Use when designing, running, diagnosing, or selecting supervised fine-tuning rounds for coding-agent models. Especially useful for teaching output formats, action-chain imitation, strict tool JSON, project-building trajectories, checkpoint selection by generation quality, and stopping loss-only improvements that do not improve behavior.
