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 laurigates/claude-plugins --skill adversarial-reviewgit clone --depth 1 https://github.com/laurigates/claude-pluginsWrote 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/laurigates/claude-plugins/adversarial-review)<a href="https://agentmods.dev/skills/laurigates/claude-plugins/adversarial-review"><img src="https://agentmods.dev/badge/skills/laurigates/claude-plugins/adversarial-review.svg" alt="Measured on agentmods" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 1 finding, up to medium
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 →
- medium Excessive Agency · line 7 Skill selects an external model or provider that may use a different account or billing plan than the operator expects. Undisclosed model switches can cause unexpected cost or quota consumption.Fix: Remove the model/provider override or disclose it prominently and require explicit operator approval before invoking an external coding CLI or billed model.
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 | $0.00037 | $0.02332 |
| Opus 5 | $0.00018 | $0.01166 |
| Sonnet 5 | $0.00007 | $0.00466 |
| Haiku 4.5 | $0.00004 | $0.00233 |
Grade A, and why
adversarial-review 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 — 179 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Adversarial Review
A normal review asks "is this right?" and confirms intent. Adversarial review asks "how could this be wrong?" and hunts for the fault the first pass rationalised away. It is a second pass for residual risk on high-stakes work — not a replacement for the first pass, and not for low-stakes or reversible changes where it only manufactures busywork.
This is a thin posture, not a new checklist. It layers four moves —
isolation, inverted objective, a triage gate, and a bounded loop — on top of
the domain checklists that already live in code-review, security-audit,
verify-before-plan, and cold-read-gate. It dispatches an isolated
reviewer with the matching lens and then triages what comes back, because
an agent told to find faults will invent them.
When to Use This Skill
| Use this skill when... | Use something else instead when... |
|---|---|
| Stakes are high and a normal review already passed, but residual risk remains | First-pass review of a diff/PR → code-quality-plugin:code-review |
| Red-teaming an architecture decision, ADR, or migration plan before commit | Verifying plan facts (counts, paths, build state) → agent-patterns-plugin:verify-before-plan |
| Stress-testing a design's failure modes and invariants | Pure security audit → agents-plugin security-audit / /security-review |
Probing whether outward text survives a reader → wrap cold-read-gate |
Legibility of outward text on its own → agent-patterns-plugin:cold-read-gate |
| The change is hard to reverse and a missed fault is expensive | The change is low-stakes, reversible, or throwaway — skip; it wastes tokens |
The Four Moves
| Move | What it means | Borrowed from |
|---|---|---|
| Isolation | The reviewer gets the artifact with no author context — bias can't leak in | cold-read-gate |
| Inverted objective | Brief says "enumerate failure modes," never "confirm it works" | this skill |
| Triage gate | Separate genuine faults from manufactured objections before acting | cold-read-gate Step 3 |
| Bounded loop | One revise round; a third means a structural problem the gate can't fix | cold-read-gate Step 4 |
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 Changed · +5 lines 133317d97947
- 8d ago First seen · 174 lines · 37 tokens per session scan A 729d2e0b5f70
adversarial-review is a skill published in the GitHub repository laurigates/claude-plugins (58 stars, last pushed today), licensed MIT. It adds 37 tokens to every session and 2,332 once invoked, about $0.0002 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.
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