adversarial-review

adversarial-review is a skill for Claude Code from IgorGanapolsky/ThumbGate. It costs 42 tokens per session (220 once invoked), scanned A, original, MIT.

A skeptical code review that looks for hidden regressions, unsafe assumptions, and risks before a change is released. It can review uncommitted work, a branch against a base branch, or a specific commit.

In plain words
What is it for?
Use it before merging code, deploying a release, running a migration, or making another risky change. You can focus the review on threats such as security, billing, rollback safety, or data loss.
Why use it?
It helps catch problems that a routine review may miss before they reach users or make a rollback difficult.

Skill for Claude Code

Written for Claude Code: ${CLAUDE_PLUGIN_ROOT} variable. Also seen: mentions Claude Code; mentions Codex.

Runs only inside its plugin — its command needs a path that Claude Code sets for a plugin’s own hooks and for nothing else. Install the plugin, not this.

Part of the codex-bridge plugin — 6 skills shipped together

Good fit Use it before merging code, deploying a release, running a migration, or making another risky change. You can focus the review on threats such as security, billing, rollback safety, or data loss.

Compare 6 skills from other repositories ↓
Install

Getting it into your agent

This one installs as part of its plugin. Adding the marketplace and installing the plugin brings it with everything else the plugin ships.

Claude Code
/plugin marketplace add IgorGanapolsky/ThumbGate
Claude Code
/plugin install codex-bridge

Made for: Claude Code.

Or install codex-bridge, the plugin that ships this one along with the rest of its 6 skills.

Wrote 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.

agentmods badge for adversarial-review

README.md
[![agentmods](https://agentmods.dev/badge/skills/igorganapolsky/thumbgate/adversarial-review/github.svg)](https://agentmods.dev/skills/igorganapolsky/thumbgate/adversarial-review)
Your own site
<a href="https://agentmods.dev/skills/igorganapolsky/thumbgate/adversarial-review"><img src="https://agentmods.dev/badge/skills/igorganapolsky/thumbgate/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.

agentmods 80×15 button for adversarial-review

Your own site · 80×15
<a href="https://agentmods.dev/skills/igorganapolsky/thumbgate/adversarial-review"><img src="https://agentmods.dev/badge/skills/igorganapolsky/thumbgate/adversarial-review.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 42 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 220 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5.1 $0.00042 $0.00220
Opus 5 $0.00021 $0.00110
Sonnet 5 $0.00008 $0.00044
Haiku 4.5 $0.00004 $0.00022

Measured 11d ago against content hash 82f062709822, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-11, from the pricing page.

Security

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 11d 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.

plugins/claude-codex-bridge/skills/adversarial-review/SKILL.md · 25 lines

What it actually says

Adversarial Review

Default to the current uncommitted workspace unless the user explicitly provides base=<branch> or commit=<sha>.

Run one of:

node "${CLAUDE_PLUGIN_ROOT}/scripts/codex-bridge.js" adversarial-review --uncommitted
node "${CLAUDE_PLUGIN_ROOT}/scripts/codex-bridge.js" adversarial-review --base main
node "${CLAUDE_PLUGIN_ROOT}/scripts/codex-bridge.js" adversarial-review --commit <sha>

If the user asks for a specific threat model such as security, rollback safety, billing, or data loss, pass that in --prompt.

When reporting back:

  • lead with concrete risks
  • separate proven issues from speculation
  • mention the saved artifact path if the user wants the full Codex output
Changes

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.

  1. 11d ago First seen · 25 lines · 42 tokens per session scan A 82f062709822

Subscribe to this mod's changes

adversarial-review is a skill published in the GitHub repository IgorGanapolsky/ThumbGate (26 stars, last pushed today), licensed MIT. It adds 42 tokens to every session and 220 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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