Adversarial review

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

Babysitter enforces obedience on agentic workforces and enables them to manage extremely complex tasks and workflows through deterministic, hallucination-free self-orchestration

Install

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

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What its author says it does

Copied from the file, not written here

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

SKILL.md

1.4 KB, 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