# Evals for llm-pipeline

`cases.yaml` is read by the repo's skill-eval harness. The `should_trigger` and `should_not_trigger` sets check routing precision — that orchestration/reliability/caching/cost-control requests land here, while prompt-wording goes to `prompt-engineering`, single schema-bound calls to `structured-extraction`, retrieval to `rag`, autonomous decision loops to `building-agents`, and spend dashboards to `cost-tracking`. The `capability` case checks that the agent produces a reliability-complete pipeline design (typed contracts between steps, timeouts, bounded retries, router fallback, the right caching choice, tier routing with an aborting budget cap, and per-step observability). Run it through the repo's eval runner the same way as the other skills; all cases are static-routing and design-rubric checks, so no live API calls or keys are required.
