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/sandeep-alluru/notarize/agents-mdgit clone --depth 1 https://github.com/sandeep-alluru/notarizeWrote 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/sandeep-alluru/notarize/agents-md)<a href="https://agentmods.dev/instructions/sandeep-alluru/notarize/agents-md"><img src="https://agentmods.dev/badge/instructions/sandeep-alluru/notarize/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 | $0.00135 | $0.00135 |
| Opus 5 | $0.00068 | $0.00068 |
| Sonnet 5 | $0.00027 | $0.00027 |
| Haiku 4.5 | $0.00014 | $0.00014 |
Grade A, and why
notarize 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 3d 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.
This is a copy
84% identical to groundcrew AGENTS.md — 6 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.
What it actually says
notarize — Agent Context
This file describes the project architecture for AI coding assistants (Claude Code, Cursor, Copilot).
What this project does
Canonical trace format and verifier for agent execution attestation
Module map
src/notarize/
├── # TODO: fill in module map
Key invariants
-
TODO: document invariants that must not be broken
Testing
make test # full test suite
make lint # ruff check + format
make typecheck # mypy
What NOT to change without careful thought
-
TODO: list protected areas
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.
- 3d ago First seen · 31 lines · 135 tokens per session scan A 6a19638f2225
notarize AGENTS.md is an instructions file published in the GitHub repository sandeep-alluru/notarize (0 stars, last pushed 17d ago), licensed MIT. It adds 135 tokens to every session, about $0.0007 per session on Opus 5. A static security scan graded it A with 0 findings. It is 84% identical to groundcrew AGENTS.md, differing in 6 lines, and is treated as a copy.
Other instructions, from other repositories
warrant AGENTS.md
Instructions for s0fractal/warrant, covering agent & contributor conduct (governance-critical), hard rules, the human's role and precedent (why this file exists).
jentic-one GEMINI.md
Instructions for jentic/jentic-one: Otherwise, read AGENTS.md — this repo's canonical agent guidance.
hig-doctor AGENTS.md
AGENTS.md instructions for raintree-technology/hig-doctor: HIG Doctor combines open-source audit tooling with an attributed snapshot of Apple's Human Interface Guidelines.
briefloop AGENTS.md
AGENTS.md instructions for Stahl-G/briefloop, covering agents.md, purpose, instruction scope, environment separation and context mode.
ProofFlow-v0.1 AGENTS.md
Instructions for Hyperion-GPU/ProofFlow-v0.1, covering proofflow agent rules, workflow, evidence, safety and architecture.
obsigna python.instructions.md
Instructions for agent-receipts/obsigna, a project described as: Agent Receipts — cryptographically signed audit trails for AI agent actions. Protocol spec, SDKs (Go, TypeScript, Python), and MCP proxy.