Borrowing it
Nothing to install: this file belongs to khalilbenaz/MDAN. 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/khalilbenaz/MDAN/main/.claude/commands/mdan-review-adversarial-general.mdgit clone --depth 1 https://github.com/khalilbenaz/MDANWrote 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/commands/khalilbenaz/mdan/mdan-review-adversarial-general)<a href="https://agentmods.dev/commands/khalilbenaz/mdan/mdan-review-adversarial-general"><img src="https://agentmods.dev/badge/commands/khalilbenaz/mdan/mdan-review-adversarial-general/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/commands/khalilbenaz/mdan/mdan-review-adversarial-general"><img src="https://agentmods.dev/badge/commands/khalilbenaz/mdan/mdan-review-adversarial-general.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 | $0.00027 | $0.00078 |
| Opus 5 | $0.00014 | $0.00039 |
| Sonnet 5 | $0.00005 | $0.00016 |
| Haiku 4.5 | $0.00003 | $0.00008 |
Grade A, and why
review-adversarial-general 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 10d 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.
This is a copy
94% identical to review-adversarial-general — 2 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
What it actually says
review-adversarial-general
Read the entire task file at: {project-root}/_mdan/core/tasks/review-adversarial-general.xml
Follow all instructions in the task file exactly as written.
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.
- 10d ago First seen · 11 lines · 27 tokens per session scan A a9e3b8e008c6
review-adversarial-general is a command published in the GitHub repository khalilbenaz/MDAN (0 stars, last pushed 5mo ago), licensed MIT. It adds 27 tokens to every session and 78 once invoked, about $0.0001 per session on Opus 5. A static security scan graded it A with 0 findings. It is 94% identical to review-adversarial-general, differing in 2 lines, and is treated as a copy.
Other commands, from other repositories
gh-triage
GitHub OSS maintainer lifecycle triage, review, and approval management.
code-review-swarm
Deploy specialized AI agents to perform comprehensive, intelligent code reviews that go beyond traditional static analysis.
swarm-pr
Create and manage AI swarms directly from GitHub Pull Requests, enabling seamless integration with your development workflow.
pr-manager
Comprehensive pull request management with ruv-swarm coordination for automated reviews, testing, and merge workflows.
code-review
Automated code review with swarm intelligence.
pr-enhance
Command "pr-enhance" from Soulcynics404/AgentForge, covering pr-enhance, usage, options, examples and enhance pr.