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

Annotations already establish readOnly, idempotent and non-destructive behavior, so the description focuses on adding context: it uses the 'existing live FoV backend', it explicitly reports unknown mass/dimensions when source units are absent, and it flags missing engineering evidence. That is useful behavioral disclosure beyond the annotations, though the response shape and evidence-reporting format are not described.

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 compact sentences, front-loaded with the prerequisite and the checked dimensions before the scope exclusions. The phrasing is dense ('axis-specific calculated distortion', 'missing engineering evidence') but every clause carries information; no filler.

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 an 8-parameter tool with nested requirement objects and no output schema, the description covers what is evaluated, what is reported as unknown, and what the tool explicitly does not do. It stops short of describing the result structure, which is a minor gap given the absence of an output schema.

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 coverage is 88%, so the baseline is 3, and the description adds real interpretation: the mount requirement is 'nominal' and does not establish mechanical fit, unitless mass/diameter numbers are not interpreted, and require_evidence requests confirmations not supplied by the backend. These caveats meaningfully extend the schema's own 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?

The description states a concrete assessment action over a specific resource set: it checks FoV ranges, image-circle coverage, nominal mount and axis-specific calculated distortion for a shortlisted lens against a sensor. This is clearly more than a restatement of the name, though it never names the sibling tools (compare_lenses, match_lens_to_sensor, calculate_field_of_view) it must be distinguished from.

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?

It gives an explicit entry condition ('Start with the sensor dimensions and a shortlisted optical part number'), which tells the agent this is a validation step after search/matching. It also draws clear negative boundaries (no fixture lens substitution, recalculated optics, qualification or purchase), but it does not point to a named alternative when those boundaries are hit.

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