Explain how the effort parameter governs Claude Opus 5's output beyond just reasoning?

Effort doesn't only scale how much internal reasoning Claude Opus 5 performs before answering - it governs essentially every token the model produces during a turn, including the depth of tool calls it makes and how much elaboration goes into constructing tool arguments, not just the thinking block itself.

This means two requests with identical prompts but different effort levels can differ meaningfully not just in how thorough the final answer feels, but in how many tool calls get made, how carefully each call is reasoned through before being issued, and how much total token volume the whole turn consumes end to end.

Practically, this is why Anthropic recommends running an effort sweep against your own evaluation suite when tuning Opus 5, rather than assuming a single effort level that worked well on a narrower notion of reasoning depth will also be the right choice once its effect on tool-calling behavior and total token cost is accounted for.

It also explains why effort and response verbosity are separate levers that don't move together: since effort's influence is concentrated in thinking, tool calls, and argument construction rather than the final visible reply's wording, controlling the two independently - effort via the parameter, length via explicit prompt instructions - is necessary to get both dialed in correctly.

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