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/danieloza/agent-intel-mcp/agents-mdgit clone --depth 1 https://github.com/danieloza/agent-intel-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/danieloza/agent-intel-mcp/agents-md)<a href="https://agentmods.dev/instructions/danieloza/agent-intel-mcp/agents-md"><img src="https://agentmods.dev/badge/instructions/danieloza/agent-intel-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 | $0.00281 | $0.00281 |
| Opus 5 | $0.00140 | $0.00140 |
| Sonnet 5 | $0.00056 | $0.00056 |
| Haiku 4.5 | $0.00028 | $0.00028 |
Grade A, and why
agent-intel-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 2d 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.
What it actually says
AGENTS.md
Mission
Build a portfolio-grade MCP server that discovers high-signal agent-engineering patterns and turns them into safe, reviewable AGENTS.md updates.
Stack
- TypeScript on Node.js 24
- MCP stdio server via
@modelcontextprotocol/sdk - OpenAI
Responses APIfor suggestion synthesis - GitHub API via Octokit
- SQLite via
better-sqlite3
Working Rules
- Keep the server non-destructive. Patch previews are preferred over direct writes.
- Preserve deterministic fallbacks when external APIs are unavailable.
- Favor small, composable modules in
src/core/*. - Store durable scan and suggestion state in
.agent-intel/agent-intel.db. - Keep clustering deterministic enough to test when embeddings are unavailable.
- When changing prompts or suggestion logic, keep the JSON output contract stable.
Validation
- Run
npm run build - Run
npm test - Run
npm run lint
MCP Surface
- Tools live in
src/mcp/server.ts - Business logic lives in
src/core/ - Persistence lives in
src/storage/ - CI and release workflows live in
.github/workflows/
Change Expectations
- Add tests for new extraction or suggestion heuristics.
- Document major architectural changes in
docs/ARCHITECTURE.md.
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.
- 2d ago First seen · 41 lines · 281 tokens per session scan A 618422d14372
agent-intel-mcp AGENTS.md is an instructions file published in the GitHub repository danieloza/agent-intel-mcp (0 stars, last pushed 5mo ago), licensed MIT. It adds 281 tokens to every session, about $0.0014 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
hindsight CLAUDE.md
Instructions for vectorize-io/hindsight, covering claude.md, project overview, development commands, local development (api + ui) and start both api server and control plane ui.
codedb AGENTS.md
AGENTS.md instructions for justrach/codedb, covering codedb agent guidelines, what codedb is (and isn't), review guidelines, pre-merge verification and security-sensitive areas.
claude-code-settings copilot-instructions.md
Instructions for feiskyer/claude-code-settings, covering claude.md, environment setup, required dependencies, configuration and skills.
axonhub CLAUDE.md
Claude Code instructions for looplj/axonhub: @AGENTS.md read and follow its instructions.
Assistant AGENTS.md
Instructions for bearlike/Assistant: This is a shim file for external agents.
openai-agents-python CLAUDE.md
Claude Code instructions for openai/openai-agents-python, a project described as: A lightweight, powerful framework for multi-agent workflows.