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

No annotations are provided, so the description carries the disclosure burden. It implies a read-only dataset query through the listed fields and optional filter, but does not explicitly state absence of side effects or describe result ordering/format beyond the field list.

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?

One compact sentence front-loads the resource, fields, filter behavior, and license. There is no redundant or wasteful text.

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 one-parameter lookup with no output schema, the description is complete: it identifies the dataset, enumerates returned attributes, and explains filter 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 already has 100% description coverage for the single model parameter. The description adds useful concrete examples ('PVM-20L5', 'BVM') that clarify substring matching behavior beyond the schema wording.

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 resource (Sony PVM/BVM/LMD monitor specifications) and enumerates the exact fields returned. It is clearly distinguishable from all sibling tools, none of which cover monitor hardware data.

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?

Explains that the model filter is optional and that omitting it returns all monitors, with concrete example filters. It does not name alternatives, but none of the sibling tools are plausible alternatives for this data.

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