Resolve Model

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

No annotations are provided, so the description carries full behavioral burden. It discloses that matching is deterministic and tolerates vague input, and it explains the three possible `status` values with what they mean (show candidates to user for needs_confirmation). This adds meaningful behavioral context beyond the schema. It could mention error handling or edge cases, but it covers the core behavior well.

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 two paragraphs, with the key directive front-loaded in the first sentence. The second paragraph adds essential usage guidance and status explanation. It is concise but not overly terse; every sentence contributes. Slight redundancy: 'Always check here' and the normalization details could be merged, but it's acceptable.

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?

There is an output schema (though not shown in this snippet) which likely documents the return structure, so the description doesn't need to explain return values. The description explains the statuses that are core to the tool's behavior. However, given the complexity of resolving vague input, the description could provide more detail on what constitutes 'vague' or examples, but it is adequate for an agent to understand when to use it and how it behaves.

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 compensate, but it doesn't elaborate on any parameters except 'identifier' (implicitly via 'identifier to resolve'). The description doesn't explain the purpose of `endpoint` or `platform`, even though they are optional and could influence resolution. That's a gap. However, the description mentions 'vague platform names' which hints at platform's role, but no parameter-specific details. Given 0% coverage, the description provides minimal help for parameters.

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 verb ('Match') and resource ('identifier against the local registry') and mentions its purpose of resolving vague input. It clearly indicates the tool normalizes variations like regional prefixes and version suffixes, which helps distinguish it from siblings like get_model_profile or compare_models, though it doesn't explicitly name a sibling.

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 explicitly instructs 'Always check here before researching a model', giving clear when-to-use guidance. It describes the normalization behavior (regional prefixes, version suffixes, spacing, vague platform names) that triggers the need for this tool, which is a strong usage context. It doesn't explicitly state when not to use it, but the directive is unambiguous.

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