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cccskills
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batch

Coordinate large migrations, refactors, and bulk renames by splitting them into independent tasks. After plan approval, 5–30 agents work in separate Git worktrees, isolated working directories, then review, test, and open a pull request for each task.

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Research and plan a large-scale change, then execute it in parallel across 5–30 isolated worktree agents that each open a PR.

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适用场景

  • Migrate code across many files
  • Refactor independent modules in parallel
  • Rename identifiers across directories
  • Track tests and pull requests for a large change

包含的文件(1)

  • SKILL.md5.2 KB

SKILL.md(原文)

安装前可以查看交给 AI 代理的指令内容。

Batch: Parallel Work Orchestration

You are orchestrating a large, parallelizable change across this codebase.

User Instruction

$ARGUMENTS

Phase 1: Research and Plan (Plan Mode)

Call the EnterPlanMode tool now to enter plan mode, then:

  1. Understand the scope. Launch one or more subagents (in the foreground — you need their results) to deeply research what this instruction touches. Find all the files, patterns, and call sites that need to change. Understand the existing conventions so the migration is consistent.

  2. Decompose into independent units. Break the work into 5–30 self-contained units. Each unit must:

    • Be independently implementable in an isolated git worktree (no shared state with sibling units)
    • Be mergeable on its own without depending on another unit's PR landing first
    • Be roughly uniform in size (split large units, merge trivial ones)

    Scale the count to the actual work: few files → closer to 5; hundreds of files → closer to 30. Prefer per-directory or per-module slicing over arbitrary file lists.

  3. Determine the e2e test recipe. Figure out how a worker can verify its change actually works end-to-end — not just that unit tests pass. Look for:

    • A claude-in-chrome skill or browser-automation tool (for UI changes: click through the affected flow, screenshot the result)
    • A tmux or CLI-verifier skill (for CLI changes: launch the app interactively, exercise the changed behavior)
    • A dev-server + curl pattern (for API changes: start the server, hit the affected endpoints)
    • An existing e2e/integration test suite the worker can run

    If you cannot find a concrete e2e path, use the AskUserQuestion tool to ask the user how to verify this change end-to-end. Offer 2–3 specific options based on what you found (e.g., "Screenshot via chrome extension", "Run bun run dev and curl the endpoint", "No e2e — unit tests are sufficient"). Do not skip this — the workers cannot ask the user themselves.

    Write the recipe as a short, concrete set of steps that a worker can execute autonomously. Include any setup (start a dev server, build first) and the exact command/interaction to verify.

  4. Write the plan. In your plan file, include:

    • A summary of what you found during research
    • A numbered list of work units — for each: a short title, the list of files/directories it covers, and a one-line description of the change
    • The e2e test recipe (or "skip e2e because …" if the user chose that)
    • The exact worker instructions you will give each agent (the shared template)
  5. Call ExitPlanMode to present the plan for approval.

Phase 2: Spawn Workers (After Plan Approval)

Once the plan is approved, spawn one background agent per work unit using the Agent tool. All agents must use isolation: "worktree" and run_in_background: true. Launch them all in a single message block so they run in parallel.

For each agent, the prompt must be fully self-contained. Include:

  • The overall goal (the user's instruction)
  • This unit's specific task (title, file list, change description — copied verbatim from your plan)
  • Any codebase conventions you discovered that the worker needs to follow
  • The e2e test recipe from your plan (or "skip e2e because …")
  • The worker instructions below, copied verbatim:
After you finish implementing the change:
1. **Code review** — Invoke the `Skill` tool with `skill: "code-review"` to find correctness bugs (it reports findings; it does not edit code). Fix any findings it surfaces before continuing.
2. **Run unit tests** — Run the project's test suite (check for package.json scripts, Makefile targets, or common commands like `npm test`, `bun test`, `pytest`, `go test`). If tests fail, fix them.
3. **Test end-to-end** — Follow the e2e test recipe from the coordinator's prompt (below). If the recipe says to skip e2e for this unit, skip it.
4. **Commit and push** — Commit all changes with a clear message, push the branch, and create a PR with `gh pr create`. Use a descriptive title. If `gh` is not available or the push fails, note it in your final message.
5. **Report** — End with a single line: `PR: <url>` so the coordinator can track it. If no PR was created, end with `PR: none — <reason>`.

Use subagent_type: "general-purpose" unless a more specific agent type fits.

Phase 3: Track Progress

After launching all workers, render an initial status table:

#UnitStatusPR
1<title>running—
2<title>running—

As background-agent completion notifications arrive, parse the PR: <url> line from each agent's result and re-render the table with updated status (done / failed) and PR links. Keep a brief failure note for any agent that did not produce a PR.

When all agents have reported, render the final table and a one-line summary (e.g., "22/24 units landed as PRs").

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