Recommend Models

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

With no annotations, the description carries the behavioral disclosure burden. It does reveal meaningful traits: 'hard-filter' implies exclusion of incompatible models and 'deterministically rank' implies reproducible ordering. However, it does not clarify what 'compatible' means, how ranking works, or whether the operation is read-only.

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 a single efficient sentence with no filler, and the key behavioral terms are front-loaded. It is appropriately concise, though it sacrifices useful guidance for brevity.

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 10 optional parameters, no annotations, and no parameter descriptions, this one-sentence description is insufficient for an agent to call the tool correctly. It does not explain filtering criteria, ranking rationale, or how parameters interact, and the presence of an output schema does not compensate for missing input semantics.

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 description adds no parameter-level meaning. Some parameter names like region, platform, and provider are self-explanatory, but others such as migration_goal, application_path, and source_platform remain ambiguous with no description support.

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 states a specific action—'hard-filter and deterministically rank'—and a clear resource, 'compatible registry models.' It conveys the tool's core function, though it does not explicitly distinguish it from siblings like compare_models or resolve_model.

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?

The description gives no guidance on when to use this tool versus alternatives such as compare_models, resolve_model, or get_model_profile. There are no usage scenarios, prerequisites, or exclusions, leaving the agent to infer appropriateness from the name alone.

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