AI agent skill · by @a5c-ai

Adversarial Review

Fresh adversarial code review with binary PASS/FAIL verdicts, evidence citations, and anchoring bias prevention via fresh reviewer spawning.

Archived 2026-10-23 · Source updated 2026-09-16 · License: MIT. Check the original repository for the latest version.

SKILL.md instructions

- For final comprehensive cross-unit review
- When verifying spec compliance of any implementation

## Key Differences from Collaborative Review

| Aspect | Collaborative | Adversarial |
|--------|--------------|-------------|
| Goal | Help improve code | Verify spec compliance |
| Verdict | Suggestions | Binary PASS/FAIL |
| Evidence | Optional | Required (file:line) |
| Reviewer | Can be reused | Must be fresh |
| Context | Shared | Independent |

## Fresh Reviewer Rule

On re-review after FAIL, a NEW reviewer instance spawns with no memory of the previous review. This prevents anchoring bias where a reviewer fixates on previously identified issues.

## Anti-Patterns

- Reusing reviewers after FAIL
- Passing previous findings to new reviewers
- Providing subjective or advisory feedback
- Accepting partial compliance as PASS

## Tool Use

Invoke as part of: `methodologies/metaswarm/metaswarm-execution-loop` (Phase 3)