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Built for the Claude Code community with Claude Code by @mertduzgun

Independent project, not affiliated with Anthropic

Huashu Agent Swarm

alchaincyf/huashu-skills
398 installs888 stars
Summary

This spins up multiple Claude instances that work in parallel on the same codebase, coordinating through git alone with no master orchestrator. Each agent claims tasks via lock files, commits independently, and pulls others' work in an infinite loop. Inspired by Nicholas Carlini's compiler project. You get a tmux session with 8 agents by default, a web dashboard to watch their progress, and git worktrees to keep them isolated without cloning repeatedly. It's genuinely experimental infrastructure for tackling large projects when you're willing to babysit the chaos. Watch for API rate limits and merge conflicts, but the self-organizing approach through git is legitimately interesting if you want to see what emerges from parallel AI collaboration.

Install to Claude Code

npx -y skills add alchaincyf/huashu-skills --skill huashu-agent-swarm --agent claude-code

Installs into .claude/skills of the current project.

CodeRabbit
CodeRabbit
AI writes the code. CodeRabbit catches the slop.
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Keep your Mac awake
Keep your Mac awake
Keep your Mac awake while Claude Code and 40+ AI agents run. Sleeps when they're idle.
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Context.devContext.dev
Context.dev
Integrate web data into your AI product. One API to scrape website & brand data.
Get API Key Now →
Make your agent a DeFi expert
Make your agent a DeFi expert
Agent, run crypto. Access onchain data & trade routes via 1inch.
Install now →
Make money from your Skills
Make money from your Skills
On Capafy, your Skill runs online 24/7 as an agent product, and you get paid every time someone uses it.
Start earning →
AppSignal
AppSignal
Monitor with ease. Code with confidence.
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CodeRabbit
CodeRabbit
AI writes the code. CodeRabbit catches the slop.
Try For Free →
Keep your Mac awake
Keep your Mac awake
Keep your Mac awake while Claude Code and 40+ AI agents run. Sleeps when they're idle.
One time payment $9 →
Context.devContext.dev
Context.dev
Integrate web data into your AI product. One API to scrape website & brand data.
Get API Key Now →
Make your agent a DeFi expert
Make your agent a DeFi expert
Agent, run crypto. Access onchain data & trade routes via 1inch.
Install now →
Make money from your Skills
Make money from your Skills
On Capafy, your Skill runs online 24/7 as an agent product, and you get paid every time someone uses it.
Start earning →
AppSignal
AppSignal
Monitor with ease. Code with confidence.
Start Free Trial →
Files
SKILL.mdView on GitHub

Infinite Agent Loop - 无限Agent蜂群模式

受Nicholas Carlini用16个Claude实例自主构建C编译器的启发。 没有master agent,纯git自组织,每个agent独立认领任务、写代码、推送。

触发条件

当用户提到「蜂群模式」「多agent并行」「infinite loop」「agent swarm」「启动蜂群」时使用此技能。

前置要求

  • tmux(brew install tmux)
  • claude CLI(已安装)
  • git 仓库(已有或新建)

使用流程

Step 1: 描述项目

用户告诉我:

  • 项目目录路径(必须是git仓库)
  • 项目目标和总体描述
  • 初始任务列表(或让agent自行拆解)
  • agent数量(默认8个)
  • 代码规范和测试命令

Step 2: 初始化项目

bash SKILL_DIR/scripts/setup_project.sh <项目目录>

这会在项目中创建:

  • AGENT_PROMPT.md - 从模板生成,需要我根据用户需求定制
  • TASKS.md - 初始任务清单
  • current_tasks/ - 任务认领目录
  • agent_logs/ - 日志目录

然后我根据 references/agent-prompt-template.md 定制 AGENT_PROMPT.md,填入项目具体信息。

Step 3: 启动蜂群

bash SKILL_DIR/scripts/start_swarm.sh <agent数量> <项目目录>

这会:

  1. 为每个agent创建 git worktree(共享.git对象库,不浪费磁盘)
  2. 创建 tmux session,每个pane一个agent
  3. 每个agent进入无限循环:pull → 认领任务 → 执行 → push → 下一个

Step 4: 打开观测台

python3 SKILL_DIR/scripts/dashboard.py <项目目录> 8420

浏览器打开 http://localhost:8420,可以:

  • 实时查看所有agent状态、git log、任务进度
  • 查看每个agent的最新日志
  • 输入框直接发送指令给agent(写入HUMAN_INPUT.md)
  • 一键停止所有agent

也可以用命令行监控:

# 终端状态
bash SKILL_DIR/scripts/status.sh <项目目录>

# 发送指令
bash SKILL_DIR/scripts/send_input.sh <项目目录> "你的指令"

# 直接进入tmux观察
tmux attach -t swarm-<项目名>

Step 5: 停止

bash SKILL_DIR/scripts/stop_swarm.sh <项目目录>

自动停止所有agent + 合并分支 + 清理worktrees。

核心机制

Git自组织协调

  • 每个agent通过 current_tasks/*.lock 文件认领任务
  • 通过 TASKS.md 了解全局进度
  • 通过 git log 了解其他agent的工作
  • 冲突由agent自行解决

Git Worktree隔离

  • 不用多份clone,用 git worktree 实现隔离
  • 所有worktree共享同一个 .git 对象库
  • 每个agent在自己的worktree独立工作

无限循环

  • 每个agent完成一个session后自动开始下一个
  • 通过 git pull 获取其他agent的最新成果
  • 通过 sleep 间隔避免API限流

关键配置

参数默认值说明
agent数量8可在启动时指定
sleep间隔5秒agent_loop.sh中可调
模型claude-opus-4-6agent_loop.sh中可调

风险和应对

风险应对
API限流sleep间隔 + 可调agent数量
合并冲突AGENT_PROMPT指导小粒度commit
死循环无用功日志监控 + 停止条件
磁盘空间stop_swarm.sh自动清理
成本失控可在AGENT_PROMPT中限制session数

花叔出品 | AI Native Coder · 独立开发者 公众号「花叔」| 30万+粉丝 | AI工具与效率提升 代表作:小猫补光灯(AppStore付费榜Top1)·《一本书玩转DeepSeek》

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CodeRabbit
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AI writes the code. CodeRabbit catches the slop.
Try For Free →
Keep your Mac awake
Keep your Mac awake
Keep your Mac awake while Claude Code and 40+ AI agents run. Sleeps when they're idle.
One time payment $9 →
Context.devContext.dev
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Integrate web data into your AI product. One API to scrape website & brand data.
Get API Key Now →
Make your agent a DeFi expert
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Agent, run crypto. Access onchain data & trade routes via 1inch.
Install now →
Make money from your Skills
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On Capafy, your Skill runs online 24/7 as an agent product, and you get paid every time someone uses it.
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Categories
AI & Agent Building
First SeenJun 3, 2026
View on GitHub

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