magnus919_agent-skills/agent-evals-and-observability/references/source-index.md

Source and Status Index

Sources inform decisions; they become binding only when adopted by applicable policy, contract, or regulation. Versions and statuses were checked 2026-07-13 unless otherwise stated. Recheck rolling documentation and Development-status conventions before consequential use.

Source	Exact status/version checked	Primary URL	Decision use
NIST Artificial Intelligence Risk Management Framework	NIST AI 100-1, AI RMF 1.0, January 2023; NIST reports revision work underway	https://doi.org/10.6028/NIST.AI.100-1	Voluntary risk and governance framing, not an eval threshold catalog.
NIST AI RMF Generative AI Profile	NIST AI 600-1, July 2024	https://doi.org/10.6028/NIST.AI.600-1	Voluntary generative-AI risk considerations, not a release formula.
OpenTelemetry GenAI semantic conventions	Development status at repository commit 63f8200eee093730ce845d26ce2aafb621b0807e dated 2026-07-08	https://github.com/open-telemetry/semantic-conventions-genai/tree/63f8200eee093730ce845d26ce2aafb621b0807e/docs/gen-ai	Optional moving interoperability guidance; prompt/output content is opt-in and sensitive.
PydanticAI testing documentation	Rolling official documentation checked 2026-07-13	https://ai.pydantic.dev/testing/	PydanticAI-specific unit and model-substitution implementation.
Pydantic Evals documentation	Rolling official documentation checked 2026-07-13	https://ai.pydantic.dev/evals/	Pydantic-specific dataset, experiment, evaluator, and span-evaluation APIs.
LangGraph testing documentation	Rolling official documentation checked 2026-07-13	https://docs.langchain.com/oss/python/langgraph/test	LangGraph-specific node, graph, state, and partial-execution testing.
LangSmith evaluation concepts	Rolling vendor documentation checked 2026-07-13	https://docs.langchain.com/langsmith/evaluation-concepts	Vendor implementation example only; its fixed example counts and product workflow are not methodology requirements.
“Judging LLM-as-a-Judge with MT-Bench and Chatbot Arena”	Zheng et al., arXiv:2306.05685 v4, 2023-12-24	https://arxiv.org/abs/2306.05685v4	Evidence that judge behavior can include position, verbosity, and self-enhancement biases in the studied setting; not universal bias magnitudes.
“G-Eval: NLG Evaluation using GPT-4 with Better Human Alignment”	Liu et al., arXiv:2303.16634, 2023	https://arxiv.org/abs/2303.16634	Example of rubric-guided model judging; use as research context, not a universal judge protocol.
“SelfCheckGPT: Zero-Resource Black-Box Hallucination Detection for Generative Large Language Models”	Manakul et al., EMNLP 2023	https://aclanthology.org/2023.emnlp-main.557/	Consistency-based hallucination signal and its limits; not a factuality oracle.
“FActScore: Fine-grained Atomic Evaluation of Factual Precision in Long Form Text Generation”	Min et al., EMNLP 2023	https://aclanthology.org/2023.emnlp-main.741/	Claim-level factual precision framing; source attribution and domain limits remain decision-specific.
Ragas documentation	Rolling documentation; verify API and metric definitions before use	https://docs.ragas.io/	Named implementation example for RAG evaluation; metric names do not establish a release threshold.