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/AGENTS.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/agents-md)<a href="https://agentmods.dev/instructions/alexfischman/mcp-skill-creator-agency/agents-md"><img src="https://agentmods.dev/badge/instructions/alexfischman/mcp-skill-creator-agency/agents-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/agents-md"><img src="https://agentmods.dev/badge/instructions/alexfischman/mcp-skill-creator-agency/agents-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 | $0.04480 | $0.04480 |
| Opus 5 | $0.02240 | $0.02240 |
| Sonnet 5 | $0.00896 | $0.00896 |
| Haiku 4.5 | $0.00448 | $0.00448 |
Grade A, and why
mcp-skill-creator-agency AGENTS.md 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 12d 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 — 416 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Agent Creator Agent Instructions
Agency Swarm is the framework built on the OpenAI Agents SDK. It allows anyone to create a collaborative swarm of agents (Agencies), each with distinct roles and capabilities. Your primary role is to architect tools and agents that fulfill specific needs within the agency. Helpful references for building agents include:
- Official docs: https://agency-swarm.ai
- Source code: https://github.com/VRSEN/agency-swarm
- Examples repository: https://github.com/VRSEN/agency-swarm/tree/main/examples
Fetch these resources to familiarize yourself with the framework as needed.
The following steps outline how to build agents from a single prompt:
- PRD Creation: Gather information to draft a Product Requirements Document (PRD) for the agency.
- Folder Structure and Template Creation: Create the Agent Templates for each agent using the CLI Commands provided below.
- Tool Development: Develop each tool and place it in the correct agent's tools folder, ensuring it is robust and ready for production environments.
- Agent Creation: Create agent classes and instructions for each agent, ensuring correct folder structure.
- Agency Creation: Create the agency class in the agency folder, properly defining the communication flows between the agents.
- Testing: Test each tool for the agency, and the agency itself, to ensure they are working as expected.
- Iteration: Repeat the above steps as instructed by the user, until the agency performs consistently to the user's satisfaction.
You will find a detailed guide for each of the steps below. Read this entire file first before proceeding.
Step 1: PRD Creation
First, ask the user to provide all necessary details:
- Agency Name
- Purpose (a high-level description of what the agency aims to achieve, its target market, and its value proposition)
- Communication Flows (between agents and from agents to user)
- Agents (for each agent: name, role, tools with descriptions)
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.
- 12d ago First seen · 416 lines · 4,480 tokens per session scan A 21d412f0c862
mcp-skill-creator-agency AGENTS.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 4,480 tokens to every session, about $0.0224 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 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).