Automate issue-to-Draft-PR pipeline by labeling issues for GitHub Copilot assignment.
Works with
Label an issue with ai-copilot to trigger GitHub Actions, which auto-assigns Copilot via GraphQL and initiates code generation, branch creation, and Draft PR opening
Requires GitHub Copilot Pro+, Business, or Enterprise; one-time setup deploys the workflow, registers a PAT secret, and creates the label
Copilot PRs are treated as external contributions and require manual approval before CI runs; subs
AI-first code editor with Composer
Before installing skills in Cursor, ensure your development environment meets these requirements:
node --versioncopilot-coding-agentExecute the skills CLI command in your project's root directory to begin installation:
Fetches copilot-coding-agent from supercent-io/skills-template 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-coding-agent. Access via /copilot-coding-agent 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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If you add the
ai-copilotlabel to an issue, GitHub Actions automatically assigns it to Copilot, and Copilot creates a branch → writes code → opens a Draft PR.
repo scope# One-click setup (register token + deploy workflow + create label)
bash scripts/copilot-setup-workflow.sh
This script does:
COPILOT_ASSIGN_TOKEN as a repo secret.github/workflows/assign-to-copilot.ymlai-copilot label# Create issue + ai-copilot label → auto-assign Copilot
gh issue create \
--label ai-copilot \
--title "Add user authentication" \
--body "Implement JWT-based auth with refresh tokens. Include login, logout, refresh endpoints."
# Add label to issue #42 → trigger Actions
gh issue edit 42 --add-label ai-copilot
export COPILOT_ASSIGN_TOKEN=<your-pat>
bash scripts/copilot-assign-issue.sh 42
Issue created/labeled
↓
GitHub Actions triggered (assign-to-copilot.yml)
↓
Look up Copilot bot ID via GraphQL
↓
replaceActorsForAssignable → set Copilot as assignee
↓
Copilot Coding Agent starts processing the issue
↓
Create branch → write code → open Draft PR
↓
Auto-assign you as PR reviewer
Required GraphQL header:
GraphQL-Features: issues_copilot_assignment_api_support,coding_agent_model_selection
| Workflow | Trigger | Purpose |
|---|---|---|
assign-to-copilot.yml |
Issue labeled ai-copilot |
Auto-assign to Copilot |
copilot-pr-ci.yml |
PR open/update | Run CI (build + tests) |
Copilot is treated like an external contributor.
copilot-pr-ci.yml CI runs normally# Check CI after manual approval
gh pr list --search 'head:copilot/'
gh pr view <pr-number>
Review the issue spec in planno before assigning to Copilot (independent skill, not required):
Review and approve this issue spec in planno
After approval, add the ai-copilot label → trigger Actions.
PM writes an issue → add ai-copilot label
→ Actions auto-assigns → Copilot creates Draft PR
→ Team only performs PR review
Follow-up issues created by Vibe Kanban:
refactors/docs cleanup/add tests
→ ai-copilot label → Copilot handles
→ Team focuses on main feature development
Jira issue → Zapier/webhook → auto-create GitHub Issue
→ ai-copilot label → Copilot PR
→ Fully automated pipeline
# Bulk-add label to backlog issues
gh issue list --label "tech-debt" --json number \
| jq '.[].number' \
| xargs -I{} gh issue edit {} --add-label ai-copilot
# List PRs created by Copilot
gh pr list --search 'head:copilot/'
# Specific issue status
gh issue view 42
# PR CI status
gh pr checks <pr-number>
=== Setup ===
bash scripts/copilot-setup-workflow.sh one-time setup
=== Issue assignment ===
gh issue create --label ai-copilot ... new issue + auto-assign
gh issue edit <num> --add-label ai-copilot existing issue
bash scripts/copilot-assign-issue.sh <num> manual assign
=== Verify results ===
gh pr list --search 'head:copilot/' Copilot PR list
gh pr view <num> PR details
gh pr checks <num> CI status
=== Constraints ===
Copilot Pro+/Business/Enterprise required
First PR requires manual approval (treated as an external contributor)
PAT: repo scope required
Make data-driven prioritization decisions faster
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
Prerequisites
Time Estimate
30-60 minutes to see productivity improvements
Steps
Common Pitfalls
✓ Do
✗ Don't
💡 Pro Tips
✓ 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.
supercent-io/skills-template
mattpocock/skills
parcadei/continuous-claude-v3
cursor/plugins
ailabs-393/ai-labs-claude-skills
pproenca/dot-skills
We added copilot-coding-agent from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.
Solid pick for teams standardizing on skills: copilot-coding-agent is focused, and the summary matches what you get after install.
Registry listing for copilot-coding-agent matched our evaluation — installs cleanly and behaves as described in the markdown.
Useful defaults in copilot-coding-agent — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.
copilot-coding-agent has been reliable in day-to-day use. Documentation quality is above average for community skills.
copilot-coding-agent reduced setup friction for our internal harness; good balance of opinion and flexibility.
Registry listing for copilot-coding-agent matched our evaluation — installs cleanly and behaves as described in the markdown.
copilot-coding-agent fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.
We added copilot-coding-agent from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.
copilot-coding-agent has been reliable in day-to-day use. Documentation quality is above average for community skills.
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