AttackGen is a cybersecurity tool that uses large language models and the MITRE ATT&CK and ATLAS frameworks to create incident-response scenarios tailored to selected threat actors, AI attack cases, and organisational details. Security teams and purple teams can use it to test and practise responses to cyber incidents. Its catalogue entries provide instructions and skills for using AttackGen.
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 skills add mrwadams/attackgen --skill attackgen-tabletopgit clone --depth 1 https://github.com/mrwadams/attackgenWrote 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/skills/mrwadams/attackgen/attackgen-tabletop)<a href="https://agentmods.dev/skills/mrwadams/attackgen/attackgen-tabletop"><img src="https://agentmods.dev/badge/skills/mrwadams/attackgen/attackgen-tabletop/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/skills/mrwadams/attackgen/attackgen-tabletop"><img src="https://agentmods.dev/badge/skills/mrwadams/attackgen/attackgen-tabletop.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00155 | $0.02349 |
| Opus 5.5 | $0.00062 | $0.00940 |
| Sonnet 5.5 | $0.00031 | $0.00470 |
| Haiku 4.5 | $0.00015 | $0.00235 |
Grade A, and why
attackgen-tabletop 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 yesterday.
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.
The source is not reproduced here
Licensed GPL-3.0
The repository is licensed GPL-3.0, which this catalogue does not treat as permission to reproduce the file. Read it at the source.
What ships with it
4 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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.
- yesterday Changed · +1 lines 7e97904dd367
- 1mo ago First seen · 180 lines · 155 tokens per session scan A 6953f0642ba3
attackgen-tabletop is a skill published in the GitHub repository mrwadams/attackgen (1,255 stars, last pushed 2d ago), licensed GPL-3.0. It adds 155 tokens to every session and 2,349 once invoked, about $0.0006 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 2026-08-30.
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Use this skill when the user asks to save, recall, find, or organize notes. Triggers on: 'remember this', 'save this', 'note this', 'what did we discuss about...', 'check the notebook', 'find in carnet'. Also use proactively when discovering findings worth preserving across sessions.