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/packtman/ai-tools-secure-configs/agents-mdgit clone --depth 1 https://github.com/packtman/AI-Tools-Secure-ConfigsWrote 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/packtman/ai-tools-secure-configs/agents-md)<a href="https://agentmods.dev/instructions/packtman/ai-tools-secure-configs/agents-md"><img src="https://agentmods.dev/badge/instructions/packtman/ai-tools-secure-configs/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 | $0.00460 | $0.00460 |
| Opus 5 | $0.00230 | $0.00230 |
| Sonnet 5 | $0.00092 | $0.00092 |
| Haiku 4.5 | $0.00046 | $0.00046 |
Grade A, and why
AI-Tools-Secure-Configs 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 5d 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
Cursor Cloud specific instructions
This is a documentation and configuration reference repository (AI-Secure-Configs). It contains security-hardened configuration templates and deployment guides for AI coding tools. There is no runnable application, no build system, and no package dependencies.
Repository structure
Each top-level directory (e.g. claude-code/, cursor/, github-copilot/) provides config templates and markdown guides for a specific AI tool. The rollout-guide/ directory contains a cross-tool deployment plan.
File types
.md— Documentation and deployment checklists.json/.jsonc— Configuration templates (70 JSON + 4 JSONC files).yaml/.yml— Configuration templates (10 files).toml— Configuration templates (14 files).sh— Example hook scripts inclaude-code/examples/hook-scripts/.mdc— Cursor rule files
Development workflow
There is no build, test suite, or dev server. Development consists of editing documentation and config files. To validate changes:
# Validate JSON files
python3 -c "import json; json.load(open('path/to/file.json'))"
# Validate YAML files
yamllint -d relaxed path/to/file.yaml
# Validate TOML files
python3 -c "import toml; toml.load('path/to/file.toml')"
# Validate shell scripts
bash -n path/to/script.sh
Tools available in the environment
python3withyaml,tomlpackages for config validationyamllintat~/.local/bin/yamllintbash -nfor shell script syntax checkinggitfor version control
Notes
- JSONC files (
.jsonc) contain comments and cannot be validated with standard JSON parsers; they are documentation-oriented config examples. - The
claude-code/CLAUDE.mdfile is a security instructions template (not project documentation for this repo itself). - There is no CI/CD pipeline configured (no
.github/workflows/directory).
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.
- 5d ago First seen · 50 lines · 460 tokens per session scan A 1ed18be8bd6a
AI-Tools-Secure-Configs AGENTS.md is an instructions file published in the GitHub repository packtman/AI-Tools-Secure-Configs (4 stars, last pushed today), licensed MIT. It adds 460 tokens to every session, about $0.0023 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
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.
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.
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).