batch-orchestration

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

1|Updated May 6, 2026
One-click install
npx skills add https://github.com/surfingalien/FinSurfing --skill batch-orchestration-surfingalien
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: batch-orchestration
Source: https://github.com/surfingalien/FinSurfing/tree/main/.claude/skills/batch-orchestration
Command: npx skills add https://github.com/surfingalien/FinSurfing --skill batch-orchestration-surfingalien

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 risky when done in one giant edit. This Skill splits the work into independent units and runs them in parallel with isolated worktrees and per-unit verification. ## Core Features & Use Cases - Research and Decomposition: Scans the repo to find every matching instance, then splits the work into 5-30 independent, self-contained, verifiable units. - Plan Approval Gate: Presents the full unit list and waits for explicit confirmation before spawning any agents. - Parallel Execution with Isolation: Each unit runs in its own git worktree with a dedicated background agent that implements the change, runs tests, and opens a PR. - Use Case: Convert 18 React class components to function components — the Skill finds all 18, gets your approval, then runs 18 parallel agents that each convert one file, run its tests, and open a PR. ## Quick Start Ask the AI to run /batch followed by a change pattern, such as converting all React class components to function components 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 finds all matching files, splits them into independent units, and runs one agent per unit in parallel after your approval.

How does parallel code migration avoid merge conflicts?

Each unit runs in its own isolated git worktree with a dedicated agent and context window, so agents never write to the same checkout. Each agent opens a separate pull request, keeping changes independent and reviewable.

When should I not use batch orchestration for code changes?

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

How many files justify using a batch workflow?

The recommended range is 5 to 30 independent units. Fewer than 5 does not justify the orchestration overhead, while more than 30 increases coordination and review costs.

What happens when one parallel agent fails its tests?

Failed units are flagged in the final summary with error details instead of being silently skipped. You can retry failed units individually while the successful units keep their opened pull requests.