Agent Skills: adversarial-review

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

UncategorizedID: a5c-ai/babysitter/adversarial-review

Install this agent skill to your local

pnpm dlx add-skill https://github.com/a5c-ai/babysitter/tree/HEAD/library/methodologies/metaswarm/skills/adversarial-review

Skill Files

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library/methodologies/metaswarm/skills/adversarial-review/SKILL.md

Skill Metadata

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