Evaluation-first fits
- benchmarking prompts or models
- tracking regressions over time
- measuring quality distributions
Evals judge the output. Correction repairs the workflow.
People comparing LLM evals with correction workflows are usually deciding whether they need benchmark-style measurement, or an operational loop that can recover from hallucination, role drift, and fake completion.
VeriClaw belongs on the correction side: it helps teams move from evidence to intervention and then verify the redo before sign-off.
Choose evals when
Evals matter for quality measurement and regression tracking. They are not the same as live correction after an agent claims work is complete.
Correction-first fits
- recovering from false completion
- reviewing evidence after drift
- re-opening work that was closed too early