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librenotes/.wave/prompts/speckit-flow/create-pr.md
Michael Czechowski 22370827ee Add GitHub issue pipelines and prompts using gh CLI 
gh-issue-impl, gh-issue-research, gh-issue-rewrite, gh-issue-update
pipelines with corresponding prompts for fetch-assess, plan,
implement, and create-pr steps.

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
2026-02-25 17:02:42 +01:00

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You are creating a pull request for the implemented feature and requesting a review.

Feature context: {{ input }}

Working Directory

You are running in an isolated git worktree shared with previous pipeline steps. Your working directory IS the project root. The feature branch was created by a previous step and is already checked out.

Instructions

  1. Find the branch name and feature directory from the spec info artifact

  2. Verify implementation: Run go test -race ./... one final time to confirm all tests pass. If tests fail, fix them before proceeding.

  3. Stage changes: Review all modified and new files with git status and git diff. Stage relevant files — exclude any sensitive files (.env, credentials).

  4. Commit: Create a well-structured commit (or multiple commits if logical):

    • Use conventional commit prefixes: feat:, fix:, refactor:, test:, docs:
    • Write concise commit messages focused on the "why"
    • Do NOT include Co-Authored-By or AI attribution lines

  5. Push: Push the branch to the remote repository:

    git push -u origin HEAD

  6. Create Pull Request: Use gh pr create with a descriptive summary:

    gh pr create --title "<concise title>" --body "<PR body with summary and test plan>"

    The PR body should include:

    • Summary of changes (3-5 bullet points)
    • Link to the spec file in the specs/ directory
    • Test plan describing how changes were validated
    • Any known limitations or follow-up work needed

  7. Request Copilot Review: After the PR is created, request a review from Copilot:

    gh pr edit --add-reviewer "copilot"

CONSTRAINTS

  • Do NOT spawn Task subagents — work directly in the main context

Output

Produce a JSON status report matching the injected output schema.