
Adversarial Review
- 1.1k installs
- 217 repo stars
- Updated March 19, 2026
- poteto/noodle
adversarial-review is an agent skill that runs three specialized adversarial reviewer agents—Architect, Skeptic, and a third lens—to stress-test architecture, correctness, and simplicity before merging code.
About
adversarial-review is a poteto/noodle agent skill that orchestrates three distinct adversarial reviewer perspectives on a proposed change before merge. The Architect lens challenges structural fitness, coupling points, boundary violations, and scale assumptions. The Skeptic lens probes correctness, missing edge cases, and failure sequences. A third specialized lens rounds out the review with additional adversarial scrutiny described in the noodle reviewer-lenses framework. Developers reach for adversarial-review when a standard friendly PR review is insufficient and they want deliberate pushback on design decisions, implicit assumptions, and simplification opportunities. Findings map to tags like boundary-discipline and redesign-from-first-principles.
- Three distinct adversarial reviewer lenses: Architect, Skeptic, and Minimalist
- Architect lens maps findings to boundary-discipline, foundational-thinking, redesign-from-first-principles
- Skeptic lens maps findings to prove-it-works, fix-root-causes, serialize-shared-state-mutations
- Minimalist lens maps findings to subtract-before-you-add, outcome-oriented-execution, cost-aware-delivery
- Hard-gate review that surfaces structural, correctness, and complexity issues before code reaches production
Adversarial Review by the numbers
- 1,107 all-time installs (skills.sh)
- +25 installs in the week ending Aug 5, 2026 (Skillselion tracking)
- Ranked #107 of 1,352 Code Review & Quality skills by installs in the Skillselion catalog
- Security screen: CRITICAL risk (skills.sh audit)
- Data as of Aug 5, 2026 (Skillselion catalog sync)
npx skills add https://github.com/poteto/noodle --skill adversarial-reviewAdd your badge
Show developers this skill is listed on Skillselion. Paste this into your README.
| Installs | 1.1k |
|---|---|
| repo stars | ★ 217 |
| Security audit | 1 / 3 scanners passed |
| Last updated | March 19, 2026 |
| Repository | poteto/noodle ↗ |
How do you adversarially review code before merging?
Run three specialized adversarial reviewer agents that stress-test architecture, correctness, and simplicity before merging.
Who is it for?
Engineers submitting significant PRs who want structured pushback on design, edge cases, and unnecessary complexity before merge.
Skip if: Trivial one-line fixes or teams that only need lint/format checks without architectural debate.
When should I use this skill?
The user requests adversarial, pre-merge, or multi-perspective code review on a diff, PR, or architecture proposal.
What you get
A multi-lens adversarial review report with architecture, correctness, and simplicity findings mapped to action tags.
- Multi-lens adversarial review report
- Tagged findings for architecture and correctness issues
By the numbers
- Uses 3 distinct adversarial reviewer lenses
Files
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/nullUse --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" > "$REVIEW_DIR/skeptic.md" 2>/dev/nullRun with run_in_background: true.
Name each output file after the lens: skeptic.md, architect.md, minimalist.md.
Build each reviewer's prompt using the template in references/reviewer-prompt.md.
Step 4 — Verify and Synthesize Verdict
Before reading reviewer output, log which CLI was used and confirm the output files exist:
echo "reviewer_cli=codex|claude"
ls "$REVIEW_DIR"/*.mdIf 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).
Reviewer Lenses
Three distinct adversarial perspectives. Each reviewer adopts one lens exclusively.
Architect
Challenge structural fitness. Ask:
- Does the design actually serve the stated goal, or does it serve a goal the author assumed?
- Where are the coupling points that will hurt when requirements shift?
- What boundary violations exist? Where does responsibility leak between components?
- What implicit assumptions about scale, concurrency, or ordering will break first?
Map findings to: boundary-discipline, foundational-thinking, redesign-from-first-principles.
Skeptic
Challenge correctness and completeness. Ask:
- What inputs, states, or sequences will break this?
- What error paths are unhandled or silently swallowed?
- What race conditions or ordering dependencies exist?
- What does the author believe is true that isn't proven?
- Where is "it works on my machine" masquerading as verification?
Map findings to: prove-it-works, fix-root-causes, serialize-shared-state-mutations.
Minimalist
Challenge necessity and complexity. Ask:
- What can be deleted without losing the stated goal?
- Where is the author solving problems they don't have yet?
- What abstractions exist for a single call site?
- Where is configuration or flexibility added without a concrete second use case?
- Is this the simplest possible path to the outcome, or is it the path that felt most thorough?
Map findings to: subtract-before-you-add, outcome-oriented-execution, cost-aware-delegation.
Reviewer Prompt Template
Each reviewer gets a single prompt containing:
1. The stated intent (from Step 2) 2. Their assigned lens (full text from references/reviewer-lenses.md) 3. The principles relevant to their lens (file contents, not summaries) 4. The code or diff to review 5. Instructions: "You are an adversarial reviewer. Your job is to find real problems, not validate the work. Be specific — cite files, lines, and concrete failure scenarios. Rate each finding: high (blocks ship), medium (should fix), low (worth noting). Write findings as a numbered markdown list to your output file."
Spawn all reviewers in parallel.
Verdict Format
## Intent
<what the author is trying to achieve>
## Verdict: PASS | CONTESTED | REJECT
<one-line summary>
## Findings
<numbered list, ordered by severity (high -> medium -> low)>
For each finding:
- **[severity]** Description with file:line references
- Lens: which reviewer raised it
- Principle: which brain principle it maps to
- Recommendation: concrete action, not vague advice
## What Went Well
<1-3 things the reviewers found no issue with -- acknowledge good work>
## Lead Judgment
<for each finding: accept or reject with a one-line rationale>Verdict Logic
- PASS — no high-severity findings
- CONTESTED — high-severity findings but reviewers disagree on them
- REJECT — high-severity findings with reviewer consensus
Related skills
How it compares
Choose adversarial-review over single-pass review skills when a change needs deliberate architectural and correctness challenge, not just style or lint feedback.
FAQ
What reviewer lenses does adversarial-review use?
adversarial-review applies three adversarial lenses: Architect challenges structural fitness and coupling, Skeptic probes correctness and edge cases, and a third specialist lens adds further adversarial scrutiny before merge.
When should developers invoke adversarial-review?
adversarial-review suits significant pull requests or architecture changes that need deliberate pushback before merge. Skip it for trivial fixes that only require lint or formatting checks.
Is Adversarial Review safe to install?
skills.sh reports 1 of 3 security scanners passed. Review the Security Audits panel on this page before installing in production.