self-consistency-check

self-consistency-check is a Multi-agent review & consensus skill for AI agents, published by UnpaidAttention in the fable5-methodology repository on GitHub. Skillspace rates self-consistency-check D (68/100) and it passed the safety scan; the rating is based on static analysis only.

Force the combination step that a weaker model can't do in one pass — surface conflicts between constraints, and interactions between requirements and edge cases, using a pairwise sweep, a fresh-context cold read by a subagent that never saw your reasoning, and N-version divergence on the hard kernel. Trigger this after producing a plan, design, spec, or multi-constraint solution and BEFORE committing to it — especially when the task carries more than ~3 interacting constraints, a schema/interface decision, or high stakes. Do NOT trigger for a single-constraint or trivial task (17.3 tiers say skip it), for reviewing an already-written code diff (that's code-review), or for verifying tests ran (that's verification-and-review). This skill checks that the DESIGN is internally consistent before code exists.

Grade

D

Quality

68 / 100

Safety

Passed

GitHub stars

83

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

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