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 agentmods add skills/uziii2208/mcp2agy/swarmnpx skills add uziii2208/mcp2agy --skill swarmgit clone --depth 1 https://github.com/uziii2208/mcp2agyWrote 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/uziii2208/mcp2agy/swarm)<a href="https://agentmods.dev/skills/uziii2208/mcp2agy/swarm"><img src="https://agentmods.dev/badge/skills/uziii2208/mcp2agy/swarm.svg" alt="Measured on agentmods" 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 | $0.00067 | $0.00644 |
| Opus 5 | $0.00034 | $0.00322 |
| Sonnet 5 | $0.00013 | $0.00129 |
| Haiku 4.5 | $0.00007 | $0.00064 |
Grade A, and why
mcp2agy-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 4d 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 — 63 lines — stays where its author put it; the contents beside it link to each section on GitHub.
/swarm — Multi-Agent Coordinated Offensive Swarm (v3.0.0)
0. Overview & Swarm Architecture
The Swarm orchestrates all specialist subagents in a synchronized, event-driven mesh:
┌───────────────────────────┐
│ Swarm Commander (/swarm)│
└─────────────┬─────────────┘
│
┌───────────────────┬──────────────────┼──────────────────┬───────────────────┐
▼ ▼ ▼ ▼ ▼
┌──────────────┐ ┌──────────────┐ ┌──────────────┐ ┌──────────────┐ ┌──────────────┐
│ Recon Agent │──►│Scanner Agent │──►│Verifier Agent│──►│Exploit/Fixer │──►│Reporter Agent│
│(OSINT/Ports) │ │ (AST & SAST) │ │ (PoC Rigor) │ │ (PoC & Diff) │ │(Advisory/Rep)│
└──────────────┘ └──────────────┘ └──────────────┘ └──────────────┘ └──────────────┘
1. Swarm Execution Workflow
- Reconnaissance Squad: Spawns passive & active discovery subagents to map external ports, web endpoints, and repositories.
- Audit Squad: Launches repository 0day scanner on discovered source code, producing
candidates.yaml. - Verification Squad: Spawns parallel Verifier subagents to prove reachability and create deterministic PoCs.
- Exploit & Remediation Squad: Develops weaponized harnesses for verified criticals and generates atomic patches (
fixes.diff). - Reporting Squad: Assembles publication-ready executive reports and GHSA advisory drafts.
2. Invocation Pattern
{
"Subagents": [
{
"TypeName": "mcp2agy-recon-agent",
"Role": "Swarm Reconnaissance Scout",
"Model": "flash",
"Workspace": "inherit",
"Prompt": "Perform full reconnaissance on <target>..."
},
{
"TypeName": "Hyperdope AI — Repository 0day Audit Scanner",
"Role": "Swarm 0day Scanner",
"Model": "inherit",
"Workspace": "inherit",
"Prompt": "Execute static 0day triage on discovered repositories..."
}
]
}
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.
- 4d ago First seen · 63 lines · 67 tokens per session scan A e46053668e9d
mcp2agy-swarm is a skill published in the GitHub repository uziii2208/mcp2agy (1 stars, last pushed 6d ago), licensed MIT. It adds 67 tokens to every session and 644 once invoked, about $0.0003 per session on Opus 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.
Other skills, from other repositories
systematic-debugging
Use when encountering any bug, test failure, or unexpected behavior, before proposing fixes.
local-ai-agents
Build local-first AI agents that run entirely on a developer workstation with Microsoft Foundry Local and Qwen function-calling models. Covers Small Language Models (SLMs), the OpenAI-compatible local endpoint, sandboxed local tools, local RAG with Chroma, local MCP servers, hybrid cloud/local routing, and the…
next-cache-components-adoption
Turn on Cache Components in a Next.js app and resolve the blocking routes it surfaces. Use when the user wants to enable, adopt, or migrate to Cache Components, flip the cacheComponents flag, work through a flood of blocking-prerender / instant validation errors, run the cache-components-instant-false codemod, or…
next-cache-components-optimizer
Drive a Next.js route to instant navigation by setting up an agentic loop, under Cache Components / PPR, on initial load (hard navigation) and client-side navigation (soft navigation). Encode the goal as a failing @next/playwright instant() e2e and work it to green, one verified route at a time; the shipped test then…
next-partial-prefetching-adoption
Turn on Partial Prefetching in a Next.js app and work through the insights it surfaces. Use when the user wants to enable or adopt Partial Prefetching, flip the partialPrefetching flag, opt routes in with export const prefetch = 'partial', audit Link prefetch={true} behavior, preserve existing prefetched UI with…
chronicle
Analyze Copilot session history for standup reports, usage tips, session search, and session reindexing. Use when the user asks for a standup, daily summary, usage tips, workflow recommendations, wants to search or find past sessions by keyword/file/PR, wants to reindex their session store, or asks about deleting…