get_detections_in_bbox

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

No annotations are provided, so the description carries the full burden, and it does substantial work: it discloses estimated recall (~0.6), warns that absence of a detection is not absence of PV, flags kwp/surface/tilt/azimuth as model estimates, and explains what quality_filter=true actually filters on. It omits operational traits such as truncation behavior when max_count is hit and any auth/rate constraints.

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-loads the core action and return value, then layers the data-quality caveats in short, information-dense sentences that each add distinct value. It is on the long side for a five-parameter tool, but no sentence is pure 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?

With no annotations and no output schema, the description should ideally describe the return shape and truncation behavior; it only hints at geometry via 'including footprint geometry'. The data-quality caveats are thorough, but an agent still cannot tell what a truncated result looks like or how to page through a larger area.

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 20%, so the description must compensate; it does add the WGS84 lon/lat coordinate convention and the geographic extent semantics, which the schema alone does not state. However, four of five parameters (min_lon/min_lat/max_lon/max_lat) remain undocumented, and the description discusses a quality_filter parameter that does not appear in the input schema at all, which could mislead an agent about available inputs.

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 and resource ('Get rooftop-PV detections') plus the exact spatial scope ('within a geographic bounding box (WGS84 lon/lat)') and what is returned ('including footprint geometry'). The phrase 'map-style spatial queries over a small area' separates it from the sibling search_detections and count_detections, which an agent can distinguish without opening any schema.

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?

Gives a clear usage context ('Intended for map-style spatial queries over a small area') and a prerequisite-style pointer to get_data_quality_reference before assessing fitness. It stops short of explicit when-not-to-use guidance or naming which sibling to prefer for non-spatial or aggregate queries.

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