I want to create a "harness" that does this with Claude Code and other expensive agents.
Buffer user prompts, use conversation history and repo state as context -- and run a local model or a cheap and fast cloud model like Haiku to determine the optimal way to address the user's ask, reframe the query with better context (user reviews and approves if needed) and THEN let expensive models like Opus have a go at it.
If we are operating within Anthropic ecosystem with Haiku and Opus -- this sort of logic should ideally be doable within Claude Code as harness. Currently skills cannot be tagged to different models. Ideally we should be able to say -- for trivial tasks, the skill should always use Haiku even if invoked from a session with Opus xhigh.
Buffer user prompts, use conversation history and repo state as context -- and run a local model or a cheap and fast cloud model like Haiku to determine the optimal way to address the user's ask, reframe the query with better context (user reviews and approves if needed) and THEN let expensive models like Opus have a go at it.
If we are operating within Anthropic ecosystem with Haiku and Opus -- this sort of logic should ideally be doable within Claude Code as harness. Currently skills cannot be tagged to different models. Ideally we should be able to say -- for trivial tasks, the skill should always use Haiku even if invoked from a session with Opus xhigh.