pr

name	pr
version	1.0.0
description	[Git] Use when you need to create pull request with standard format.
disable-model-invocation	true

Quick Summary

Goal: Create a pull request with standardized format (summary, test plan, changes list).

Workflow:

1. Analyze -- Review all commits and changes on the branch
2. Draft -- Create PR title (<70 chars) and body with summary + test plan
3. Create -- Push branch and create PR via gh pr create

Key Rules:

• PR title under 70 characters; use body for details
• Include summary bullets and test plan checklist
• Push to remote with -u flag before creating PR

Be skeptical. Apply critical thinking, sequential thinking. Every claim needs traced proof, confidence percentages (Idea should be more than 80%).

Create Pull Request: $ARGUMENTS

Create a pull request with the standard project format.

Steps

1. Check current branch status:

   • Run git status to see all changes
   • Run git diff to review modifications
   • Ensure all changes are committed

2. Analyze commits:

   • Run git log --oneline -10 to see recent commits
   • Identify all commits to include in the PR

3. Create PR with standard format:

   gh pr create --title "[Type] Brief description" --body "$(cat <<'EOF'
   ## Summary
   - Bullet points describing changes
   
   ## Changes
   - List of specific changes made
   
   ## Test Plan
   - [ ] Unit tests added/updated
   - [ ] Manual testing completed
   - [ ] No regressions introduced
   
   ## Related Issues
   - Closes #issue_number (if applicable)
   
   Generated with Claude Code
   EOF
   )"
   

4. PR Title Format:

   • [Feature] - New functionality
   • [Fix] - Bug fix
   • [Refactor] - Code improvement
   • [Docs] - Documentation only
   • [Test] - Test changes only

Notes

• Ensure branch is pushed before creating PR
• Target branch is usually develop or master
• Add reviewers if specified in $ARGUMENTS

---

[IMPORTANT] Use TaskCreate to break ALL work into small tasks BEFORE starting — including tasks for each file read. This prevents context loss from long files. For simple tasks, AI MUST ATTENTION ask user whether to skip.

AI Mistake Prevention — Failure modes to avoid on every task: Check downstream references before deleting. Deleting components causes documentation and code staleness cascades. Map all referencing files before removal. Verify AI-generated content against actual code. AI hallucinates APIs, class names, and method signatures. Always grep to confirm existence before documenting or referencing. Trace full dependency chain after edits. Changing a definition misses downstream variables and consumers derived from it. Always trace the full chain. Trace ALL code paths when verifying correctness. Confirming code exists is not confirming it executes. Always trace early exits, error branches, and conditional skips — not just happy path. When debugging, ask "whose responsibility?" before fixing. Trace whether bug is in caller (wrong data) or callee (wrong handling). Fix at responsible layer — never patch symptom site. Assume existing values are intentional — ask WHY before changing. Before changing any constant, limit, flag, or pattern: read comments, check git blame, examine surrounding code. Verify ALL affected outputs, not just the first. Changes touching multiple stacks require verifying EVERY output. One green check is not all green checks. Holistic-first debugging — resist nearest-attention trap. When investigating any failure, list EVERY precondition first (config, env vars, DB names, endpoints, DI registrations, data preconditions), then verify each against evidence before forming any code-layer hypothesis. Surgical changes — apply the diff test. Bug fix: every changed line must trace directly to the bug. Don't restyle or improve adjacent code. Enhancement task: implement improvements AND announce them explicitly. Surface ambiguity before coding — don't pick silently. If request has multiple interpretations, present each with effort estimate and ask. Never assume all-records, file-based, or more complex path.

Critical Thinking Mindset — Apply critical thinking, sequential thinking. Every claim needs traced proof, confidence >80% to act. Anti-hallucination: Never present guess as fact — cite sources for every claim, admit uncertainty freely, self-check output for errors, cross-reference independently, stay skeptical of own confidence — certainty without evidence root of all hallucination.

MUST ATTENTION apply critical thinking — every claim needs traced proof, confidence >80% to act. Anti-hallucination: never present guess as fact.

MUST ATTENTION apply AI mistake prevention — holistic-first debugging, fix at responsible layer, surface ambiguity before coding, re-read files after compaction.

Closing Reminders

IMPORTANT MUST ATTENTION break work into small todo tasks using TaskCreate BEFORE starting IMPORTANT MUST ATTENTION search codebase for 3+ similar patterns before creating new code IMPORTANT MUST ATTENTION cite file:line evidence for every claim (confidence >80% to act) IMPORTANT MUST ATTENTION add a final review todo task to verify work quality

[TASK-PLANNING] Before acting, analyze task scope and systematically break it into small todo tasks and sub-tasks using TaskCreate.