adversarial-crosscheck

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

Take a prompt or task the user is about to give Claude — especially a judgment they're invested in ("is this plan sound?", "review my design", "should we adopt X?", "poke holes in this", "am I fooling myself here?") — and run it through two opposing rewrites in clean contexts (a neutralised pass and a disowned-and-inverted adversarial pass), then present both for the user to reconcile. Use this whenever the user wants to pressure-test their own thinking, worries they're being flattered or agreed-with, asks to "red-team", "cross-check", "steelman against", or "sanity-check" something, or hands over work they clearly want to succeed and asks for an honest assessment. It counters sycophancy by widening coverage — it does NOT produce a single "unbiased" or "debiased" answer, and it deliberately refuses tasks it can't honestly automate.

Grade

D

Quality

66 / 100

Safety

Passed

GitHub stars

28

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

Our two independent classifiers differ on this skill's category, so treat the placement as provisional.

This rating describes the version of the repository we crawled; it may have changed since, so go by its current files.

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