AI Agent Skills

Verify implementation matches change artifacts. Use when the user wants to validate that implementation is complete, correct, and coherent before archiving.

Audit brittle or tautological tests and, when cleanup is authorized, delete or rewrite them around independently specified behavior.

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After fixing a bug, find and rate other instances of the same pattern in the codebase. Two modes: described, or inferred from a recent fix with self-validation. Triggers…

Use when reconciled multi-agent output needs an evidence-based PASS, CONDITIONAL PASS, or FAIL record before authorized delivery.

Use when an agent task needs bounded context packets, checkpoint-aware compaction, a fresh-session primer, or policy-controlled child results without loading raw logs in…

Use when a consequential decision has genuinely competing positions that need bounded adversarial review before a human decision.

Use when multiple agent results must be checked for missing evidence, scope drift, contradictions, and merge conflicts before an acceptance decision.

Use when one agent must iteratively plan, act, evaluate evidence, and revise under a readable policy until acceptance, checkpoint, stop, or human escalation.

Use when a user asks to inspect coordination memory, propose a durable decision or resolution, review pending memory proposals, or apply an explicitly approved proposal…

Use when a goal needs multiple bounded agent roles, parallel or dependent task packets, explicit scope partitions, and a provider-neutral DAG. Not for research-domain ro…