probe_models

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

With no annotations provided, the description carries the full behavioral burden. It discloses the HTTP-route behavior, the difference between omitting and passing model, and the important nuance that an endpoint refusing the listing does not mean it cannot answer. This is substantive behavioral context.

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 compact, front-loaded with the core action, and each sentence earns its place: usage, parameter behavior, motivation, and an important caveat. No filler or redundancy.

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?

Given one optional parameter, an output schema, and no annotations, the description covers all essential context: what the tool does, which parameter selects what, when to rely on it, and how to interpret a refusal. Nothing critical is missing.

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 description must supply meaning for model. It does so clearly: pass model to probe one member, omit it to probe every configured member. This adds real semantic value beyond the bare enum/default in the schema.

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 opens with a specific verb + resource: ask a member's endpoint which model ids it exposes via the /models route. It clearly separates probe_models from siblings like ask or ask_all by focusing on endpoint/model-id discovery rather than answer 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?

It explicitly states when to use the tool: after an unknown-model error or to discover provider offerings. It also explains the parameter-driven choice between probing one member or all members, though it does not explicitly name alternatives or exclusion cases.

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