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/meltedinhex/analyst-ai-pack/agents-mdgit clone --depth 1 https://github.com/meltedinhex/analyst-ai-packWrote 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/meltedinhex/analyst-ai-pack/agents-md)<a href="https://agentmods.dev/instructions/meltedinhex/analyst-ai-pack/agents-md"><img src="https://agentmods.dev/badge/instructions/meltedinhex/analyst-ai-pack/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 | $0.00832 | $0.00832 |
| Opus 5 | $0.00416 | $0.00416 |
| Sonnet 5 | $0.00166 | $0.00166 |
| Haiku 4.5 | $0.00083 | $0.00083 |
Grade A, and why
analyst-ai-pack 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 4d 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 — 74 lines — stays where its author put it; the contents beside it link to each section on GitHub.
AGENTS.md — Using AnalystAIPack as an AI agent
This repository is a skill library for malware analysis, reverse engineering, and threat hunting. If you are an AI coding/security agent, read this file first: it tells you how to find the right skill, run it safely, and chain skills into an investigation.
What this repo is
- 118 self-contained skills under
skills/, one folder each. - Every skill has:
SKILL.md(the procedure),scripts/analyst.py(a runnable tool),references/api-reference.md(script docs + sources), andLICENSE. - Machine-readable catalog:
index.json. Human catalog:CATALOG.md.
How to pick a skill
- Search the catalog by intent, not just keyword:
python tools/analyst-pack.py search <topic> # e.g. "kerberos", "pe imports", "beacon" python tools/analyst-pack.py list --subdomain threat-hunting - Read the chosen
SKILL.md. Honor itsWhen to Useand especially the**Do not use**line — it states the boundaries of the technique. Do not apply a skill outside its scope.
How to run a skill
Each skill's tool is a small CLI. Inspect it, then run it:
python tools/analyst-pack.py show <skill-name> # see its subcommands
python tools/analyst-pack.py run <skill-name> -- <args> # run it
# or directly:
python skills/<skill-name>/scripts/analyst.py <subcommand> <args>
Scripts print structured JSON. Use that output as input to the next skill or a report.
Safety rules (do not violate)
- Never execute the malware sample. Every script performs static, read-only analysis. Do not add code that runs, detonates, or connects to a sample's infrastructure.
- Assume an isolated lab. Skills that handle samples include a
Safety & Handlingsection — follow it. Do not move samples out of the working directory. - Keep IOCs defanged in any output you share (
hxxp://,1[.]2[.]3[.]4). The scripts already do this; preserve it. - No live samples in the repo. This project ships none; never commit one (see
.gitignore).
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.
- 4d ago First seen · 74 lines · 832 tokens per session scan A d204b74a8317
analyst-ai-pack AGENTS.md is an instructions file published in the GitHub repository meltedinhex/analyst-ai-pack (22 stars, last pushed 1mo ago), licensed Apache-2.0. It adds 832 tokens to every session, about $0.0042 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
AiSOC AGENTS.md
AGENTS.md instructions for beenuar/AiSOC, covering learned user preferences and learned workspace facts.
ai-dfir-toolkit CLAUDE.md
Instructions for depalmar/ai-dfir-toolkit, covering project context, what this is, commands, rules that are not negotiable and what a restricted runner cannot verify.
ida-pro-mcp CLAUDE.md
Instructions for mrexodia/ida-pro-mcp, covering claude.md, what this project is, core implementation rules, ida thread safety and api conventions.
MISP CLAUDE.md
Claude Code instructions for MISP/MISP, covering claude.md, project overview, build and development commands, php dependencies and running tests.
sift-mcp AGENTS.md
Instructions for AppliedIR/sift-mcp, covering valhuntir — forensic investigation platform, getting started, available mcp servers, malware analysis escalation and investigation recording.
pentest-mcp-server CLAUDE.md
Claude Code instructions for cyanheads/pentest-mcp-server, covering developer protocol, core rules, patterns, tool (representative — pentestlookuptechnique) and server instructions.