Token Scout FAQs

Question 1

What compatibility challenges does Token Scout solve for AI agents?

Accepted Answer

Token Scout addresses critical compatibility issues like tool format fragmentation (e.g., Anthropic vs. OpenAI), context window clipping, and reasoning tag corruption. It profiles every discovered model for these dimensions, ensuring your agent only routes to models that are perfectly compatible with the task requirements.

Question 2

Which LLM providers and models does Token Scout support?

Accepted Answer

Token Scout performs live discovery from a wide range of cloud providers including OpenRouter (28+ free models), Groq, Cerebras, Mistral, GitHub Models, and Google AI. It also automatically discovers and integrates with local Ollama instances running on your network, providing access to an even broader ecosystem of models.

Question 3

How does Token Scout help reduce LLM inference costs?

Accepted Answer

Token Scout helps significantly reduce costs by prioritizing free and low-cost LLM models. It performs live discovery of cheap options across various providers and allows agents to set a maximum cost per 1K tokens. This dynamic routing ensures your agent always picks the most economical viable model for each task.

Question 4

What is Token Scout and how does it benefit AI agents?

Accepted Answer

Token Scout is a powerful tool that enables AI agents to discover and route to the best available LLM inference endpoints in real-time. It filters models by compatibility (tool calls, context, reasoning), budget, and quota, ensuring your agents use the most efficient and cost-effective models without breaking workflows or exhausting provider limits.

Question 5

Does Token Scout add latency by acting as a proxy?

Accepted Answer

No, Token Scout operates without being a proxy or middleware. It simply provides your agent with the optimal model's ID and direct endpoint, allowing the agent to call the model directly. This design ensures zero latency tax and maximum efficiency.

Token Scout

Token Scout

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