Borrowing it
Nothing to install: this file belongs to Project-VIC-International/Agentic-AI-Development-Course. 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/Project-VIC-International/Agentic-AI-Development-Course/main/AGENTS.mdgit clone --depth 1 https://github.com/Project-VIC-International/Agentic-AI-Development-CourseWrote 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/project-vic-international/agentic-ai-development-course/agents-md)<a href="https://agentmods.dev/instructions/project-vic-international/agentic-ai-development-course/agents-md"><img src="https://agentmods.dev/badge/instructions/project-vic-international/agentic-ai-development-course/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/project-vic-international/agentic-ai-development-course/agents-md"><img src="https://agentmods.dev/badge/instructions/project-vic-international/agentic-ai-development-course/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 | $0.01389 | $0.01389 |
| Opus 5.5 | $0.00556 | $0.00556 |
| Sonnet 5.5 | $0.00278 | $0.00278 |
| Haiku 4.5 | $0.00139 | $0.00139 |
Grade A, and why
Agentic-AI-Development-Course 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 18d 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 — 87 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Agent Instructions: Agentic AI Development Course
These instructions apply to every AI coding agent working in this repository (Cursor, Claude Code, Codex, GitHub Copilot, Gemini CLI, OpenCode, Zed, Warp, and others).
This repository contains training materials for the Agentic AI Development Course, a two-part session that teaches investigators and examiners to build interoperable mission tools for crimes-against-children and other digital investigations using agentic AI and open standards. It is delivered at events such as the National Cyber Crime Conference (NCCC) and DFRWS APAC.
Students do their hands-on work in a private repository created from the project template. The template's policies/ folder holds the full development policies; this file covers the course materials themselves.
Audience
- Law enforcement investigators, digital forensic examiners, intelligence analysts, prosecutors, and researchers from many countries
- Working crimes-against-children cases and other digital investigations
- No prior programming experience assumed
- English may be a second or third language
- Explanations must be in plain language with investigation-relevant examples
Key Standards
All tools and examples in this course must be compliant with:
- UCO (Unified Cyber Ontology): foundational cyber domain vocabulary
- Namespace:
https://ontology.unifiedcyberontology.org/uco/ - GitHub: https://github.com/ucoProject
- Namespace:
- CASE (Cyber-investigation Analysis Standard Expression): cyber-investigation extension
- Namespace:
https://ontology.caseontology.org/case/ - GitHub: https://github.com/casework
- Namespace:
- CAC Ontology (Crimes Against Children Ontology): domain-specific extension
- Namespace:
https://cacontology.projectvic.org/ - GitHub: https://github.com/Project-VIC-International/CAC-Ontology
- Namespace:
- SOLVE-IT (optional): digital forensics techniques, weaknesses, and mitigations knowledge base
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.
- 18d ago First seen · 87 lines · 1,389 tokens per session scan A 351883c1db69
Agentic-AI-Development-Course AGENTS.md is an instructions file published in the GitHub repository Project-VIC-International/Agentic-AI-Development-Course (5 stars, last pushed 14d ago), licensed Apache-2.0. It adds 1,389 tokens to every session, about $0.0056 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 2026-10-14.
Other instructions, from other repositories
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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).
deepseek-harness AGENTS.md
AGENTS.md instructions for deepseek-ai/deepseek-harness, covering agents.md, pre-stable apis and released session data, repository layout, commands and host sandbox failures.