get_lighting_quality

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

Annotations already declare readOnly/idempotent/non-destructive, but the description adds real behavioral context beyond them: exactly what is counted (type, mobility, shadow casters, intensity stats), what is excluded (sky lights), that the score is a heuristic rather than a measure of built lighting, and that nothing is built. This is unusually rich disclosure.

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?

Front-loaded with purpose, scope, and routing before the caveats and field list. It is dense and mostly earns its length, though the long enumerated return-field list is verbose – justified here only because no output schema exists.

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?

Given a zero-param, no-output-schema tool, the description covers scope, exclusions, the meaning of the computed score, sibling routing, and an explicit list of returned fields. Nothing an agent needs to call this correctly is missing.

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 tool takes zero parameters, so there is nothing to disambiguate; baseline 4 applies. The description instead documents the many return fields, which compensates for the absent output schema.

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+resource ('Read-only census of the actors with a light component') and pins the scope precisely ('first world context, normally the editor level'). It also names the sibling tools it is not, so an agent can distinguish it without opening schemas.

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 routes the agent: 'For one light use get_light_properties, for lights near a point get_lighting_in_area.' It also sets expectations about what the score means and explicitly notes sky lights are not counted, which is actionable guidance.

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