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

With no annotations provided, the description carries the full burden of behavioral disclosure, and it does so thoroughly. It warns that this is a detection dataset, not an exhaustive inventory (recall ~0.6), that missing detections do not imply absence of PV, and that fields like kwp are model estimates rather than surveyed values.

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 somewhat long but every sentence carries useful information: the action, the return shape, the alternative tool, and data caveats. It is front-loaded with the main purpose and then layered with guidance, though it could be slightly tightened without losing value.

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 the tool's complexity (8 parameters, no annotations, no output schema), the description covers the essential invocation context: return shape, filtering logic, sibling differentiation, and data quality limitations. It does not detail the contents of quality_summary or the output record fields, but this is a minor gap for a search tool whose parameters are fully schema-documented.

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 schema already documents all 8 parameters in detail. The description only paraphrases the filter categories without adding new parameter-level meaning beyond the schema, which meets the baseline for full coverage but does not exceed it.

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 specific verb and resource ('Search individual rooftop-PV detections') and enumerates the filter dimensions (département, INSEE code, capacity range, confidence). It also distinguishes itself from the sibling get_detections_in_bbox by explicitly routing spatial/map queries there.

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 gives explicit when-not-to-use guidance: 'use get_detections_in_bbox instead for map/spatial queries with geometry.' It also directs the agent to call get_data_quality_reference before assessing fitness, providing clear context for appropriate invocation.

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