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

No annotations are provided, so the description carries the full behavioral burden. It states the search intent but does not disclose whether the operation is read-only, what the return format is, whether it reports positions or counts, or any auth/rate-limit constraints.

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, front-loaded sentence with no redundant or wasted wording. It is appropriately sized for a simple one-parameter tool.

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?

For a simple scan tool with no annotations and no output schema, the description explains the purpose but omits return-value behavior and result interpretation. It is minimally adequate but leaves an agent guessing about output 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?

The schema has 0% description coverage for the single 'text' parameter, but the description implies that 'text' is the input to scan. It does not add details about expected format, size, or examples, so it only partially compensates for the schema gap.

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 gives a specific verb and resource: 'Find known model ids in text.' It also adds the condition 'deprecated or shutting down,' so the agent can understand the tool's scope. However, it does not explicitly distinguish itself from siblings like check_model or upcoming_shutdowns.

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 implies scanning text for deprecated model IDs but gives no explicit when-to-use guidance, no exclusions, and no comparison to sibling tools such as check_model or upcoming_shutdowns.

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