Borrowing it
Nothing to install: this file belongs to AlexFischman/mcp-skill-creator-agency. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/AlexFischman/mcp-skill-creator-agency/main/CLAUDE.mdgit clone --depth 1 https://github.com/AlexFischman/mcp-skill-creator-agencyWrote 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/instructions/alexfischman/mcp-skill-creator-agency/claude-md)<a href="https://agentmods.dev/instructions/alexfischman/mcp-skill-creator-agency/claude-md"><img src="https://agentmods.dev/badge/instructions/alexfischman/mcp-skill-creator-agency/claude-md/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/instructions/alexfischman/mcp-skill-creator-agency/claude-md"><img src="https://agentmods.dev/badge/instructions/alexfischman/mcp-skill-creator-agency/claude-md.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 | $0.01709 | $0.01709 |
| Opus 5 | $0.00855 | $0.00855 |
| Sonnet 5 | $0.00342 | $0.00342 |
| Haiku 4.5 | $0.00171 | $0.00171 |
Grade D, and why
mcp-skill-creator-agency CLAUDE.md scanned grade D with 2 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 11d 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.
Asks the agent to reveal its instructionsmediumSystem prompt leakage
Directions to print, repeat or translate the system prompt extract configuration the operator did not intend to expose.
- OPENAI_API_KEY (required) - Show instructions how to get it Harvests environment variableshighData exfiltration
Enumerating or grepping the environment for keys collects credentials unrelated to what the mod says it does.
6. **Collect API keys BEFORE development** (with instructions from api-researcher): This is a copy
92% identical to OpenSwarm CLAUDE.md — 24 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.
How it starts
The opening of the file, as written. The whole thing — 173 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Agency Builder
You are a specialized agent that coordinates specialized sub-agents to build production-ready Agency Swarm v1.0.0 agencies.
Background
Agency Swarm is an open-source framework designed for orchestrating and managing multiple AI agents, built upon the OpenAI Assistants API. Its primary purpose is to facilitate the creation of "AI agencies" or "swarms" where multiple AI agents with distinct roles and capabilities can collaborate to automate complex workflows and tasks.
A Note on Communication Flow Patterns
In Agency Swarm, communication flows are uniform, meaning you can define them in any way you want. Below are some examples:
Orchestrator-Workers (Most Common)
agency = Agency(
ceo, # Entry point for user communication
communication_flows=[
(ceo, worker1),
(ceo, worker2),
(ceo, worker3),
],
shared_instructions="agency_manifesto.md",
)
Sequential Pipeline (handoffs)
from agency_swarm.tools.send_message import SendMessageHandoff
# Each agent needs SendMessageHandoff as their send_message_tool_class
agent1 = Agent(..., send_message_tool_class=SendMessageHandoff)
agent2 = Agent(..., send_message_tool_class=SendMessageHandoff)
agency = Agency(
agent1,
communication_flows=[
(agent1, agent2),
(agent2, agent3),
],
shared_instructions="agency_manifesto.md",
)
Collaborative Network
agency = Agency(
ceo,
communication_flows=[
(ceo, developer),
(ceo, designer),
(developer, designer),
],
shared_instructions="agency_manifesto.md",
)
See documentation for more details.
Available Sub-Agents
- api-researcher: Researches MCP servers and APIs, saves docs locally
- prd-creator: Transforms concepts into PRDs using saved API docs
- agent-creator: Creates complete agent modules with folder structure
- tools-creator: Implements tools prioritizing MCP servers over custom APIs
- instructions-writer: Write optimized instructions using prompt engineering best practices
- qa-tester: Test agents with actual interactions and tool validation
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.
- 11d ago First seen · 173 lines · 1,709 tokens per session scan D 93513aaf4835
mcp-skill-creator-agency CLAUDE.md is an instructions file published in the GitHub repository AlexFischman/mcp-skill-creator-agency (2 stars, last pushed 9mo ago), licensed MIT. It adds 1,709 tokens to every session, about $0.0085 per session on Opus 5. A static security scan graded it D with 2 findings (asks the agent to reveal its instructions, harvests environment variables). It is 92% identical to OpenSwarm CLAUDE.md, differing in 24 lines, and is treated as a copy.
Other instructions, from other repositories
next.js AGENTS.md
AGENTS.md instructions for vercel/next.js, covering next.js development guide, codebase structure, monorepo overview, core package: packages/next and other important packages.
codex AGENTS.md
AGENTS.md instructions for openai/codex, covering rust/codex-rs, the codex-core crate, code review rules, crate api surface and model visible context.
vscode buildNext.instructions.md
Working notes and architecture documentation for the new esbuild-based build system in build/next. Use when making changes to the new build pipeline (transpile/bundle commands, NLS plugin, source-map handling, resource copying, or self-hosting watch tasks).
spec-kit AGENTS.md
AGENTS.md instructions for github/spec-kit, covering agents.md, about spec kit and specify, quickstart — add a new integration in 5 steps, integration architecture and integrationmanifest — file tracking.
langchain AGENTS.md
AGENTS.md instructions for langchain-ai/langchain, covering global development guidelines for the langchain monorepo, corridor security analysis, project architecture and context, monorepo structure and development tools & commands.
vscode oss-third-party-notices.instructions.md
Instructions for microsoft/vscode, covering vs code oss third-party-notices pipeline, architecture, pipeline flow in ci, applying the notice (cutover) and fallback chain (never fail the build).