Testing patterns for PHPUnit and Playwright E2E tests. Use when writing tests, debugging test failures, setting up test coverage, or implementing test patterns for ActivityPub features.
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Use when implementation is complete, all tests pass, and you need to decide how to integrate the work - guides completion of development work by presenting structured options for merge, PR, or cleanup
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查看安装方法安装前可以查看交给 AI 代理的指令内容。
Guide completion of development work by presenting clear options and handling chosen workflow.
Core principle: Verify tests → Present options → Execute choice → Clean up.
Announce at start: "I'm using the finishing-a-development-branch skill to complete this work."
Before presenting options, verify tests pass:
# Run project's test suite
npm test / cargo test / pytest / go test ./...
If tests fail:
Tests failing (<N> failures). Must fix before completing:
[Show failures]
Cannot proceed with merge/PR until tests pass.
Stop. Don't proceed to Step 2.
If tests pass: Continue to Step 2.
# Try common base branches
git merge-base HEAD main 2>/dev/null || git merge-base HEAD master 2>/dev/null
Or ask: "This branch split from main - is that correct?"
Present exactly these 4 options:
Implementation complete. What would you like to do?
1. Merge back to <base-branch> locally
2. Push and create a Pull Request
3. Keep the branch as-is (I'll handle it later)
4. Discard this work
Which option?
Don't add explanation - keep options concise.
# Switch to base branch
git checkout <base-branch>
# Pull latest
git pull
# Merge feature branch
git merge <feature-branch>
# Verify tests on merged result
<test command>
# If tests pass
git branch -d <feature-branch>
Then: Cleanup worktree (Step 5)
# Push branch
git push -u origin <feature-branch>
# Create PR
gh pr create --title "<title>" --body "$(cat <<'EOF'
## Summary
<2-3 bullets of what changed>
## Test Plan
- [ ] <verification steps>
EOF
)"
Then: Cleanup worktree (Step 5)
Report: "Keeping branch <name>. Worktree preserved at <path>."
Don't cleanup worktree.
Confirm first:
This will permanently delete:
- Branch <name>
- All commits: <commit-list>
- Worktree at <path>
Type 'discard' to confirm.
Wait for exact confirmation.
If confirmed:
git checkout <base-branch>
git branch -D <feature-branch>
Then: Cleanup worktree (Step 5)
For Options 1, 2, 4:
Check if in worktree:
git worktree list | grep $(git branch --show-current)
If yes:
git worktree remove <worktree-path>
For Option 3: Keep worktree.
| Option | Merge | Push | Keep Worktree | Cleanup Branch |
|---|---|---|---|---|
| 1. Merge locally | ✓ | - | - | ✓ |
| 2. Create PR | - | ✓ | ✓ | - |
| 3. Keep as-is | - | - | ✓ | - |
| 4. Discard | - | - | - | ✓ (force) |
Skipping test verification
Open-ended questions
Automatic worktree cleanup
No confirmation for discard
Never:
Always:
Called by:
Pairs with:
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Testing patterns for PHPUnit and Playwright E2E tests. Use when writing tests, debugging test failures, setting up test coverage, or implementing test patterns for ActivityPub features.
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Cloud laboratory platform for automated protein testing and validation. Use when designing proteins and needing experimental validation including binding assays, expression testing, thermostability measurements, enzyme activity assays, or protein sequence optimization. Also use for submitting experiments via API, tracking experiment status, downloading results, optimizing protein sequences for better expression using computational tools (NetSolP, SoluProt, SolubleMPNN, ESM), or managing protein design workflows with wet-lab validation.
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Add unsigned integer (uint) type support to PyTorch operators by updating AT_DISPATCH macros. Use when adding support for uint16, uint32, uint64 types to operators, kernels, or when user mentions enabling unsigned types, barebones unsigned types, or uint support.
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This skill should be used when the user asks to "create an agent", "add an agent", "write a subagent", "agent frontmatter", "when to use description", "agent examples", "agent tools", "agent colors", "autonomous agent", or needs guidance on agent structure, system prompts, triggering conditions, or agent development best practices for Claude Code plugins.
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Master advanced AgentDB features including QUIC synchronization, multi-database management, custom distance metrics, hybrid search, and distributed systems integration. Use when building distributed AI systems, multi-agent coordination, or advanced vector search applications.
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Create and train AI learning plugins with AgentDB's 9 reinforcement learning algorithms. Includes Decision Transformer, Q-Learning, SARSA, Actor-Critic, and more. Use when building self-learning agents, implementing RL, or optimizing agent behavior through experience.
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