reseed-performance-baseline

reseed-performance-baseline is an MLOps & model serving skill for AI agents, published by hao-ai-lab in the FastVideo repository on GitHub. Skillspace rates reseed-performance-baseline D (61/100) and it passed the safety scan; the rating is based on static analysis only.

Re-seed the HF performance-tracking baseline for an intentional runtime, dependency, environment-caused benchmark shift, or reviewed v2 calibration using one or more reviewed normalized performance JSONs. Use when performance CI fails because metrics such as latency, throughput, component time, or peak memory changed for an accepted reason and the rolling median baseline in FastVideo/performance-tracking must be advanced, or when a new v2 exact comparable identity needs its first approved baseline. The workflow backs up existing history under /tmp, validates all source JSONs for the same legacy (model_id, gpu_type) target or the same v2 exact identity, rejects internally inconsistent source batches, uploads one success=true baseline record per accepted source JSON, and offers to clean local temp state after a successful upload.

Grade

D

Quality

61 / 100

Safety

Passed

GitHub stars

4,385

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

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