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Earlier quoted context omitted.
And LLMs will get more accurate. What happens when the LLM uses the wrong parameters? If it's an immediate error then it will just try again, no need for protocol changes, just better LLMs.
The difference between 99% reliability and 100% reliability is huge in this case.
Earlier quoted context omitted.
The difference between 99% reliability and 100% reliability is huge in this case.
I misunderstood the problem then, I thought it would take only a few seconds for the LLM to issue the call, see the error, fix the call.
I didn’t find it entertaining.
In this situation, I would have a tool called "request ability to edit GLTF". I This would trigger an addition to the tool list specifically for your desired GLTF. The model would send the "tool list changed' notification and now the LLM would have access.
If you want to do it without the tool list changed notification ability, I'd have two tools, get schema for GLTF, and edit GLTF with schema. If you note that the get schema is a dependency for edit, the LLM could probably plumb that together on it's own fairly well
You could probably also support this workflow using sampling.
I have a blog post here that has an example of dynamically changing the tool list- https://jonwoodlief.com/rest3-mcp.html . In this situation, I would have a tool called "request ability to edit GLTF". I This would trigger an addition to the tool list specifically for your desired GLTF. The model would send the "tool list changed' notification and now the LLM would have access. If you want to do it without the tool l…