dispatch

作者 bassimeledath已验证

A Claude Code skill that 10x's your effective context window by dispatching tasks to background AI workers.

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2026/8/23
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⚠️ 第三方软件声明

本 Skill 为第三方开源软件,独立托管于 GitHub。SkillTip 仅为信息目录,不控制或维护底层仓库。所显示的安全检查为自动化且范围有限,安装前请自行审查源码。

阅读服务条款

安装

添加到你的 Claude Code skills 目录:

# Add to your Claude Code skills
git clone https://github.com/bassimeledath/dispatch

快速入门

使用 dispatch 等 Skills 的指南。

安全报告

已验证

上次扫描:—

{
  "status": "PASSED",
  "issues": []
}

README.md

/dispatch Dispatch logo

Dispatch 10x's Claude Code's effective context window size. Instead of filling your session with implementation, /dispatch turns it into a lightweight orchestrator — work fans out to background agents, each with their own full context window.

Before: a single session where context fills up fast doing tasks sequentially, with the user overwhelmed tracking everything. After: dispatch keeps your main session lean while workers execute in parallel with their own fresh contexts, and the dispatcher carries the cognitive load.

Without dispatch: You ask Claude to review code, refactor a module, write tests, and update docs. Each task fills the context window. By task 3, Claude is losing track. By task 5, you're starting a new session.

With dispatch: You describe all 5 tasks. Workers execute in parallel with fresh contexts. Your main session stays lean. Questions surface to you when needed — no polling, no context lost.

/dispatch use sonnet to find better design patterns for the auth module

Why dispatch

Your session stays lean

Dispatch inverts the usual model: the main session becomes a mediator, not the thinker. It writes a checklist and hands it off. The actual implementation — reading code, reasoning about edge cases, writing tests — happens in fresh worker contexts that each get their own full window. Your main session's context is preserved for orchestration.

The dispatcher carries the cognitive load

With claude --background, multiple terminals, or fire-and-forget agent runners — you are the orchestrator. You track what's running, check on progress, notice failures, and context-switch between outputs.

With dispatch, the AI dispatcher tracks all workers, surfaces questions, reports completions, handles errors, and offers recovery. Your job reduces to: (a) describe what you want, (b) answer questions when asked.

Workers ask questions back

When a /dispatch worker gets stuck, it doesn't silently fail or hallucinate. It asks a clarifying question — the dispatcher surfaces it to you, you answer, and the worker continues without losing context. No restart, no re-explaining, no lost work.

Worker is asking: "requirements.txt doesn't exist. What feature should I implement?"
> Add a /health endpoint that returns JSON with uptime and version.

Answer sent. Worker is continuing.

Non-blocking — you never wait

The moment a worker is dispatched, your session is immediately free. Dispatch another task. Ask a question. Write code. Workers run in parallel and results arrive as they complete.

Any model, one interface

Mix models per task. Claude for deep reasoning, GPT for broad generation, Gemini for speed. Reference any model by name — if it's not in your config, /dispatch auto-discovers and adds it. If multiple models are named in one prompt, dispatch uses the last one mentioned. If no model is specified, dispatch confirms your default before proceeding.

/dispatch use opus to review this PR for edge cases
/dispatch use gemini to refactor the config parser — it's getting unwieldy

Requires Claude Code as your host session. Dispatch is a skill that runs inside Claude Code — the host plans tasks and spawns workers. Other CLIs like Cursor and Codex work as workers only (background agents that execute subtasks).

Install

npx skills add bassimeledath/dispatch -g     # user-level (all projects)
npx skills add bassimeledath/dispatch        # project-level (team-shared)

How it works

  1. You run /dispatch task description
  2. A checklist plan is created — the only context your main session needs
  3. A background worker picks it up in a fresh, full context window and checks off items as it goes
  4. If the worker has a question, it asks — you answer — it continues (no context lost in either direction)
  5. You get results when it's done, or ask for status anytime — your main session is still lean

Complex example

Example — pre-launch sweep for a fullstack SaaS app:

/dispatch we launch Thursday, need a full pre-launch sweep:

1) security audit the auth flow (JWT, sessions, password reset) and the
   stripe payment integration. use opus, do it in a worktree

2) performance - load test the top 5 API endpoints, find N+1 queries,
   check db indexes on users/orders/products tables. sonnet in a worktree

3) frontend audit - accessibility (WCAG 2.1 AA), bundle size, flag any
   components missing error boundaries. dispatch sonnet

4) generate OpenAPI specs for every endpoint that's missing one. use gemini

5) error handling audit - find uncaught exceptions, missing try/catch,
   inconsistent error response formats across all API routes. sonnet, worktree

ask me if anything is unclear. security is highest priority - flag
anything critical immediately

Dispatch reads the prompt, creates 5 plans, and fans out:

All 5 workers dispatched with their monitors. Here's the summary:

Security (worktree):
  ● security-audit — Opus 4-6 (worktree): Full auth + payment security review

Performance (worktree):
  ● perf-audit — Sonnet 4-6 (worktree): API load testing + DB index review

Frontend (single worker):
  ● frontend-audit — Sonnet 4-6: Accessibility, bundle size, error boundaries

Docs (single worker):
  ● api-docs — Gemini 2.5 Flash: Generate missing OpenAPI specs

Error handling (worktree):
  ● error-handling — Sonnet 4-6 (worktree): Uncaught exceptions + error format audit

All running in background. Five workers, three models, three worktrees —
your session wrote five checklists and is idle. Dispatch more work or say
"status" anytime.

Best practice: warm up at session start

Run /dispatch with no arguments at the beginning of a session to pre-load your config:

/dispatch

This reads ~/.dispatch/config.yaml into the dispatcher's context so subsequent dispatches are faster and don't need confirmation prompts. It's a good habit to add as a Claude Code memory so you remember to do it each session:

"Run /dispatch at the start of each session to warm up the config."

Setup

On first run, /dispatch auto-detects your CLIs (claude, agent, codex), discovers available models, and generates ~/.dispatch/config.yaml. No manual config needed.

Configuration

Three sections in ~/.dispatch/config.yaml:

Backends — CLI commands for each provider:

backends:
  claude:
    command: >
      env -u CLAUDE_CODE_ENTRYPOINT -u CLAUDECODE
      claude -p --dangerously-skip-permissions
  cursor:
    command: >
      agent -p --force --workspace "$(pwd)"
  codex:
    command: >
      codex exec --full-auto -C "$(pwd)"

Models — one line each, mapped to a backend:

models:
  opus:            { backend: claude }
  sonnet:          { backend: claude }
  gpt-5.3-codex:  { backend: codex }
  gemini-3.1-pro:  { backend: cursor }

Aliases — named shortcuts with optional role prompts:

aliases:
  security-reviewer:
    model: opus
    prompt: >
      You are a security-focused reviewer. Prioritize OWASP Top 10.

Prerequisites

Host (required):

Workers (optional — for multi-model dispatch):

Updating

Skills CLI (recommended):

npx skills update

This updates all installed skills to their latest versions. Run npx skills check first to see what's changed.

Symlinked to a local clone? If your .claude/skills/dispatch is a symlink to a local git checkout, just pull:

cd /path/to/your/dispatch && git pull

Changes are picked up immediately — Claude Code hot-reloads skills from disk.

Architecture

The dispatcher reads your config, creates a checklist plan, then spawns a background worker and monitor. The worker executes each item and checks it off. If it needs clarification, it writes a question to the IPC directory — the monitor detects it and notifies the dispatcher, which surfaces it to you and relays your answer back, all without the worker losing context.

Sequence diagram showing the dispatch flow: user triggers dispatch, dispatcher creates plan and spawns worker + monitor, worker executes checklist items, IPC handles questions and answers, monitor detects completion and notifies dispatcher.

License

MIT

常见问题

What is dispatch?

dispatch is an open-source ai agents skill for AI coding assistants such as Claude Code, Codex CLI, and ChatGPT, built by bassimeledath. A Claude Code skill that 10x's your effective context window by dispatching tasks to background AI workers. It has 411 GitHub stars.

Is dispatch safe to use?

Yes. dispatch passed SkillsLLM's automated security scan — a dependency vulnerability audit plus prompt-injection heuristics — with no high-severity issues. You can read the full report in the Security Report section on this page.

How do I install dispatch?

Clone the repository with "git clone https://github.com/bassimeledath/dispatch" and add it to your Claude Code skills directory (see the Installation section above).

Are there alternatives to dispatch?

Yes. SkillsLLM lists many other AI Agents skills you can browse and compare side by side. Open the AI Agents category from the badge at the top of this page, or use the Related Skills and comparison links further down to weigh dispatch against similar tools.

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