openai_inspect_model

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

No annotations are supplied, so the description carries the full burden. It does disclose a meaningful trait beyond the name: the result combines a live API probe with locally documented data, implying a network call and a merged response. It does not state that the tool is read-only, what happens when the model is unknown or unreachable, or whether the live check can fail independently of the local data.

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?

One compact sentence with no filler, and the dual-source framing is front-loaded. The phrase "live API visibility" is somewhat abstract jargon that could be plainer, which keeps it from a 5.

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 the description need not explain return values, and the one-parameter surface is small. However, the identifier format is undocumented and the relationship to openai_get_model is unresolved, leaving gaps an agent must guess at before calling.

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% and the single required parameter model_id has no title beyond its key. The description never explains the expected identifier format (e.g., a canonical OpenAI model name versus a local alias) or whether unknown IDs are tolerated. For the one input the agent must supply, this leaves real ambiguity.

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 pairs a specific verb ("Inspect") with a specific resource (a model) and names the two information sources it merges: live API visibility and locally documented capabilities/endpoints. That is materially more informative than the bare name. It stops short of distinguishing itself from the sibling openai_get_model, so an agent cannot tell from the text alone which of the two 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 guidance, no exclusions, and no reference to any alternative. With openai_get_model, openai_list_models, and openai_recommend_model all in the sibling set, the description should say when inspection is preferable to a plain metadata fetch. The agent is left to infer usage from the word "inspect".

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