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

With no annotations, the description carries the full burden and handles it well: it discloses the $0.10 cost, the honest 'unknown: not in catalog' per-id behavior, and the any_action_needed aggregation rule. It does not detail exact response fields or error behavior, but the core operational traits are clear.

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?

Three dense sentences with no filler: cost is front-loaded, behavior is specific, and the use case is provided last. Every sentence earns its place.

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 single-parameter batch status tool, the description gives enough to invoke it and interpret the result: input, per-id outcome, unknown handling, and the boolean gate. Minor gaps around exact entry shape and error conditions remain, but the tool is not complex enough to require more.

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 100%, so the parameter is already documented. The description adds context ('signed catalog', 'pinned-model set') that clarifies intent, but does not provide essential meaning beyond the schema, so the baseline 3 applies.

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?

States a specific verb ('Look up'), a resource ('model ids in the signed catalog'), and a precise output ('one entry per id... plus any_action_needed'). It also distinguishes itself from a per-item lookup flow by emphasizing the batch, single-answer design.

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?

Explicitly frames the intended use case: a CI pipeline's pinned-model set, producing one signed answer and one boolean to gate a build. It contrasts with 'parsing an array of free lookups by hand', giving clear context, though it does not name a specific alternative tool or list exclusion criteria.

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