Borrowing it
Nothing to install: this file belongs to RenatoMignone/From-LLMs-to-Secure-Agents. 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/RenatoMignone/From-LLMs-to-Secure-Agents/main/AGENTS.mdgit clone --depth 1 https://github.com/RenatoMignone/From-LLMs-to-Secure-AgentsWrote 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/renatomignone/from-llms-to-secure-agents/agents-md)<a href="https://agentmods.dev/instructions/renatomignone/from-llms-to-secure-agents/agents-md"><img src="https://agentmods.dev/badge/instructions/renatomignone/from-llms-to-secure-agents/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/renatomignone/from-llms-to-secure-agents/agents-md"><img src="https://agentmods.dev/badge/instructions/renatomignone/from-llms-to-secure-agents/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 | $0.00503 | $0.00503 |
| Opus 5.5 | $0.00201 | $0.00201 |
| Sonnet 5.5 | $0.00101 | $0.00101 |
| Haiku 4.5 | $0.00050 | $0.00050 |
Grade A, and why
From-LLMs-to-Secure-Agents 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 17d 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 — 34 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Agent Instructions
Build a sequential, source-grounded, visual guide to agentic AI and its security.
Run contract
- Run
python3 scripts/main.py state resolve. Do not read fullPROJECT_STATUS.mdorROADMAP.mdduring normal runs. - Read returned local
AGENTS.md,chapter-plan.md, and only selected policies. - Check for any pending tasks below before starting new units.
- Follow the matching author, review, or blocked path in
docs/autonomous-workflow.md. - Work on one unit. Stop after review, completion, or a recorded blocker.
Policy map
- Scope and structure:
docs/project-charter.md,docs/information-architecture.md - Prose and chapters:
docs/style-guide.md,docs/chapter-template.md - Sources, visuals, and code:
docs/evidence-policy.md,docs/visuals-policy.md,docs/examples-policy.md - Site and upkeep:
docs/site-policy.md,docs/maintenance.md,docs/roadmap.md
Invariants
- Use simple English; define technical terms on first use. Omit empty placeholders.
- Never create ASCII/text-based schemas or scripted/programmatic drawing schemes. Use the image generation skill for PNG/WebP cartoon illustrations matching
assets/images/repo-images/source/prompt.txt. - Use 1 to 3 cartoon visuals when they materially improve comprehension. One strong visual is enough for a focused chapter; reserve multiple visuals for architecture, workflow, state, and threat scenarios that need them.
- If image generation quota is temporarily exhausted, save prompts in
source/and record a pending entry inAGENTS.mdfor the next session to generate. - Include a next-unit navigation button at the end of each chapter.
- Teach in dependency order: functional architecture before detailed security.
- Map risks to components; ground claims in official sources (
sources/<chapter-path>/<source-id>.yml). - Keep visuals local and traceable; save visual prompts in
source/before generating. No SVGs. - Keep Markdown canonical; validate the site (
npm --prefix site run build && npm --prefix site run check). - Store small runnable examples under
examples/<chapter-path>/. - Make minimal implementation code blocks expandable by default using
<details><summary>Expand minimal Python implementation</summary>...</details>. - Do not use em dashes.
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.
- 1mo ago Changed · +6 lines · +103 tokens per session 0741cb0e6d3e
- 1mo ago Changed · +25 tokens per session a0e3428b2aa9
- 1mo ago First seen · 34 lines · 478 tokens per session scan A df52890cdd8d
From-LLMs-to-Secure-Agents AGENTS.md is an instructions file published in the GitHub repository RenatoMignone/From-LLMs-to-Secure-Agents (7 stars, last pushed 2d ago), licensed MIT. It adds 503 tokens to every session, about $0.0020 per session on Opus 5.5. 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
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).
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.
vscode oss-third-party-notices.instructions.md
Instructions for microsoft/vscode, covering vs code oss third-party-notices pipeline, architecture, pipeline flow in ci, cache eligibility and rollout and applying the notice (cutover).
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 copilot-instructions.md
Copilot instructions for microsoft/vscode, covering vs code copilot instructions, project overview, root folders, core architecture (src/ folder) and built-in extensions (extensions/ folder).
vscode model-prompts.instructions.md
Model-specific prompt authoring and registry guidelines.