tool description wording does matter, at least in my testing. models seem to use the description to reason about whether a tool "should" apply, not just whether it can. two things that helped: (1) explicit input format with an example, (2) a one-sentence note about what the tool does NOT handle. the negative case helps models avoid calling it on edge cases and then failing, which trains them (in context) to prefer it when it's actually the right fit.