation quality is above average for community skills.
- ZZara Malhotra★★★★★Oct 6, 2024
Useful defaults in copilot-sdk — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.
- VValentina Tandon★★★★★Sep 25, 2024
copilot-sdk is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.
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