“LLM evaluation”

End-to-end LLM accuracy evaluation on AMD ROCm (ROCm-only) — container setup, vLLM/SGLang/ATOM serving, lm-eval / lighteval / evalscope benchmarks.

End-to-end LLM accuracy evaluation on AMD ROCm (ROCm-only) — container setup, vLLM/SGLang/ATOM serving, lm-eval / lighteval / evalscope benchmarks.

Attach judges to config variations for automatic LLM-as-a-judge evaluation.

Use Langfuse for LLM observability and evaluation and look up Langfuse documentation.

Use after completing any non-trivial task.

Use after completing any non-trivial task

INVOKE THIS SKILL when building evaluation pipelines for LangSmith.

Self-rate a completed non-trivial task on accuracy, completeness, clarity, actionability, and conciseness, with evidence per axis and a 1-5 scorecard.

Use after completing any non-trivial task.

The run-evaluator's procedure — compute metrics, judge reasoning/missing-tools, write the eval report, open an eval PR.

Score prompts for prompt injection with TypeSafe's Jev before they reach an LLM: a reference gate function a backend can call (allow / review / block with a…

Audits any landing or service page across 48 checks in 10 categories for LLM/AI discoverability, GEO readiness, content clarity, schema markup, internal…

Use when the user wants to test, compare, or choose local Ollama models for their machine.

Bulk-evaluate a folder of resumes against one job description and flag the ones whose wording mirrors the posting closely enough that a human should look…