Adversarial review

Skill a5c-ai/babysitter/library/methodologies/metaswarm/skills/adversarial-review

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

Install

npx -y skills add a5c-ai/babysitter --skill adversarial-review

Assembled from the repository path, not quoted from the project. Check it against their README if it does not work.

SKILL.md

1.4 KB, 199 tokens by cl100k_base, as published. Nobody here has run it

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)

What ships with it: 1 file

627 B alongside SKILL.md

README.md627 B