Agent skill

Adversarial Review

Adversarial code review using cross-model approach. An agent skill from mengxi-ream/read-frog.

GPL-3.0Auto-check passedDevelopment

Install Adversarial Review

skills CLI

$ npx skills add mengxi-ream/read-frog --skill adversarial-review -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI

$ gh skill install mengxi-ream/read-frog adversarial-review --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy

$ git clone --depth 1 https://github.com/mengxi-ream/read-frog.git skills-src && mkdir -p .claude/skills && cp -r skills-src/.agents/skills/adversarial-review .claude/skills/adversarial-review && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Paste into Claude Code

Install the "adversarial-review" agent skill from https://github.com/mengxi-ream/read-frog/tree/main/.agents/skills/adversarial-review into .claude/skills/adversarial-review/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "adversarial-review", then confirm the skill loads.

Claude Code copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.

$skill-installer

$skill-installer install https://github.com/mengxi-ream/read-frog/tree/main/.agents/skills/adversarial-review

Type this inside Codex. $skill-installer <name> installs a curated skill from openai/skills. The installer writes to $CODEX_HOME/skills (default ~/.codex/skills). Restart Codex if the skill does not show up.

skills CLI

$ npx skills add mengxi-ream/read-frog --skill adversarial-review -a codex

Project install goes to .agents/skills/; add -g for ~/.codex/skills/.

GitHub CLI

$ gh skill install mengxi-ream/read-frog adversarial-review --agent codex

Project scope by default (.agents/skills/); add --scope user for a personal install.

Manual copy

$ git clone --depth 1 https://github.com/mengxi-ream/read-frog.git skills-src && mkdir -p .agents/skills && cp -r skills-src/.agents/skills/adversarial-review .agents/skills/adversarial-review && rm -rf skills-src

Use ~/.agents/skills/ instead of .agents/skills for a personal install.

Codex skills documentation · loads skills from .agents/skills/

Paste into Codex

Install the "adversarial-review" agent skill from https://github.com/mengxi-ream/read-frog/tree/main/.agents/skills/adversarial-review into .agents/skills/adversarial-review/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "adversarial-review", then confirm the skill loads.

Codex copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.

skills CLI

$ npx skills add mengxi-ream/read-frog --skill adversarial-review -a cursor

Project install goes to .agents/skills/; add -g for ~/.cursor/skills/.

GitHub CLI

$ gh skill install mengxi-ream/read-frog adversarial-review --agent cursor

Project scope by default (.agents/skills/); add --scope user for a personal install.

Manual copy

$ git clone --depth 1 https://github.com/mengxi-ream/read-frog.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/.agents/skills/adversarial-review .cursor/skills/adversarial-review && rm -rf skills-src

Use ~/.cursor/skills/ instead of .cursor/skills for a personal install.

Cursor skills documentation · loads skills from .cursor/skills/, .agents/skills/, .claude/skills/, .codex/skills/

Paste into Cursor

Install the "adversarial-review" agent skill from https://github.com/mengxi-ream/read-frog/tree/main/.agents/skills/adversarial-review into .cursor/skills/adversarial-review/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "adversarial-review", then confirm the skill loads.

Cursor copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.

gemini skills install

$ gemini skills install https://github.com/mengxi-ream/read-frog.git --path .agents/skills/adversarial-review

--scope user (default) or --scope workspace; --path is the subfolder of the repo that holds the skill; --consent skips the security confirmation prompt.

skills CLI

$ npx skills add mengxi-ream/read-frog --skill adversarial-review -a gemini-cli

Project install goes to .agents/skills/; add -g for ~/.gemini/skills/.

GitHub CLI

$ gh skill install mengxi-ream/read-frog adversarial-review --agent gemini-cli

Project scope by default (.agents/skills/); add --scope user for a personal install.

Manual copy

$ git clone --depth 1 https://github.com/mengxi-ream/read-frog.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/.agents/skills/adversarial-review .gemini/skills/adversarial-review && rm -rf skills-src

Use ~/.gemini/skills/ instead of .gemini/skills for a personal install, then run /skills reload.

Gemini CLI skills documentation · loads skills from .gemini/skills/, .agents/skills/

Paste into Gemini CLI

Install the "adversarial-review" agent skill from https://github.com/mengxi-ream/read-frog/tree/main/.agents/skills/adversarial-review into .gemini/skills/adversarial-review/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "adversarial-review", then confirm the skill loads.

Gemini CLI copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.

GitHub CLI

$ gh skill install mengxi-ream/read-frog adversarial-review

Installs for Copilot at project scope by default; add --scope user for a personal install. Preview a skill first with gh skill preview. Needs GitHub CLI 2.90.0 or later (public preview).

skills CLI

$ npx skills add mengxi-ream/read-frog --skill adversarial-review -a github-copilot

Project install goes to .agents/skills/; add -g for ~/.copilot/skills/.

Manual copy

$ git clone --depth 1 https://github.com/mengxi-ream/read-frog.git skills-src && mkdir -p .github/skills && cp -r skills-src/.agents/skills/adversarial-review .github/skills/adversarial-review && rm -rf skills-src

Use ~/.copilot/skills/ instead of .github/skills for a personal install. Commit .github/skills so cloud agent and code review can use it.

GitHub Copilot skills documentation · loads skills from .github/skills/, .claude/skills/, .agents/skills/

Paste into GitHub Copilot

Install the "adversarial-review" agent skill from https://github.com/mengxi-ream/read-frog/tree/main/.agents/skills/adversarial-review into .github/skills/adversarial-review/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "adversarial-review", then confirm the skill loads.

GitHub Copilot copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.

skills CLI

$ npx skills add mengxi-ream/read-frog --skill adversarial-review -a opencode

OpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.

GitHub CLI

$ gh skill install mengxi-ream/read-frog adversarial-review --agent opencode

Project scope by default (.agents/skills/); add --scope user for a personal install.

Manual copy

$ git clone --depth 1 https://github.com/mengxi-ream/read-frog.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/.agents/skills/adversarial-review .opencode/skills/adversarial-review && rm -rf skills-src

Use ~/.config/opencode/skills/ instead of .opencode/skills for a personal install.

OpenCode skills documentation · loads skills from .opencode/skills/, .claude/skills/, .agents/skills/

Paste into OpenCode

Install the "adversarial-review" agent skill from https://github.com/mengxi-ream/read-frog/tree/main/.agents/skills/adversarial-review into .opencode/skills/adversarial-review/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "adversarial-review", then confirm the skill loads.

OpenCode copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.

Facts

Skill name: adversarial-review
GitHub stars: 10k
Used in: 1 other repo
Token cost: ~905 tokens
SKILL.md length: 397 words
Files: 4 (incl. references)
Skills in repo: 9
Repo updated: Oct 9, 2026
First seen: Oct 7, 2026
Licence: GPL-3.0

At a glance

Adversarial code review using cross-model approach. An agent skill from mengxi-ream/read-frog.

Works in 5 steps: Load Principles → Determine Scope and Intent → Detect Model and Spawn Reviewers → …
Development work in your project
SKILL.md covers Step 1 — Load Principles, Step 2 — Determine Scope and…, Step 3 — Detect Model and… and Step 4 — Verify and Synthesize…, plus 1 more section
Calls codex and claude

What it does

Adversarial Review is an agent skill from mengxi-ream/read-frog. Adversarial code review using cross-model approach. Spawns reviewers on the opposing model (Claude uses Codex, Codex uses Claude) to challenge work from distinct critical lenses. Produces a synthesized verdict with findings and lead judgment. Triggers: "adversarial review".

Its SKILL.md is about 910 tokens, which your agent loads only when the skill is triggered. The skill folder holds 4 other files, including reference files (for example `references/reviewer-lenses.md`, `references/reviewer-prompt.md` and `references/verdict-format.md`).

It sits in Development. It works with Chrome Extensions. The repository describes itself as: 🐸 Read Frog - Language Learning & Translate | 🐸 陪读蛙 - 语言学习与翻译. The licence is GPL-3.0.

When your agent uses it

Development work in your project

Example prompts

“adversarial review”
“/adversarial-review”

Workflow steps

5 steps, taken from the step headings in SKILL.md.

Load Principles
Determine Scope and Intent
Detect Model and Spawn Reviewers
Verify and Synthesize Verdict
Render Judgment

What it can do on your machine

Read from SKILL.md and the folder at commit 80140ea. It shows what the files ask for, not the result of running them.

Tool permissions
Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.
From allowed-tools in the SKILL.md frontmatter.
Runs code
Shell commands in SKILL.md call:
- codex
- claude
From the folder's file list and the shell code blocks in SKILL.md.
Network
No URLs in SKILL.md.
From URLs in SKILL.md, links to its own repository left out.
Credentials
Names no API keys, tokens, secrets or passwords.
From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Adversarial Review loads about 905 tokens when it runs, and up to ~1.6k if it reads all its reference files. Until then it costs about 73 tokens; SKILL.md has 397 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it: ~73
When it runs · the whole SKILL.md, loaded when a task matches: ~905
With references · SKILL.md plus every file in references/, read only if the agent opens them: ~1.6k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.

SKILL.md

The full file from mengxi-ream/read-frog at commit 80140ea, republished under its GPL-3.0 licence (© mengxi-ream). 397 words, ~905 tokens.

Download SKILL.mdSave it as .claude/skills/adversarial-review/SKILL.md (or your agent's skills folder). This skill also uses 3 other files; get the full folder from GitHub.

name: adversarial-review
description: Adversarial code review using cross-model approach. Spawns reviewers on the opposing model (Claude uses Codex, Codex uses Claude) to challenge work from distinct critical lenses. Produces a synthesized verdict with findings and lead judgment. Triggers: "adversarial review".
schedule: After cook sessions that produce large diffs (200+ lines), implement plan phases, or complete a planning session

Adversarial Review

Spawn reviewers on the opposite model to challenge work. Reviewers attack from distinct lenses grounded in brain principles. The deliverable is a synthesized verdict — do NOT make changes.

Hard constraint: Reviewers MUST run via the opposite model's CLI (codex exec or claude -p). Do NOT use subagents, the Agent tool, or any internal delegation mechanism as reviewers — those run on your own model, which defeats the purpose.

Step 1 — Load Principles

Read brain/principles.md. Follow every [[wikilink]] and read each linked principle file. These govern reviewer judgments.

Step 2 — Determine Scope and Intent

Identify what to review from context (recent diffs, referenced plans, user message).

Determine the intent — what the author is trying to achieve. This is critical: reviewers challenge whether the work achieves the intent well, not whether the intent is correct. State the intent explicitly before proceeding.

Assess change size:

Size	Threshold	Reviewers
Small	< 50 lines, 1-2 files	1 (Skeptic)
Medium	50-200 lines, 3-5 files	2 (Skeptic + Architect)
Large	200+ lines or 5+ files	3 (Skeptic + Architect + Minimalist)

Read references/reviewer-lenses.md for lens definitions.

Step 3 — Detect Model and Spawn Reviewers

Create a temp directory for reviewer output:

REVIEW_DIR=$(mktemp -d /tmp/adversarial-review.XXXXXX)

Determine which model you are, then spawn reviewers on the opposite:

If you are Claude — spawn Codex reviewers via codex exec:

codex exec --skip-git-repo-check -o "$REVIEW_DIR/skeptic.md" "prompt" 2>/dev/null

Use --profile edit only if the reviewer needs to run tests. Default to read-only. Run with run_in_background: true, monitor via TaskOutput with block: true, timeout: 600000.

If you are Codex — spawn Claude reviewers via claude CLI:

claude -p "prompt" > "$REVIEW_DIR/skeptic.md" 2>/dev/null

Run with run_in_background: true.

Name each output file after the lens: skeptic.md, architect.md, minimalist.md.

Build each reviewer's prompt using the template in references/reviewer-prompt.md.

Show full SKILL.md (127 more words)Show less

Step 4 — Verify and Synthesize Verdict

Before reading reviewer output, log which CLI was used and confirm the output files exist:

echo "reviewer_cli=codex|claude"
ls "$REVIEW_DIR"/*.md

If any output file is missing or empty, note the failure in the verdict — do not silently skip a reviewer.

Read each reviewer's output file from $REVIEW_DIR/. Deduplicate overlapping findings. Produce a single verdict using the format in references/verdict-format.md.

Step 5 — Render Judgment

After synthesizing the reviewers, apply your own judgment. Using the stated intent and brain principles as your frame, state which findings you would accept and which you would reject — and why. Reviewers are adversarial by design; not every finding warrants action. Call out false positives, overreach, and findings that mistake style for substance.

Append the Lead Judgment section to the verdict (see references/verdict-format.md).

Files

SKILL.md and 3 other files (references) in .agents/skills/adversarial-review of mengxi-ream/read-frog.

SKILL.md
references/reviewer-lenses.md
references/reviewer-prompt.md
references/verdict-format.md

Open the folder on GitHubat commit 80140ea

Used in 1 other repository

We found 1 copy of this SKILL.md (exact, near-identical or edited) in other folders, from 1 other GitHub owner. This page covers the copy in mengxi-ream/read-frog, which our catalogue first saw on October 7, 2026.

poteto/noodle.agents/skills/adversarial-review

Compare with similar skills

Adversarial Review next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.

Adversarial Review compared with similar skills
Skill	Stars	Used in	Tokens	Auto-check	Licence	Repo updated
Adversarial Review this skillmengxi-ream/read-frog	10k	1 repos	~905	Automated safety check: Pass	GPL-3.0	yesterday
Wxt Browser Extensionsvantezzen/skip-silence	469	2 repos	~1.9k	Automated safety check: Pass	MIT	3 mo ago
Archifymolvqingtai/WebChat	2.6k	—	~5.6k	Automated safety check: Pass	MIT	27 days ago
Kimi WebbridgeMoonshotAI/kimi-code	7.8k	—	~3.6k	Automated safety check: Pass	MIT	today
Repomix Browser Extension Developeryamadashy/repomix	29k	1 repos	~288	Automated safety check: Pass	MIT	today
Voyager Contributevoyager-crew/voyager	20k	—	~1.2k	Automated safety check: Pass	GPL-3.0	yesterday

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Works with

Chrome Extensions

Questions about Adversarial Review

What does Adversarial Review do?

Adversarial code review using cross-model approach. An agent skill from mengxi-ream/read-frog. Adversarial Review is an agent skill from mengxi-ream/read-frog. Adversarial code review using cross-model approach.

When should I use Adversarial Review?

Adversarial Review fits situations like: development work in your project.

How do I install Adversarial Review in Claude Code?

Run `npx skills add mengxi-ream/read-frog --skill adversarial-review -a claude-code`. Or copy the skill folder (.agents/skills/adversarial-review in mengxi-ream/read-frog) into .claude/skills/adversarial-review in your project. Claude Code loads it when a task matches its description.

How do I install Adversarial Review in Codex?

Run `npx skills add mengxi-ream/read-frog --skill adversarial-review -a codex`. Or copy the skill folder (.agents/skills/adversarial-review in mengxi-ream/read-frog) into .agents/skills/adversarial-review in your project. Codex loads it when a task matches its description.

Can I use Adversarial Review in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add mengxi-ream/read-frog --skill adversarial-review -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/adversarial-review, .gemini/skills/adversarial-review, .github/skills/adversarial-review and .opencode/skills/adversarial-review in your project.

What does Adversarial Review need to run?

Going by SKILL.md and its folder, Adversarial Review needs the command-line tools its instructions call (codex and claude).

Does Adversarial Review access the network?

SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.

Is Adversarial Review safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.

What licence does Adversarial Review use?

Adversarial Review is published under the GPL-3.0 licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Adversarial Review use?

About 905 tokens (SKILL.md is roughly 3.6k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full. Its references folder adds about 735 tokens, read only when the agent opens those files.

What are the alternatives to Adversarial Review?

Skills that share tags, products or a category with Adversarial Review: Wxt Browser Extensions (vantezzen/skip-silence, 469 stars), Archify (molvqingtai/WebChat, 2.6k stars), Kimi Webbridge (MoonshotAI/kimi-code, 7.8k stars) and Repomix Browser Extension Developer (yamadashy/repomix, 29k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Adversarial Review?

mengxi-ream (a GitHub user) maintains it in mengxi-ream/read-frog, which has 10,029 GitHub stars. The repository holds 9 skills in this directory. The repository was last updated on October 9, 2026.

Source: mengxi-ream/read-frog on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.

Install Adversarial Review

Facts

At a glance

What it does

When your agent uses it

Example prompts

Workflow steps

What it can do on your machine

Tool permissions

Runs code

Network

Credentials

Context cost

Safety

SKILL.md

Adversarial Review

Step 1 — Load Principles

Step 2 — Determine Scope and Intent

Step 3 — Detect Model and Spawn Reviewers

Step 4 — Verify and Synthesize Verdict

Step 5 — Render Judgment

Files

Used in 1 other repository

Compare with similar skills

Similar skills

More from mengxi-ream/read-frog

Related

Questions about Adversarial Review