Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations, the description fully carries behavioral details: it is free, returns only the latest observation, and uses substring matching. It also discloses the return fields and timestamp, making behavior transparent.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is packed but not bloated; every sentence adds value. It is front-loaded with 'FREE' and key output fields, but a bit long and could be tightened without losing clarity.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

The description explains the output fields (per-token prices, timestamp), usage context, and provides cross-references and hints. It fully covers what an agent needs to know to decide when to use this tool and what results to expect, despite lacking an output schema.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The description explains model_id's substring behavior but entirely omits the 'limit' parameter. Since schema coverage is 0%, it should explain both parameters; the limit's purpose (likely result cap) is not mentioned.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool's function: retrieving current per-token prices for LLMs, with specific fields listed. It distinguishes itself from siblings by explicitly noting it returns current prices and not price movements, with alternatives named.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

Provides explicit use cases ('check what a model costs right now, or compare a handful of models') and anti-use cases ('Do NOT use it to see how a price MOVED'), pointing to specific alternative tools. Also explains substring matching and how to resolve exact IDs.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.