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Batch Large-Scale Changes

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Claude Code's official bundled skill /batch automates large-scale code changes. It researches the codebase to understand change scope, decomposes work into 5-30 independent units, processes each in a separate git worktree with an independent agent, and automatically creates PRs upon completion.

Trigger/batch
FrequencyFor large tasks

Team needing API migration across hundreds of files? Use /batch to auto-decompose and parallelize changes

Tech lead enforcing code standards across the codebase? Run /batch to split by module and generate PRs at once

BatchParallelWorktreeBundled SkillLarge-Scale

How It Works

Run /batch [description] → Research codebase
Decompose into 5-30 independent units + execution plan
Phase 2: Parallel agents per worktree
worktree-1
Process unit 1 changes
worktree-2
Process unit 2 changes
worktree-N
Process unit N changes
Auto-generate PRs per unit + change summary

Skill Code

# Batch Orchestrator — Built-in Bundled Skill ## Trigger: /batch [change description] Claude Code's official bundled skill for large-scale codebase changes. ### Workflow: 1. Research phase: - Scan codebase for affected files - Identify dependencies and impact scope - Map change boundaries 2. Decomposition: - Split into 5-30 independent units - Ensure each unit is self-contained - Generate execution plan with ordering 3. Parallel execution (git worktrees): ```bash # Each unit runs in its own worktree .claude/worktrees/batch-unit-1/ .claude/worktrees/batch-unit-2/ .claude/worktrees/batch-unit-N/ # Each agent: # 1. Creates a branch # 2. Applies changes # 3. Runs tests # 4. Creates a PR ``` 4. Post-processing: - Collect results from all worktrees - Report success/failure per unit - Generate summary with PR links ### Key features: - Automatic conflict detection between units - Shared memory across worktrees (v2.1.63+) - Resume capability for failed units - Dry-run mode for preview ### SKILL.md structure: ```yaml --- name: batch description: Research codebase, decompose, and parallelize changes ```

Copy and paste into your CLAUDE.md to start using immediately.

How Batch Large-Scale Changes Works

Batch scans the codebase to map change scope, decomposes work into 5-30 independent units, processes each in a separate git worktree, and auto-generates PRs after tests pass.

When to Use Batch Large-Scale Changes

Ideal for API migrations, code standard enforcement, framework upgrades, and other changes spanning hundreds of files.

Key Strengths

  • Auto-decomposition splits large tasks into manageable units
  • Git worktree-based parallel execution prevents conflicts
  • Per-unit PR creation simplifies code review
  • Failed units can be retried independently

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