Borrowing it
Nothing to install: this file belongs to Liberty91LTD/cti-skills. 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/Liberty91LTD/cti-skills/main/AGENTS.mdgit clone --depth 1 https://github.com/Liberty91LTD/cti-skillsWrote 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/liberty91ltd/cti-skills/agents-md)<a href="https://agentmods.dev/instructions/liberty91ltd/cti-skills/agents-md"><img src="https://agentmods.dev/badge/instructions/liberty91ltd/cti-skills/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/liberty91ltd/cti-skills/agents-md"><img src="https://agentmods.dev/badge/instructions/liberty91ltd/cti-skills/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 | $0.01165 | $0.01165 |
| Opus 5 | $0.00583 | $0.00583 |
| Sonnet 5 | $0.00233 | $0.00233 |
| Haiku 4.5 | $0.00117 | $0.00117 |
Grade A, and why
cti-skills 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 9d 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 — 90 lines — stays where its author put it; the contents beside it link to each section on GitHub.
AGENTS.md — Orientation for AI agents
You're an agent loading the cti-skills pack. This file tells you what's here, how to use it, and what conventions to follow. It's platform-neutral — the same rules apply in Claude Code, Cursor, Codex, Windsurf, and any other agentic IDE that supports the Agent Skills spec.
What this pack is
Cyber Threat Intelligence skills: threat actor profiling, IOC investigation, OSINT methodology, detection engineering (SIGMA/YARA/KQL), intelligence writing, and self-updating knowledge cells on nation-state and cybercrime threats.
Not an internal ops tool. A public distribution artifact. Optimize for adoption and clarity over enforced rigor.
Shape
skills/ # flat — ~52 composable skills (will flatten in Phase C)
.claude/ # Claude Code specific (agents, settings). Other platforms ignore.
.claude-plugin/ # plugin manifest for Claude Code marketplace install
tools/ # REGISTRY.md + per-API integration guides + zero-dep CLIs
data/ # sample IOCs, reports, PIRs — example content, not required
mitre-attack/ # local MITRE ATT&CK Enterprise dataset
VERSIONS.md # per-skill semver + changelog
validate-skills.sh # frontmatter linter — run before committing
Finding and invoking skills
Skills are self-describing via YAML frontmatter. The description field includes trigger phrases — match user intent against descriptions to decide which skill to use.
---
name: threat-actor-profile
description: Use when the user asks to profile a threat actor, build an actor card, or characterize an adversary group. Produces an actor profile with aliases, TTPs, targeting, attribution confidence, and observed infrastructure.
---
Skills can invoke other skills. An investigation skill like /ip-investigation will chain /lookup-virustotal, /lookup-otx, /lookup-shodan, and then apply rigor skills like /score-source and /apply-tlp. When you're a skill composing others, state the composition explicitly at the top of the skill body: "This skill invokes: X, Y, Z."
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.
- 9d ago First seen · 90 lines · 1,165 tokens per session scan A d57777ad4a2a
cti-skills AGENTS.md is an instructions file published in the GitHub repository Liberty91LTD/cti-skills (17 stars, last pushed 1mo ago), licensed MIT. It adds 1,165 tokens to every session, about $0.0058 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 2026-08-30.
Other instructions, from other repositories
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.
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).
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).
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.
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.