Linting Prompts Before Model Calls Can Cut Wasted AI Pipeline Runs

A developer discovered that repeated failures in an AI pipeline were caused by a flawed, ambiguous prompt rather than the model itself, with the same bad instruction triggering multiple unnecessary calls. The insight prompted a shift in focus: checking prompt quality before any model call is made, not after reviewing model output. To enforce this, a lightweight Python linter was built to verify that each prompt file includes a defined role, constraints, and output format, while flagging vague phrases like 'do your best'. The linter runs as a deterministic CI stage in GitLab, blocking the pipeline before any model quota is consumed if a prompt fails the structural check. The approach treats prompts as versioned contracts, arguing that static validation of inputs is a cheaper and more reliable first gate than relying on model retries to surface bad instructions.