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 monkey1wizard/Golem-Agents-Legion --skill adversarial-reviewgit clone --depth 1 https://github.com/monkey1wizard/Golem-Agents-LegionWrote 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/monkey1wizard/golem-agents-legion/adversarial-review)<a href="https://agentmods.dev/skills/monkey1wizard/golem-agents-legion/adversarial-review"><img src="https://agentmods.dev/badge/skills/monkey1wizard/golem-agents-legion/adversarial-review/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/monkey1wizard/golem-agents-legion/adversarial-review"><img src="https://agentmods.dev/badge/skills/monkey1wizard/golem-agents-legion/adversarial-review.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 | $0.00000 | $0.00725 |
| Opus 5 | $0.00000 | $0.00362 |
| Sonnet 5 | $0.00000 | $0.00145 |
| Haiku 4.5 | $0.00000 | $0.00072 |
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 5d 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 — 57 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Adversarial Review
Single-source method for adversarial review across GAL roles. This skill is target-agnostic: apply it to plans, diffs, docs, decisions, claims, and review write-back.
Forked Invocation
Direct invocation (/adversarial-review <target>) runs in an independent subagent with no access to the invoking conversation. That isolation is the point: a review inherited from the authoring context is not an independent judgment.
Review target: $ARGUMENTS
- Resolve any referenced path against the repository and read it yourself. Nothing about the target is already known to you.
- Gather evidence with your own tools before forming a verdict. A finding with no repo evidence, no observed behavior, and no named receipt is refuted by rule 2, including your own.
- Return one verdict block —
APPROVE/REVISE/REJECT— with the evidence cited by file path and line. - With no target given, return
REVISE: no review target provided.
Roles that apply this method from their own agent context (architect, analyst, designer, tester, steward) read the sections below and ignore this one.
Core Method
- Steel-man the proposal first. Restate the strongest honest version of the proposal before attacking it. Do not argue against a weaker straw-man.
- Refute by default under doubt. If a claim is under-evidenced, treat it as refuted until evidence arrives. Missing evidence is not a soft pass.
- Run the minimalism gate by pointer, not restatement. Apply conventions/minimalism.md before accepting any new mechanism, abstraction, file, or dependency. Do not restate the ladder here.
- Enforce evidence discipline. Anchor findings in concrete repo evidence, observable behavior, deterministic receipts, or an explicitly named absence of evidence. Do not invent certainty.
- Use explicit verdict vocabulary.
APPROVE= proceedREVISE= fixable gaps; stop and loop backREJECT= wrong direction; rethink from first principles
- Treat
REVISEas a jidoka stop-line. Do not continue downstream while a blocking review gap remains open. NotRunis never pass. Missing execution, missing receipt, timeout, disconnected-partial, or unobserved behavior cannot be upgraded by optimistic prose.
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.
- 5d ago First seen · 57 lines · 0 tokens per session scan A da10c186ef6b
adversarial-review is a skill published in the GitHub repository monkey1wizard/Golem-Agents-Legion (15 stars, last pushed yesterday), licensed MIT. It costs nothing until one of its globs matches a file; then it loads 725 tokens. 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 2026-09-04.
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omh-code-review
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revdiff-plan
Review the last Codex assistant message (plan, analysis, or proposal) with inline annotations in a TUI overlay. Extracts the most recent response from Codex rollout files and opens it in revdiff for review and annotation. Activates on "revdiff-plan", "review plan with revdiff", "annotate plan", "review last response"…
code-reviewer
Code review specialist focused on patterns, bugs, security, and performance.
full-repo-review
Comprehensive four-wave review of all repo source files, producing a prioritized issue backlog.