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.
npx skills add Biraj2004/huashu-skills-english --skill huashu-agent-swarm-engit clone --depth 1 https://github.com/Biraj2004/huashu-skills-englishWrote 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.
[](https://agentmods.dev/skills/biraj2004/huashu-skills-english/huashu-agent-swarm-en)<a href="https://agentmods.dev/skills/biraj2004/huashu-skills-english/huashu-agent-swarm-en"><img src="https://agentmods.dev/badge/skills/biraj2004/huashu-skills-english/huashu-agent-swarm-en/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.
<a href="https://agentmods.dev/skills/biraj2004/huashu-skills-english/huashu-agent-swarm-en"><img src="https://agentmods.dev/badge/skills/biraj2004/huashu-skills-english/huashu-agent-swarm-en.svg" alt="Reviewed on agentmods" width="80" height="20"></a>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.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00049 | $0.03554 |
| Opus 5.5 | $0.00020 | $0.01422 |
| Sonnet 5.5 | $0.00010 | $0.00711 |
| Haiku 4.5 | $0.00005 | $0.00355 |
Grade A, and why
huashu-agent-swarm 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.
How it starts
The opening of the file, as written. The whole thing — 472 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Infinite Agent Loop — Multi-Agent Swarm Mode
Inspired by Nicholas Carlini's experiment of using 16 Claude instances to autonomously build a C compiler. No master agent. Pure git self-organisation. Each agent independently claims tasks, writes code, and pushes.
Trigger Conditions
Use this skill when the user mentions "swarm mode", "multi-agent parallel", "infinite loop", "agent swarm", or "launch swarm".
Prerequisites
- tmux (
brew install tmux) - Claude CLI (already installed)
- A git repository (existing or new)
Usage Workflow
Step 1: Describe the Project
The user tells me:
- Project directory path (must be a git repository)
- Project goal and overall description
- Initial task list (or let the agents break it down themselves)
- Number of agents (default: 8)
- Code standards and test commands
Step 2: Initialise the Project
bash SKILL_DIR/scripts/setup_project.sh <project-directory>
This creates the following inside the project:
AGENT_PROMPT.md— Generated from a template; I customise it based on user requirementsTASKS.md— Initial task checklistcurrent_tasks/— Task claim directoryagent_logs/— Logs directory
I then customise AGENT_PROMPT.md using references/agent-prompt-template.md, filling in project-specific details.
Step 3: Launch the Swarm
bash SKILL_DIR/scripts/start_swarm.sh <number-of-agents> <project-directory>
This will:
- Create a git worktree for each agent (shared
.gitobject store — no disk waste) - Create a tmux session with one pane per agent
- Each agent enters an infinite loop: pull → claim task → execute → push → next task
Step 4: Open the Dashboard
python3 SKILL_DIR/scripts/dashboard.py <project-directory> 8420
Open http://localhost:8420 in your browser to:
- View all agent statuses, git log, and task progress in real time
- View the latest logs for each agent
- Send instructions directly to agents via the input box (written to HUMAN_INPUT.md)
- Stop all agents with one click
What ships with it
9 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
- references/agent-prompt-template.md 4.1 KB
- references/carlini-lessons.md 3.3 KB
- scripts/agent_loop.sh 2.8 KB runs code
- scripts/dashboard.py 21 KB runs code
- scripts/send_input.sh 1.0 KB runs code
- scripts/setup_project.sh 2.7 KB runs code
- scripts/start_swarm.sh 3.3 KB runs code
- scripts/status.sh 2.7 KB runs code
- scripts/stop_swarm.sh 2.3 KB runs code
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.
- 1mo ago First seen · 472 lines · 49 tokens per session scan A e821fac09b65
huashu-agent-swarm is a skill published in the GitHub repository Biraj2004/huashu-skills-english (3 stars, last pushed 1mo ago), licensed MIT. It adds 49 tokens to every session and 3,554 once invoked, about $0.0002 per session on Opus 5.5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.
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