Agent skill · Audited from source
adversarial-review
skill · poteto/noodleMIT licenceAudited 20 Oct 2026 · source a75fdcc2eb73
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…
Cite
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
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
| Layer | What we check | Result | Findings |
|---|---|---|---|
L0 Provenance | Repo owner, licence, archive status, activity | WARN | 3 |
L1 Static source | Secrets, path traversal, supply chain, hidden code | NA | 0 |
L2 Instructions | Prompt injection, authority framing, hidden directives | PASS | 0 |
L3 Inventory | The files and declarations match the source | PASS | 0 |
L4 Sandbox | Run in isolation and watch behaviour | SKIPPED why | 0 |
Gates applied: no behavioural pass.
Findings (3)
MEDIUMInventory / provenanceinv.symlink · .claude/agents
.claude/agents
- Why
- link not followed
- Fix
- —
MEDIUMInventory / provenanceinv.symlink · .claude/hooks
.claude/hooks
- Why
- link not followed
- Fix
- —
MEDIUMInventory / provenanceinv.symlink · .claude/skills
.claude/skills
- Why
- link not followed
- Fix
- —
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
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
| Agent | Status | More |
|---|---|---|
| Codex | Mentioned in its text, not tested | Skills for Codex · About Codex |
Audit history
Every audit, every source change
- !CAUTION B 89 / 100
first audit · source
a75fdcc2eb73
README badge
For maintainers · shows the latest audit
[](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.
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Questions about adversarial-review
What does the adversarial-review skill do?
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Sources
- github.com/poteto/noodle/tree/main/.agents/skills/adversarial-re — the audited source at commit a75fdcc2eb73 and every finding aboveObserved · 20 Oct 2026
Spotted something wrong? Report a correction · Methodology
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Opens with this page as the source. We add nothing else to the prompt.
- What does the adversarial-review skill do?
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- What can adversarial-review access on my machine?