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No \"looks good\" allowed. Adopts a cynical stance — assume problems exist and find them.\n\n## How It Works\n\n1. **Read content** with a cynical, critical perspective\n2. **Identify issues** across completeness, correctness, and quality\n3. **Search for what's missing** — not just what's present and wrong\n4. **Minimum threshold** — Must find 10+ issues or re-analyze deeper\n\n## Usage\n\n```\nbmad-review-adversarial-general [content]\n```\n\nExample:\n```\nbmad-review-adversarial-general src\u002Fstore\u002FtradingStore.ts\n```\n\n## Review Dimensions\n\n- **Completeness** — What's missing? Edge cases? Error handling?\n- **Correctness** — Does it do what it claims? Are there bugs?\n- **Quality** — Is the code clean? Are there code smells?\n- **Security** — Are there vulnerabilities?\n- **Performance** — Are there inefficiencies?\n- **Maintainability** — Will future developers understand this?\n\n## Output Format\n\n```markdown\n## Adversarial Review: [Artifact]\n\n### Findings\n\n1. **[SEVERITY]** — [Location] — [Description]\n2. **[SEVERITY]** — [Location] — [Description]\n...\n\n### Summary\n- Critical: N\n- High: N\n- Medium: N\n- Low: N\n\n### Recommendations\n[Prioritized action items]\n```\n\n## Human Filtering Required\n\nThe AI is instructed to find problems, so it will find problems even when they don't exist. **You decide what's real.** Review each finding, dismiss false positives, fix what 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