adversarial-panel

adversarial-panel is a Multi-agent review & consensus skill for AI agents, published by makinux in the adversarial-panel repository on GitHub. Skillspace rates adversarial-panel D (66/100) and it passed the safety scan; the rating is based on static analysis only.

Run a multi-model adversarial mutual review with facilitator synthesis — the "Fable 5-style" metacognition pattern, reproducible on Opus or any Claude model: 2+ panelists (different model families where possible) independently answer, adversarially critique each other across rounds, and the main session acts as facilitator, synthesizing agreements, live disagreements, and calibrated confidence into one answer. Use this whenever the user asks to debate or adversarially review a claim, hypothesis, design, decision, or answer with multiple models or perspectives; says things like "discuss with Opus and Codex", "get a second opinion", "red-team this", "devil's advocate", 敵対的レビュー, 相互レビュー, 多モデル討論, 合議, 議論させて; or wants a high-stakes answer with explicit uncertainty instead of a single-pass response. Also use proactively when the user challenges your confidence ("are you sure?") on something consequential.

Grade

D

Quality

66 / 100

Safety

Passed

GitHub stars

74

Unproven: rated by static analysis only, not yet compared head-to-head.

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