get_detection_details

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

With no annotations, the description carries the full behavioral burden and does so well: it discloses that kwp/surface/tilt/azimuth are model estimates rather than surveyed values, states the dataset's estimated recall (~0.6), warns that a missing detection does not mean no PV exists, and explains the quality_filter semantics via source_encoding. This is unusually rich disclosure for a read tool.

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 the core purpose and mostly efficient, but the model-estimate caveat is stated twice ('surface, kwp, tilt, azimuth — model estimates' and again 'kwp, surface, tilt and azimuth are model estimates, not surveyed values'), which is redundant repetition.

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 output schema, the description correctly enumerates the returned fields (imagery years, decoded sources, frpv_proba, false-positive flag, rnb_id, location codes, confidence signals) and pairs them with data-quality caveats. An agent has everything needed to interpret and trust the result.

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 100% and there is only one parameter, whose schema description already defines it as the registry identifier. The description says 'by id' but adds no format, range, or lookup semantics beyond the schema, so the baseline 3 applies.

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?

Opens with a specific verb+resource ('Get the full record of one detection by id') and enumerates exactly what the record contains, which cleanly separates it from siblings like search_detections, count_detections, and get_detections_in_bbox. An agent can identify this as the single-record fetch without opening the 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 clear context (single-detection lookup) and routes the agent to a sibling: 'Call get_data_quality_reference for the full picture before assessing fitness for a specific use case.' However it never states when to choose this over search_detections, nor any exclusion conditions, so it stops short of full when/when-not guidance.

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