Github Issue Complete

GitHub Issue Complete Workflow (Full Auto)

This skill provides a "one-stop shop" for the entire software development lifecycle on GitHub. It implements a dual-issue strategy: a Main Issue (human-facing) for project management and a Sub-Issue (agent-facing) for implementation.

📋 Mandatory Task List (task.md)

At the very beginning of Phase 1, the agent MUST initialize and maintain a local task.md file in the workspace containing all steps of the workflow. The agent must update the progress ([ ] to [/] to [x]) continuously and print the updated plan explicitly to the user.

Mandatory task.md Template:

- [ ] Phase 1: Initialization & Strategy
  - [ ] Determine/Fetch Main Issue
  - [ ] Create/Prepare Human-Facing Main Issue with assignments (read from `package.json` `"agents"` block or fallback `docs/project.json` stakeholders)
  - [ ] Create Agent Issue (Sub-Issue, title prefix `[Agent]`) and link natively via helper script or fallback
  - [ ] Link Agent Issue inside Main Issue checklist
- [ ] Phase 2: Implementation & Validation
  - [ ] Set up Git Worktree and copy `.env` configuration
  - [ ] Implement features and refactorings
  - [ ] Perform Code Verification (Unit tests, TypeScript compile check, ESLint verification)
  - [ ] Perform Local Code Review (utilizing `review-code` skill inside a generalist subagent)
  - [ ] Create Pull Request (Title: `feat: ...`, body resolves Agent Issue, references Main Issue)
- [ ] Phase 3: Quality Gate & Review
  - [ ] Trigger remote PR review via `review-pull-request` skill
  - [ ] Resolve any review findings via `resolve-review` skill
- [ ] Phase 4: Finalization & Handover
  - [ ] Update Main Issue checklist to complete
  - [ ] Add `test` label to Main Issue
  - [ ] Post Browser Click Path and testing instructions comments on Main Issue
  - [ ] Ask user to test locally and confirm task completion BEFORE running cleanup
  - [ ] Run `npm run log:clear` to clean temporary log files
  - [ ] Present final summary with links to Main Issue, Agent Issue, and Pull Request

---

Phase 1: Initialization & Strategy

1. Analyze User Input: Extract the core objective, any constraints, and relevant context.
2. Initialize Task List: Create task.md with the template above and print the plan to the user.
3. Determine Main Issue:

• Ask the user: "Should I create a new Main Issue for this request, or use an existing one as a reference?"
• YOLO Mode / No Response: If the user is in YOLO mode or provides no specific issue, default to creating a new Main Issue.
• If using an existing issue, fetch its details: gh issue view .

1. Create/Prepare Main Issue (Human-Facing):

• Goal: This issue tracks the high-level requirement and is used by project managers and testers.
• Content: Must include the user's initial prompt and all relevant information passed to the agent.
• Assignment: Assign the Product Manager and Senior Developer usernames retrieved from package.json "agents" block or fallback docs/project.json stakeholders (e.g. productManager and seniorDeveloper). If neither is present, default to @me.
• Sub-Task Checklist: Add a section ## Implementation Progress with a checkbox for the sub-issue: - [ ] Agent Issue #: [Short Description].
• Action:
• If new: gh issue create --title "[Feature/Bug] " --body "" --assignee "pm-username,dev-username"
• If existing: Update the body to include the new requirement and the checklist.

1. Create and Link Agent Issue (Sub-Issue):

• Goal: This is the technical implementation ticket for the agent, natively linked as a GitHub sub-issue.
• Action:
• Activate the github-issue-create skill to construct and create the implementation issue (Prefix: [Agent]).
• Extract the created sub-issue's sequential issue number (e.g., #).
• Natively link the sub-issue to the Main Issue using the foolproof helper script (which resolves the database ID and handles markdown fallbacks automatically):

``bash npx node .agents/skills/github-sub-issue-add/scripts/github-sub-issue-helper.js add --parent --sub ``

• Activate the github-issue-refine skill on the sub-issue to ensure it's implementation-ready.
• Update the Main Issue: Replace # in the Main Issue's checklist with the actual Agent Issue number.

---

Phase 2: Implementation & Validation

1. Solve the Agent Issue: Activate the github-issue-solve skill.

• CRITICAL: Pass the Agent Issue Number to github-issue-solve.
• Follow its workflow for implementation, testing (Vitest, Browser + Logs), and internal review.

1. Perform Local Code Review (CRITICAL): Activate the review-code skill.

• You MUST run the review-code skill inside a generalist/research subagent to evaluate local changes objectively.
• Meticulously check for compliance with AGENTS.md, docs/rules/, and look out for critical bugs or code quality issues.
• Any 🔴 Critical or 🟠 High findings must be resolved before proceeding.

1. Create Pull Request: The PR should be created as part of the github-issue-solve workflow.

• Ensure the PR body says Resolves # and Part of #.

---

Phase 3: Quality Gate & Review

1. PR Review: Activate the review-pull-request skill to review the remote PR.
2. Resolution: Activate resolve-review if changes are requested.

---

Phase 4: Finalization & Handover

1. Update Main Issue:

• Label: Add the test label to the Main Issue.
• Click Path: Post a comment on the Main Issue with the Browser Click Path for testing (using the PR deployment URL).
• Checklist: Update the checklist in the Main Issue body to mark the sub-issue as complete: - [x] Agent Issue #.

1. Request Local Testing & Confirmation (MANDATORY):

• Stop executing automated steps.
• Explicitly present your final implementation details, screenshots/click-paths, and the URL/port of your local running instance.
• Ask the user to test the changes locally in their browser.
• Seek explicit, written user confirmation that the task is fully complete and that you are authorized to run cleanup.

1. Cleanup (Only after confirmation):

• Remove any isolated git worktrees if applicable.
• Run npm run log:clear to clean temporary log files.

1. Final Summary:

• Inform the user that the sub-issue is complete and the Main Issue is ready for testing.
• Provide links to the Main Issue, Agent Issue, and Pull Request.

Source & license

This open-source skill is cataloged on AgentStack and links to its original source — we do not rehost the code.

• Author: P2ERGmbH
• Source: P2ERGmbH/agentic-coding
• License: MIT

Install and usage instructions live in the source repository linked above.