If the model can't get the information it needs to accurately answer the question, it must surface that risk to you instead of guessing. This is part of model intelligence and tool use competency. Fable and to a lesser extent Opus is very good at this

It's both. Some models, given web search and web fetch may only run a search and assume the summary text is correct and blindly return it. Others will validate by running a web fetch and checking the whole page contents. Even better, the model will run multiple searches and fetches to cross check the information. The best models will attempt to verify whether a source is authoritative or not and try to only return authoritative results.

I have an example here: https://gist.github.com/nijave/2873b8b10d8c732e46264237b0755...

Tldr; all the Claude models had identical tools and some used them efficiently and verified data while others did a crap job and hallucinated responses. Additionally, Exa MCP tools generally worked better even on older/smaller model (Llama)