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 instructions/zazencodes/random-number-mcp/agents-mdgit clone --depth 1 https://github.com/zazencodes/random-number-mcpWrote 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/zazencodes/random-number-mcp/agents-md)<a href="https://agentmods.dev/instructions/zazencodes/random-number-mcp/agents-md"><img src="https://agentmods.dev/badge/instructions/zazencodes/random-number-mcp/agents-md.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 | $0.00829 | $0.00829 |
| Opus 5 | $0.00415 | $0.00415 |
| Sonnet 5 | $0.00166 | $0.00166 |
| Haiku 4.5 | $0.00083 | $0.00083 |
Grade A, and why
random-number-mcp 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 6d 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 — 76 lines — stays where its author put it; the contents beside it link to each section on GitHub.
CLAUDE.md
This file provides guidance to Claude Code (claude.ai/code) when working with code in this repository.
Commands
# Install dependencies
uv sync --dev
# Run tests
uv run pytest
# Run a single test
uv run pytest tests/test_tools.py::test_function_name
# Lint and format
uv run ruff check --fix
uv run ruff format
# Type checking
uv run mypy src/
# Run server locally
uv run random-number-mcp
# Build package
uv build
# Inspect/test with MCP Inspector
npx @modelcontextprotocol/inspector uv run random-number-mcp
Architecture
The package is a FastMCP server with a three-layer structure:
server.py— FastMCP app instance and@app.tool()decorated endpoints. Handles MCP protocol concerns (e.g., JSON string weights parsing). Entry point ismain().tools.py— Pure Python business logic, callsrandomandsecretsstdlib modules. No FastMCP dependency; testable in isolation.utils.py— Shared validation helpers used bytools.py.
Tools fall into two categories: standard pseudorandom (random module) and cryptographically secure (secrets module).
Release Process
The Release Checklist in README.md is canonical — follow it, don't work from memory. Notes for agents:
- The version lives in four fields across three files:
pyproject.toml,src/random_number_mcp/__init__.py, andserver.json(which carries it both at the top level and underpackages[0]). Miss one and the release ships inconsistent metadata. CHANGELOG.mdis updated as part of the same commit as the version bump.- Release from
main, with the branch merged and pushed first. Fetch before assuming localmainis current — work is sometimes merged upstream via PR, so a local-only merge can leave you diverged.
Cutting the release
Always ask the maintainer for explicit confirmation before this step. Creating the release publishes to PyPI automatically via the release: published trigger in .github/workflows/publish.yml, and that is irreversible — a version can never be overwritten or reused on PyPI.
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.
- 6d ago First seen · 76 lines · 829 tokens per session scan A f49df9a82c2d
random-number-mcp AGENTS.md is an instructions file published in the GitHub repository zazencodes/random-number-mcp (50 stars, last pushed 1mo ago), licensed MIT. It adds 829 tokens to every session, about $0.0041 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 2026-08-30.
Other instructions, from other repositories
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.
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 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).
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.