“LLM evaluation”

Run and interpret the project's quality matrix after correctness and route gates are closed.

Merge MMI and DDD evaluation results — and the UX evaluation when it exists — into a unified improvement plan.

MLflow 3 GenAI agent evaluation.

Independently evaluate a native proposal with explained quality scores, coverage-limited novelty and a previously frozen blind baseline.

An ExpectationEvaluation records one open or closed window for an Expectation.

Open-source platform for tracing, evaluating and managing prompts for agents, LLMs and ML models

统一机会评估主链路、八维评分与 Gate；默认输出原生文档，不调用生图。

Use before research or engineering-research decisions: deciding whether to continue a direction, run an experiment, change route, interpret results, write a…

Evaluate the UX of an existing UI from its inventory — Nielsen's heuristics, WCAG 2.2, task efficiency, consistency, navigation — as a UX index with…

Evaluates a third-party repo, skill or plugin before importing it.

Use Hugging Face Evaluate to load metrics, comparisons, and measurements; compute and combine results; run evaluator pipelines; create custom modules…

Use when a request needs a baseline for one configuration to run, read, or iterate; not for a controlled comparison across multiple configurations (use…

Evaluate CampaignForge concepts, media, and channel drafts for brand fit, clarity, factual support, and platform readiness before final review.

Evaluates scientific figures for publication quality using VLM-as-a-judge.

Testing and benchmarking LLM agents including behavioral testing, capability assessment, reliability metrics, and production monitoring—where even top agents…

Use when asked how the labor-code assistant performs, to score it, or to review its golden set.

INVOKE THIS SKILL when building evaluation pipelines for LangSmith.

Testing and benchmarking LLM agents including behavioral testing, capability assessment, reliability metrics, and production monitoring—where even top agents…

Autonomous AI agent benchmark evaluation register: task completion rates, planning accuracy, tool invocation precision, and cost benchmarks.

Planejar avaliação de computação com baselines e validade.

End-to-end Torch LLM PTQ recipe for AMD Quark — for PyTorch / HuggingFace transformers models (safetensors input): quantize, then validate, then evaluate…

Open-source framework that builds, evaluates and self-improves multi-agent LLM workflows from a goal.

Evaluate DDD principle conformance across 3 layers and 12 criteria.

Qualitative evaluation of Modularity Maturity Index across 4 axes: cohesion, coupling, independence, reusability.