dispatching-parallel-agents

dispatching-parallel-agents is a skill for Claude Code, Codex from xintaofei/codeg. It costs 26 tokens per session (1,363 once invoked), scanned A, a copy of dispatching-parallel-agents, Apache-2.0.

A workflow for giving separate, unrelated coding tasks to different AI agents at the same time, with each agent receiving only the information it needs.

In plain words
What is it for?
Use it to split unrelated test failures, bugs, or subsystem investigations into parallel tasks, then coordinate the results.
Why use it?
It avoids investigating independent bugs or failures one after another and keeps each investigation focused.

Skill for Claude CodeCodex

Written for no agent in particular: nothing here depends on one. Also seen: mentions subagents.

Good fit Use it to split unrelated test failures, bugs, or subsystem investigations into parallel tasks, then coordinate the results.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/xintaofei/codeg/dispatching-parallel-agents
About the project

Codeg is a collaborative workspace that brings multiple AI coding agents and their sessions into one searchable application. Developers use it to coordinate agents, delegate work, and review unattended coding tasks across desktop, server, Docker, and mobile clients. The catalogue entries are skills and instructions for workflows within Codeg.

xintaofei/codeg · 3,887 stars · on GitHub · docs.codeg.app

Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

Any agent
npx skills add xintaofei/codeg --skill dispatching-parallel-agents
Clone the repo
git clone --depth 1 https://github.com/xintaofei/codeg

Made for: Claude Code, Codex.

Wrote this? Show the measurements

A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.

agentmods badge for dispatching-parallel-agents

README.md
[![agentmods](https://agentmods.dev/badge/skills/xintaofei/codeg/dispatching-parallel-agents/github.svg)](https://agentmods.dev/skills/xintaofei/codeg/dispatching-parallel-agents)
Your own site
<a href="https://agentmods.dev/skills/xintaofei/codeg/dispatching-parallel-agents"><img src="https://agentmods.dev/badge/skills/xintaofei/codeg/dispatching-parallel-agents/github.svg" alt="Measured on agentmods" height="20"></a>

Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.

agentmods 80×15 button for dispatching-parallel-agents

Your own site · 80×15
<a href="https://agentmods.dev/skills/xintaofei/codeg/dispatching-parallel-agents"><img src="https://agentmods.dev/badge/skills/xintaofei/codeg/dispatching-parallel-agents.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 26 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,363 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
Origin 100% copy Near-identical to another mod in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5.1 $0.00026 $0.01363
Opus 5.5 $0.00010 $0.00545
Sonnet 5.5 $0.00005 $0.00273
Haiku 4.5 $0.00003 $0.00136

Measured 1mo ago against content hash 1968923066f3, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

Grade A, and why

dispatching-parallel-agents scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 1mo ago.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

Origin

This is a copy

100% identical to dispatching-parallel-agents — 0 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.

src-tauri/experts/skills/dispatching-parallel-agents/SKILL.md · 168 lines

How it starts

The opening of the file, as written. The whole thing — 168 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Dispatching Parallel Agents

Overview

You delegate tasks to specialized agents with isolated context. By precisely crafting their instructions and context, you ensure they stay focused and succeed at their task. They should never inherit your session's context or history — you construct exactly what they need. This also preserves your own context for coordination work.

When you have multiple unrelated failures (different test files, different subsystems, different bugs), investigating them sequentially wastes time. Each investigation is independent and can happen in parallel.

Core principle: Dispatch one agent per independent problem domain. Let them work concurrently.

When to Use

digraph when_to_use {
    "Multiple failures?" [shape=diamond];
    "Are they independent?" [shape=diamond];
    "Single agent investigates all" [shape=box];
    "One agent per problem domain" [shape=box];
    "Can they work in parallel?" [shape=diamond];
    "Sequential agents" [shape=box];
    "Parallel dispatch" [shape=box];

    "Multiple failures?" -> "Are they independent?" [label="yes"];
    "Are they independent?" -> "Single agent investigates all" [label="no - related"];
    "Are they independent?" -> "Can they work in parallel?" [label="yes"];
    "Can they work in parallel?" -> "Parallel dispatch" [label="yes"];
    "Can they work in parallel?" -> "Sequential agents" [label="no - shared state"];
}

Use when:

  • 3+ test files failing with different root causes
  • Multiple subsystems broken independently
  • Each problem can be understood without context from others
  • No shared state between investigations

Don't use when:

  • Failures are related (fix one might fix others)
  • Need to understand full system state
  • Agents would interfere with each other

The Pattern

1. Identify Independent Domains

Group failures by what's broken:

  • File A tests: Tool approval flow
  • File B tests: Batch completion behavior
  • File C tests: Abort functionality

Each domain is independent - fixing tool approval doesn't affect abort tests.

Read the full file on GitHub · 168 lines

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. 1mo ago First seen · 168 lines · 26 tokens per session scan A 1968923066f3

Subscribe to this mod's changes

dispatching-parallel-agents is a skill published in the GitHub repository xintaofei/codeg (3,887 stars, last pushed 6d ago), licensed Apache-2.0. It adds 26 tokens to every session and 1,363 once invoked, about $0.0001 per session on Opus 5.5. A static security scan graded it A with 0 findings. It is 100% identical to dispatching-parallel-agents, differing in 0 lines, and is treated as a copy.

Related

Other skills, from other repositories

terminal

Use Desktop Commander for terminal and command-line work, especially anything that needs a shell whose state persists across turns: Python/Node REPLs, database shells, dev servers and other long-running processes, SSH into remote machines, and Windows PowerShell. Also handles everyday terminal tasks — navigating…

wonderwhy-er/DesktopCommanderMCP · 209 tokens

knowledge-base

Create and maintain a Markdown knowledge base that any AI agent can read, search, and update. Use when the user wants to start a knowledge base, add or update notes, organize docs/notes for an agent or LLM to consume, build an index of notes, or run a cleanup/maintenance pass on an existing MD knowledge base. Triggers…

wonderwhy-er/DesktopCommanderMCP · 112 tokens

obsidian-vault

Organize Obsidian vaults with MOCs, wikilinks, frontmatter/properties, dashboards, orphan-note checks, and cleanup workflows. Use ONLY when the user explicitly refers to Obsidian — by naming "Obsidian", an Obsidian "vault", or an Obsidian-specific feature such as wikilinks ("[[ ]]"), the Dataview or Bases plugins, or…

wonderwhy-er/DesktopCommanderMCP · 171 tokens

desktop-commander-overview

Use for Desktop Commander MCP capabilities — persistent shells and REPLs, long-running processes, filesystem beyond the workspace, structured files (.xlsx, .docx, .pdf, images) and large local data files such as CSVs, ripgrep search at scale, SSH, or cross-turn state.

wonderwhy-er/DesktopCommanderMCP · 67 tokens

ai-tools-setup

Set up, connect, validate, and repair Claude Desktop and MCP servers using Desktop Commander — inspecting and fixing mcp.json / claudedesktopconfig.json, getting MCP servers to connect, and diagnosing local AI tooling. Use when a user wants to install, configure, connect, validate, or fix Claude Desktop, an MCP…

wonderwhy-er/DesktopCommanderMCP · 168 tokens

computer-health-check

Run a comprehensive, read-only health check on the user's computer and return a scored chat summary with prioritized, plain-English recommendations and safe cleanup suggestions. Use this whenever the user wants to check their computer's health, speed it up, free up / reclaim disk space, find what's eating CPU / memory…

wonderwhy-er/DesktopCommanderMCP · 209 tokens