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Agent skill · Audited from source

adversarial-review

skill · poteto/noodleMIT licenceAudited 20 Oct 2026 · source a75fdcc2eb73

★ 523pushed 215 days ago
!CAUTIONGrade B · 89/100 · 3 findings · a75fdcc
523repo stars · whole poteto/noodle

Is it safe? With care — CAUTION, grade B (89/100). We read this skill's source at commit a75fdcc2eb73 and found no filesystem, network or shell access and no hard-coded secrets. The audit raised 3 findings, 0 critical or high. What it does: 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…

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Cite this page

ModelsAtlas. “adversarial-review (poteto/noodle)”. Retrieved 20 Oct 2026. https://modelsatlas.com/skills/poteto/adversarial-review

Trust audit

Audit 0.4.1 · source read 20 Oct 2026

Trust score89/100!CAUTION B
0 critical0 high3 medium0 low0 info

CAUTION means the audit found things worth knowing before you trust this skill. Grade B is shared by 16,667 of 17,602 audited skills.

What the source does

  • FilesystemNone observedNo reads or writes in the source
  • NetworkNone observedNo outbound calls in the source
  • ShellNone observedNo commands run in the source
  • DependenciesPinnedNothing floats
  • SecretsNone foundNo keys in source

Five audit layers

LayerWhat we checkResultFindings
L0 ProvenanceRepo owner, licence, archive status, activityWARN3
L1 Static sourceSecrets, path traversal, supply chain, hidden codeNA0
L2 InstructionsPrompt injection, authority framing, hidden directivesPASS0
L3 InventoryThe files and declarations match the sourcePASS0
L4 SandboxRun in isolation and watch behaviourSKIPPED why0

Gates applied: no behavioural pass.

Findings (3)

Audit 0.4.1 · source sha a75fdcc2eb73 · 20 Oct 2026Report an issue or request a re-scan

Provenance

Who published it, and what the verdict is pinned to

  • Publisherpoteto GitHub userOwner of the repository this skill is read from
  • Source folderpoteto/noodle/.agents/skills/adversarial-reviewThe exact folder we audited
  • LicenceMITAs the repository states it
  • Commit pinned for this verdicta75fdcc2eb73A new audit runs when the source changes
  • Repository statusNot archivedLast push 215 days ago
  • Sandboxed runNot runSkills are read, not executed; layer L4 is skipped

What it tells the agent

Full source on GitHub ↗

Its 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…

---
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:

```sh
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`:

```sh
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:

```sh
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`.

## Step 4 — Verify and Synthesize Verdict

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

```sh
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`).

Excerpt, first 3,619 characters of SKILL.md, verbatim from the audited commit. It is text from someone else’s repository, quoted so you can judge it before your agent reads it.

Install

Pinned to the audited commit a75fdcc

Download folder ↗
git clone https://github.com/poteto/noodle
git -C noodle checkout a75fdcc2eb73

The author documents no install command, so this uses the repository directly. Our verdict covers commit a75fdcc2eb73 only.

Works in which agents?

What its own text says, not a test

AgentStatusMore
CodexMentioned in its text, not testedSkills for Codex · About Codex
“Mentioned” means the skill’s text names the agent. We have not run it there.

Audit history

Every audit, every source change

  1. !CAUTION B 89 / 100

    first audit · source a75fdcc2eb73

README badge

For maintainers · shows the latest audit

ModelsAtlas: CAUTION BMODELSATLASCAUTION · B
[![ModelsAtlas: CAUTION B](https://modelsatlas.com/skills/poteto/adversarial-review/badge.svg)](https://modelsatlas.com/skills/poteto/adversarial-review/)

The badge shows our verdict and grade for this skill, and links back to this page. It changes when the audit does.

Add this badge to your README

[![ModelsAtlas: CAUTION B](https://modelsatlas.com/skills/poteto/adversarial-review/badge.svg)](https://modelsatlas.com/skills/poteto/adversarial-review/)

Questions about adversarial-review

What does the adversarial-review skill do?
Orchestrate agents using skills
Is adversarial-review safe to install?
With care. The audit graded it B (89/100) and found 3 things worth knowing before you trust this skill, listed below with the exact line each was found on.
What can adversarial-review access on my machine?
The audit observed no filesystem, network or shell use at all in its source.
Which assistants does adversarial-review work with?
Its documentation mentions codex. That is what the text claims, not a compatibility test we ran.
How current is this page?
The grade is for one exact copy of the source (a75fdcc2eb73), read on 2026-10-20. The repository is watched, and a new audit runs when it changes — this is the first audit.

Sources

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