chat_completion

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

With no annotations, the description carries the full disclosure burden, and it does add real value beyond the schema: the underlying endpoint, the non-streaming guarantee, and the fact that content plus usage are returned. It omits auth/API-key requirements, rate limits, error behavior, and whether tool calls are honored, which matter for a remote LLM invocation.

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 compact clauses, front-loaded with the operation type and endpoint, with zero filler. Every fragment conveys something the caller can act on.

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 partially covers outputs ('assistant content and usage') which is valuable given no output schema, but with 7 parameters at 43% coverage and no annotations, a caller still lacks guidance on tuning parameters, error handling, or auth. Adequate as a minimum-viable definition, not complete.

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 coverage is only 43%, so the description should compensate but instead says nothing about the seven parameters — no mention of temperature/top_p tuning, max_tokens, stop sequences, or the tools array. The only useful parameter hint (model comes from list_models) lives in the schema, not the description.

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+resource (non-streaming chat completion) and anchors it to a concrete endpoint (POST /v1/chat/completions). The 'non-streaming' qualifier implicitly separates it from a streaming variant, though it doesn't explicitly reference the only sibling, list_models, which is trivial anyway.

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?

Usage is only implied: 'stream=false' signals this is the choice when you do not want a streamed response, but there is no explicit when-to-use/when-not-to-use statement or pointer to alternatives for token budgeting or model selection. The agent must infer the operating context.

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