chat

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

No annotations are provided, so the description must carry the burden. It discloses the return value (assistant reply text) but does not mention side effects, rate limits, auth, or error behavior. For a simple chat tool this is acceptable but not rich.

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?

Two sentences with zero waste. The purpose and return type are front-loaded, and the example provider list adds value without bloat.

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?

For a simple chat tool with 4 well-described params and no output schema, the description covers the return type and scope. Nothing critical is missing for an agent to call it correctly, though it could mention streaming or multi-turn if relevant.

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?

Schema description coverage is 100% – all four parameters have descriptions. The description adds no additional meaning beyond the schema, so baseline 3 applies. The examples in the schema are sufficient.

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?

States a specific verb (chat/text completion) and resource (any LLM on apimodels.app) and explicitly lists example providers. Clearly distinguishes from siblings like generate_image and text_to_speech by focusing on text generation.

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?

Implies usage for text-based chat and completion, and the sibling tool names (generate_image, generate_video, text_to_speech) make the boundary obvious. However, it does not explicitly state when not to use it or name alternatives for text tasks.

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