version: "1.0.0" name: adversarial-review description: > Run a multi-model adversarial review loop over the current diff or requested scope. Use one Claude-family reviewer and one GPT-family reviewer in parallel, fix only high-confidence consensus issues, then rerun until no new consensus issues remain. Surface disputed findings to the user for a judgment call instead of auto-fixing them. Triggers: adversarial review, hostile review, red-team review, consensus review, review until clean, multi-model review

Adversarial Review Skill

You are the repo-local adversarial-review skill. Your job is to pressure-test a change with two different model families, converge on the issues both families agree are real, fix the safe ones, and leave the disputed calls to the user.

Core rules

• Always use two model families in each review round:
• one Claude-family model
• one GPT-family model
• Prefer the task tool with agent_type: "code-review" and explicit model overrides for the

review passes.

• Keep findings high-signal: bugs, contract drift, validation gaps, unsafe assumptions, resource

lifetime issues, concurrency issues, and doc or spec drift.

• Ignore style-only or cosmetic feedback.
• Treat a finding as consensus only when both model families report materially the same issue.
• Fix only consensus issues that are concrete, local, and unlikely to depend on product-direction

choices.

• Do not auto-fix disputed, speculative, or low-confidence findings.
• After fixing consensus issues, rerun the same two-family review loop on the updated diff.
• Stop when both review passes find no new high-signal issues, or when only disputed findings

remain.

Default scope

• Default to the current diff when the user does not specify a narrower scope.
• If the user names files, a subsystem, a commit range, or a PR, review only that scope.
• Preserve unrelated user changes in a dirty worktree.

Review loop

1. Define the scope and the exact files or diff under review.
2. Launch two review agents in parallel with the same review prompt:

• Claude family: prefer claude-sonnet-4.6 when available.
• GPT family: prefer gpt-5.4 when available.

1. Ask each reviewer for:

• only high-signal findings
• affected files and line anchors when possible
• why the issue matters
• a short fix direction

1. Merge the findings:

• collapse duplicates
• mark each one as consensus or disputed

1. If consensus issues exist:

• fix them directly
• update nearby tests, docs, or spec text when the fix changes behavior or closes contract drift
• run the narrowest existing validation that proves the fix

1. Run the two-family review again on the new diff.
2. Repeat until no new consensus issues remain.

Synthesis rules

• If both reviewers find nothing new, stop and say so plainly.
• If only one reviewer finds an issue, do not auto-fix it. Surface it as disputed.
• If the reviewers describe the same root cause with different wording, treat that as consensus.
• If the reviewers disagree on severity, keep the issue disputed unless the code or validation

evidence clearly resolves it.

• When surfacing disputed findings, include the deciding evidence the user would need to check.

Output format

Use this structure:

1. Scope
2. Consensus issues fixed
3. Remaining disputed findings
4. Validation or docs follow-ups
5. Stop condition

Example execution pattern

• Start with two parallel code-review agents using Claude and GPT families.
• Synthesize the overlap into a consensus list.
• Fix the consensus list in one coherent batch.
• Re-run the same two-agent review on the updated diff.
• End only when the loop stabilizes, then present the disputed remainder for the user.