openai_get_model

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

No annotations are supplied, so the description carries the full behavioral burden, yet it only states the endpoint path. It does not disclose auth requirements, error behavior for an unknown or inaccessible model_id, whether any data is modified, or what the record contains beyond 'model record'. The GET path is the only behavioral signal, and it is a weak one.

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?

A single front-loaded sentence with no filler or repetition. It is efficient, though the terseness borders on under-specification given the overlapping siblings.

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?

An output schema exists, so return-value detail is fairly excused, and the single required parameter is self-evident. The remaining gap is the absence of any annotation context or sibling disambiguation, which matters because two other tools in this server also operate on a single model.

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 0%, so the only meaning for model_id comes from the description's {model_id} path template, which at least tells the agent it is a path identifier for a specific model. It adds nothing about accepted identifier forms (e.g. whether names like 'gpt-4o' work versus internal ids), which is the one detail that would actually have helped.

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 uses a specific verb ('Retrieve') and resource ('one model record') and even cites the underlying endpoint GET /v1/models/{model_id}, which makes the operation unambiguous. It implicitly separates itself from openai_list_models by saying 'one model record', but it never distinguishes itself from the sibling openai_inspect_model, leaving a real ambiguity about which single-model tool to pick.

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?

There is no explicit when-to-use or when-not-to-use guidance; the agent must infer that this is the lookup-by-id tool. The sibling list contains openai_inspect_model and openai_recommend_model, both plausibly overlapping with this one, and the description offers no routing rule between them.

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