This skill should be used when a user wants to (a) audit the quality and reliability of an existing LLM evaluation suite, or (b) determine which Claude model and inference parameters give the best quality-per-dollar and quality-per-second for their specific task by running a parameter sweep over tha
This skill should be used when a user wants to (a) audit the quality and reliability of an existing LLM evaluation suite, or (b) determine which Claude model and inference parameters give the best quality-per-dollar and quality-per-second for their specific task by running a parameter sweep over that eval. Applicable to any eval framework (custom harnesses, tau-bench, inspect-ai, pytest-based, etc
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