[hbarka]

I agree with your example about a deterministic answer but what I’m looking for is deterministic process. I seek the LLM’s opinion, not a boolean answer. For example, having an agentic skill or hook to do a SWOT analysis may one day (out of 1000 consistent days) result in the agent just produce S-W-O and no T in the process because it was simply context muddled that day.

[anonym29]

In that case, you don't want to be using Claude Code, which is more of a consumer product; you instead want to control the inference stack yourself. What you are looking for is structured output (you give the inference engine a JSON schema you define that the response must conform to) + a JSON schema validator that parses the output, checks if the response is valid JSON. If it is, you're good to go, if not, run the inference again. llama.cpp supports structured outputs, as do some more consumer-oriented tools that wrap like LM Studio. If you don't want to buy hardware yourself or pay exorbitant cloud rental prices, p2p GPU rental marketplaces like vast.ai can offer much more economical options.