New: 97,000+ skills indexed from GitHub repos with 100+ stars · every skill safety-checkedBrowse top skillsTop skills
Esc to closeBrowse all skills
Submit a skillBrowse skills
Submit a skillBrowse skills

Agent skill

Orchestrate Batch Refactor

by Dimillian in Dimillian/Skills

Plan and execute large refactor or rewrite efforts efficiently with parallel multi-agent analysis and implementation.

MITAuto-check passedAgent Workflows

Install Orchestrate Batch Refactor

skills CLI
$ npx skills add Dimillian/Skills --skill orchestrate-batch-refactor -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install Dimillian/Skills orchestrate-batch-refactor --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/Dimillian/Skills.git skills-src && mkdir -p .claude/skills && cp -r skills-src/orchestrate-batch-refactor .claude/skills/orchestrate-batch-refactor && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
orchestrate-batch-refactor
GitHub stars
4k
Token cost
~889 tokens
SKILL.md length
415 words
Files
4 (incl. references)
Skills in repo
12
Repo updated
First seen
Licence
MIT

At a glance

Plan and execute large refactor or rewrite efforts efficiently with parallel multi-agent analysis and implementation.

  • Works in 6 steps: Define scope and success criteria. → Run parallel analysis first. → Build one dependency-aware plan. → …
  • A user asks to refactor many files
  • SKILL.md covers Overview, Inputs, When to Use Parallelization and Core Workflow, plus 5 more sections
  • Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md

What it does

Orchestrate Batch Refactor is an agent skill from Dimillian/Skills. Plan and execute large refactor or rewrite efforts efficiently with parallel multi-agent analysis and implementation. Use when a user asks to refactor many files, split workstreams, analyze a target code area, and coordinate sub-agents with clear ownership and dependency-aware execution.

Its SKILL.md is about 890 tokens, which your agent loads only when the skill is triggered. The skill folder holds 5 other files, including reference files (for example `agents/openai.yaml`, `references/agent-prompt-templates.md` and `references/work-packet-template.md`).

It sits in Agent Workflows, covering Refactoring and Subagents. The licence is MIT.

When your agent uses it

  • A user asks to refactor many files
  • Split workstreams
  • Analyze a target code area
  • Coordinate sub-agents with clear ownership and dependency-aware execution

Example prompts

  • “/orchestrate-batch-refactor”

Workflow steps

6 steps, taken from the first numbered list in SKILL.md.

  1. Define scope and success criteria.
  2. Run parallel analysis first.
  3. Build one dependency-aware plan.
  4. Execute with worker agents.
  5. Integrate and verify.
  6. Report and close.

What it can do on your machine

Read from SKILL.md and the folder at commit 05ba982. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    No scripts in the folder and no shell commands in SKILL.md.

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    No URLs in SKILL.md.

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names no API keys, tokens, secrets or passwords.

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Orchestrate Batch Refactor loads about 889 tokens when it runs, and up to ~1.5k if it reads all its reference files. Until then it costs about 79 tokens; SKILL.md has 415 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~79
When it runs · the whole SKILL.md, loaded when a task matches
~889
With references · SKILL.md plus every file in references/, read only if the agent opens them
~1.5k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.

SKILL.md

The full file from Dimillian/Skills at commit 05ba982, republished under its MIT licence (© Dimillian). 415 words, ~889 tokens.

Download SKILL.mdSave it as .claude/skills/orchestrate-batch-refactor/SKILL.md (or your agent's skills folder). This skill also uses 3 other files; get the full folder from GitHub.
name
orchestrate-batch-refactor
description
Plan and execute large refactor or rewrite efforts efficiently with parallel multi-agent analysis and implementation. Use when a user asks to refactor many files, split workstreams, analyze a target code area, and coordinate sub-agents with clear ownership and dependency-aware execution.

Orchestrate Batch Refactor

Overview

Use this skill to run high-throughput refactors safely. Analyze scope in parallel, synthesize a single plan, then execute independent work packets with sub-agents.

Inputs

  • Repo path and target scope (paths, modules, or feature area)
  • Goal type: refactor, rewrite, or hybrid
  • Constraints: behavior parity, API stability, deadlines, test requirements

When to Use Parallelization

  • Use this skill for medium/large scope touching many files or subsystems.
  • Skip multi-agent execution for tiny edits or highly coupled single-file work.

Core Workflow

  1. Define scope and success criteria.
    • List target paths/modules and non-goals.
    • State behavior constraints (for example: preserve external behavior).
  2. Run parallel analysis first.
    • Split target scope into analysis lanes.
    • Spawn explorer sub-agents in parallel to analyze each lane.
    • Ask each agent for: intent map, coupling risks, candidate work packets, required validations.
  3. Build one dependency-aware plan.
    • Merge explorer output into a single work graph.
    • Create work packets with clear file ownership and validation commands.
    • Sequence packets by dependency level; run only independent packets in parallel.
  4. Execute with worker agents.
    • Spawn one worker per independent packet.
    • Assign explicit ownership (files/responsibility).
    • Instruct every worker that they are not alone in the codebase and must ignore unrelated edits.
  5. Integrate and verify.
    • Review packet outputs, resolve overlaps, and run validation gates.
    • Run targeted tests per packet, then broader suite for integrated scope.
  6. Report and close.
    • Summarize packet outcomes, key refactors, conflicts resolved, and residual risks.
Show full SKILL.md (180 more words)Show less

Work Packet Rules

  • One owner per file per execution wave.
  • No parallel edits on overlapping file sets.
  • Keep packet goals narrow and measurable.
  • Include explicit done criteria and required checks.
  • Prefer behavior-preserving refactors unless user explicitly requests behavior change.

Planning Contract

Every packet must include:

  1. Packet ID and objective.
  2. Owned files.
  3. Dependencies (none or packet IDs).
  4. Risks and invariants to preserve.
  5. Required checks.
  6. Integration notes for main thread.

Use references/work-packet-template.md for the exact shape.

Agent Prompting Contract

  • Use the prompt templates in references/agent-prompt-templates.md.
  • Explorer prompts focus on analysis and decomposition.
  • Worker prompts focus on implementation and validation with strict ownership boundaries.

Safety Guardrails

  • Do not start worker execution before plan synthesis is complete.
  • Do not parallelize across unresolved dependencies.
  • Do not claim completion if any required packet check fails.
  • Stop and re-plan when packet boundaries cause repeated merge conflicts.

Validation Strategy

Run in this order:

  1. Packet-level checks (fast and scoped).
  2. Cross-packet integration checks.
  3. Full project safety checks when scope is broad.

Prefer fast feedback loops, but never skip required behavior checks.

© Dimillian, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

SKILL.md and 3 other files (references) in orchestrate-batch-refactor of Dimillian/Skills.

  • SKILL.md
  • agents/openai.yaml
  • references/agent-prompt-templates.md
  • references/work-packet-template.md

Open the folder on GitHubat commit 05ba982

Compare with similar skills

Orchestrate Batch Refactor next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.

Orchestrate Batch Refactor compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
Orchestrate Batch Refactor this skillDimillian/Skills4k—~889Automated safety check: PassMIT
Antigravity Agentsmarkfulton/claude-antigravity-agents130—~2.1kAutomated safety check: PassMIT
Subagent Coordinatorflyxl/datazen114—~908Automated safety check: PassGPL-3.0
Batch Orchestrationrohitg00/pro-workflow2.9k—~1.2kAutomated safety check: PassNone
Codex CLIkortix-ai/suna20k—~1.6kAutomated safety check: PassCustom licence
Batch Refactor With Sub Agentsr3bl-org/r3bl-open-core485—~816Automated safety check: PassApache-2.0

Similar skills

  • Antigravity Agents

    markfulton/claude-antigravity-agents

    Delegate coding, code review, analysis, and research jobs to Google Antigravity CLI (agy) sub-agents that run alongside your own work.

    130 GitHub stars~2.1k tokensUpdated 2 mo ago
    Agent WorkflowsAuto-check passed

  • Subagent Coordinator

    flyxl/datazen

    Orchestrate multi-track parallel feature development with subagents and git worktrees.

    114 GitHub stars~908 tokensUpdated 7 days ago
    Agent WorkflowsAuto-check passed

  • Batch Orchestration

    rohitg00/pro-workflow

    Decompose large-scale changes into independent units and spawn parallel agents in isolated worktrees.

    2.9k GitHub stars~1.2k tokensUpdated 8 days ago
    Agent WorkflowsAuto-check passed

  • Codex CLI

    kortix-ai/suna

    Drive OpenAI's Codex CLI (codex exec) as a non-interactive coding sub-agent from inside Claude Code.

    20k GitHub stars~1.6k tokensUpdated today
    Agent WorkflowsAuto-check passed

  • Batch Refactor With Sub Agents

    r3bl-org/r3bl-open-core

    Use a sub-agent (like generalist) to perform repetitive code transformations across multiple files in a single turn.

    485 GitHub stars~816 tokensUpdated yesterday
    Agent WorkflowsAuto-check passed

  • Iterative Refinement

    sammcj/agentic-coding

    Disciplined, measurable iteration for a substantial refinement or investigation: loop against verifiable pass/fail conditions, fan work out to subagents, and keep the main context lean.

    162 GitHub stars~3.2k tokensUpdated yesterday
    Agent WorkflowsAuto-check passed

More from Dimillian/Skills

All 12 skills in this repo

  • macOS Spm App Packaging

    Dimillian/Skills

    Scaffold, build, and package SwiftPM-based macOS apps without an Xcode project.

    4k GitHub starsUsed in 5 repos~1.2k tokens
    Auto-check passed

  • React Component Performance

    Dimillian/Skills

    Analyze and optimize React component performance issues (slow renders, re-render thrash, laggy lists, expensive computations).

    4k GitHub starsUsed in 5 repos~1.2k tokens
    Auto-check passed

  • Swiftui View Refactor

    Dimillian/Skills

    Refactor and review SwiftUI view files with strong defaults for small dedicated subviews, MV-over-MVVM data flow, stable view trees, explicit dependency injection, and correct Observation usage.

    4k GitHub starsUsed in 5 repos~2k tokens
    Auto-check passed

  • Swiftui UI Patterns

    Dimillian/Skills

    Best practices and example-driven guidance for building SwiftUI views and components, including navigation hierarchies, custom view modifiers, and responsive layouts with stacks and grids.

    4k GitHub starsUsed in 5 repos~1.9k tokens
    Auto-check passed

  • Swift Concurrency Expert

    Dimillian/Skills

    Swift Concurrency review and remediation for Swift 6.2+. An agent skill from Dimillian/Skills.

    4k GitHub stars~1.1k tokensUpdated 6 mo ago
    Auto-check passed

  • GitHub

    Dimillian/Skills

    Interact with GitHub using the gh CLI. An agent skill from Dimillian/Skills.

    4k GitHub stars~480 tokensUpdated 6 mo ago
    Auto-check passed

Categories

Questions about Orchestrate Batch Refactor

What does Orchestrate Batch Refactor do?

Plan and execute large refactor or rewrite efforts efficiently with parallel multi-agent analysis and implementation. Orchestrate Batch Refactor is an agent skill from Dimillian/Skills. Plan and execute large refactor or rewrite efforts efficiently with parallel multi-agent analysis and implementation.

When should I use Orchestrate Batch Refactor?

Orchestrate Batch Refactor fits situations like: A user asks to refactor many files; split workstreams; analyze a target code area; coordinate sub-agents with clear ownership and dependency-aware execution.

How do I install Orchestrate Batch Refactor in Claude Code?

Run `npx skills add Dimillian/Skills --skill orchestrate-batch-refactor -a claude-code`. Or copy the skill folder (orchestrate-batch-refactor in Dimillian/Skills) into .claude/skills/orchestrate-batch-refactor in your project. Claude Code loads it when a task matches its description.

How do I install Orchestrate Batch Refactor in Codex?

Run `npx skills add Dimillian/Skills --skill orchestrate-batch-refactor -a codex`. Or copy the skill folder (orchestrate-batch-refactor in Dimillian/Skills) into .agents/skills/orchestrate-batch-refactor in your project. Codex loads it when a task matches its description.

Can I use Orchestrate Batch Refactor in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add Dimillian/Skills --skill orchestrate-batch-refactor -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/orchestrate-batch-refactor, .gemini/skills/orchestrate-batch-refactor, .github/skills/orchestrate-batch-refactor and .opencode/skills/orchestrate-batch-refactor in your project.

What does Orchestrate Batch Refactor need to run?

SKILL.md names no scripts, command-line tools or credentials: Orchestrate Batch Refactor is instructions for the agent only.

Does Orchestrate Batch Refactor access the network?

SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.

Is Orchestrate Batch Refactor safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.

What licence does Orchestrate Batch Refactor use?

Orchestrate Batch Refactor is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Orchestrate Batch Refactor use?

About 889 tokens (SKILL.md is roughly 3.6k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full. Its references folder adds about 590 tokens, read only when the agent opens those files.

What are the alternatives to Orchestrate Batch Refactor?

Skills that share tags, products or a category with Orchestrate Batch Refactor: Antigravity Agents (markfulton/claude-antigravity-agents, 130 stars), Subagent Coordinator (flyxl/datazen, 114 stars), Batch Orchestration (rohitg00/pro-workflow, 2.9k stars) and Codex CLI (kortix-ai/suna, 20k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Orchestrate Batch Refactor?

Dimillian (a GitHub user) maintains it in Dimillian/Skills, which has 3,984 GitHub stars. The repository holds 12 skills in this directory. The repository was last updated on March 29, 2026.

Source: Dimillian/Skills on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.