AgentSkillsCN

clean-branch

清理已合并的分支，关闭问题，并提炼复合型学习洞察

SKILL.md
--- frontmatter
name: clean-branch
description: Clean up merged branches, close issues, and extract compound learning insights
model: claude-sonnet-4-5
context: fork
agent: general-purpose
allowed-tools:
  - Bash(*)
  - Read
  - Edit
  - Write
  - Task
extended-thinking: true

Branch Cleanup & PR Retrospective

You've just merged a PR to dev. Now complete the post-merge cleanup workflow.

Workflow

Phase 1: Identify Current State

First, determine what branch you're on and find the associated merged PR and issue:

bash
# Get current branch name
git branch --show-current

# Find merged PR for this branch
gh pr list --state merged --head $(git branch --show-current) --limit 1

# Get full PR details to find issue number
gh pr view <PR_NUMBER> --json number,title,body

Phase 2: Branch Cleanup

Perform standard cleanup operations:

bash
# Switch to dev and pull latest
git checkout dev
git pull origin dev

# Delete local feature branch
git branch -d <BRANCH_NAME>

# Delete remote feature branch
git push origin --delete <BRANCH_NAME>

Phase 3: Close Associated Issue

Close the GitHub issue with a summary of what was completed:

bash
# View issue to understand what was done
gh issue view <ISSUE_NUMBER>

# Close issue with comment summarizing the work
gh issue close <ISSUE_NUMBER> --comment "Completed in PR #<PR_NUMBER>.

<Brief 1-2 sentence summary of what was implemented/fixed>

Changes merged to dev."

Important Notes

  • •PR Analysis: Compound engineering analysis happens automatically via the Stop hook
  • •No manual telemetry: The telemetry system will detect this command and analyze the PR for learning opportunities
  • •Summary format: Keep issue close comments concise but informative

What Happens Automatically

After you complete the cleanup, the telemetry system will:

  1. •Analyze the merged PR for patterns (review iterations, fix commits, common themes)
  2. •Identify compound engineering opportunities (automation, systematization, delegation)
  3. •Save insights to meta/telemetry.json in the compound_learnings[] array
  4. •Log suggestions for preventing similar issues in future PRs

This analysis looks for:

  • •Delegation opportunities: When specialized agents could have helped
  • •Automation candidates: Recurring manual processes
  • •Systematization targets: Knowledge for documentation
  • •Prevention patterns: Issues needing earlier intervention