batch-orchestration

Decompose large-scale code changes into independent units executed by parallel agents in isolated git worktrees.

2.8k|277|Updated Feb 1, 2026
One-click install
npx skills add https://github.com/rohitg00/pro-workflow --skill batch-orchestration
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: batch-orchestration
Source: https://github.com/rohitg00/pro-workflow/tree/main/skills/batch-orchestration
Command: npx skills add https://github.com/rohitg00/pro-workflow --skill batch-orchestration

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Applying the same change pattern across dozens of files (migrations, codemods, refactors) is slow and error-prone when done sequentially, and a single agent context cannot reliably handle 10+ files at once.

Core Features & Use Cases

  • Automated Decomposition: Scans the repository, finds every matching target, and splits the work into 5-30 independent, verifiable units.
  • Parallel Isolated Execution: Spawns one background agent per unit, each in its own git worktree, running tests and opening a PR per unit.
  • Approval Gate & Collection: Presents the full unit plan for explicit approval before execution, then collects pass/fail results and PR links, flagging failed units for retry.
  • Use Case: Convert 18 React class components to function components — the orchestrator finds all of them, you approve the plan, and 18 parallel agents each convert, test, and open a PR.

Quick Start

Run /batch followed by a description of the change pattern, such as asking to migrate from moment.js to dayjs across the codebase.

Frequently Asked Questions about batch-orchestration

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I run a large-scale refactor across many files at once?

Use the /batch command with a description of the change pattern, such as converting class components to function components. The orchestrator scans the repo, decomposes the work into 5-30 independent units, and runs one agent per unit in parallel after your approval.

What kinds of changes are best suited for batch parallel agents?

Batch works best for mechanical, repetitive changes: API migrations, dependency upgrades, codemod-style refactors, adding tracing or logging instrumentation, filling test coverage gaps, and applying lint rule fixes across many files.

When should I not use batch orchestration for a code change?

Avoid batching interdependent changes, shared-state modifications, architecture changes, and database schema migrations. These require sequential execution or holistic reasoning rather than independent parallel units.

How do parallel agents avoid conflicting with each other?

Each agent runs in its own isolated git worktree with its own context window, so units never share state or overwrite each other's changes. Each agent tests its own change and opens a separate PR.

What happens when a batch unit fails its tests?

Failed units are flagged in the final collection summary with error details rather than silently skipped. You can retry failed units individually after the batch completes.