Adversarial Review

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

a5c-ai Updated 1.7k repo stars

File contents

  • 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)

a5c-ai/babysitter/tree/main/library/methodologies/metaswarm/skills/adversarial-review commit b81f4a84b2

Frequently asked questions

npx skillmds@latest add a5c-ai/adversarial-review