AI Engineer · November 6, 2026

Find hidden agent failures in tool traces before changing skills

video Model Evaluation AI Engineering Agent Security

Find hidden agent failures in tool traces before changing skills video thumbnail

Why it matters

Warp describes grading completed agent sessions using the conversation, tool calls and resulting changes together. Recurring failed commands can reveal obsolete setup instructions even when the agent eventually succeeds. A separate improvement step groups failures and proposes skill changes for review, with scores tracked over time. These model-based rubrics are diagnostic aids; a score increase alone does not establish causal improvement or code correctness.

My takeaway: Sample successful sessions as well as failed ones. Look for repeated port discovery, invalid commands and unnecessary retries, then link proposed instruction changes to specific traces. Review the patch and rerun representative tasks before accepting it; retain independent correctness checks alongside efficiency scores.

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