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 mhylle/claude-skills-collection --skill adversarial-reviewergit clone --depth 1 https://github.com/mhylle/claude-skills-collectionWrote 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/mhylle/claude-skills-collection/adversarial-reviewer)<a href="https://agentmods.dev/skills/mhylle/claude-skills-collection/adversarial-reviewer"><img src="https://agentmods.dev/badge/skills/mhylle/claude-skills-collection/adversarial-reviewer/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/mhylle/claude-skills-collection/adversarial-reviewer"><img src="https://agentmods.dev/badge/skills/mhylle/claude-skills-collection/adversarial-reviewer.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
SkillSpector: 1 finding, up to low
These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →
- low Privilege Escalation · line 277 Skill requests more permissions than appear necessary for its stated functionality. Review if elevated access is justified.Fix: Request only the minimum permissions required. Document why each permission is needed. Remove broad permissions like '*' or 'all'.
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 | $0.00288 | $0.05213 |
| Opus 5 | $0.00144 | $0.02606 |
| Sonnet 5 | $0.00058 | $0.01043 |
| Haiku 4.5 | $0.00029 | $0.00521 |
Grade A, and why
adversarial-reviewer scanned grade A with 1 finding 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 12d 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.
Runs shell commandslowCapability
Expected in a hook, worth knowing in a rule or an instructions file.
`child_process`, raw SQL, `pickle.loads`, `yaml.load` — these are useful How it starts
The opening of the file, as written. The whole thing — 392 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Adversarial Code Reviewer
Adversarial code review that forces genuine perspective shifts by dispatching three hostile reviewer personas as independent subagents. Each subagent gets only the code and its persona brief — not the history of why the code was written, not Claude's reasoning about it, not prior "looks good" conclusions. Findings are then severity-classified and cross-promoted when caught by multiple personas.
Why Subagents Matter Here
The whole point of this skill is breaking out of the self-review trap: when Claude reviews code it just wrote or just read, the reviewing context shares the producing context's mental model and blind spots. If all three personas ran in the same context, the "perspective shift" would be cosmetic — same weights, same priming, same assumptions.
Running each persona as an isolated subagent forces a real reset:
- Each subagent starts with only the diff, the files, and its persona brief.
- It cannot know what problem the author was trying to solve, what was tried and rejected, or what Claude already concluded.
- It cannot be swayed by another persona's findings — the three proceed in parallel.
- Synthesis happens only after all three have independently reported.
This is the mechanism. Preserve it.
When to Use
- Before merging any PR — especially self-authored PRs with no human reviewer
- After a long coding session — fatigue produces blind spots
- When Claude just said "looks good" — if approval came easy, run this for a second opinion
- On security-sensitive code — auth, payments, data access, API endpoints
- When something feels off — trust the instinct
Usage
/adversarial-review # Review staged/unstaged changes (default)
/adversarial-review --diff HEAD~3 # Review last 3 commits
/adversarial-review --diff main...HEAD # Review a feature branch vs main
/adversarial-review --file src/auth.ts # Review a specific file in full
/adversarial-review --codebase # Review the whole repo (from CWD)
/adversarial-review --codebase src/api # Review a specific subtree
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.
- 12d ago First seen · 392 lines · 288 tokens per session scan A c288c27371c5
adversarial-reviewer is a skill published in the GitHub repository mhylle/claude-skills-collection (18 stars, last pushed 10d ago), licensed MIT. It adds 288 tokens to every session and 5,213 once invoked, about $0.0014 per session on Opus 5. A static security scan graded it A with 1 finding (runs shell commands). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
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