get_field_coverage

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

With no annotations, the description carries the full burden and does so: it defines the null convention ('not available/recorded', never '0' or 'confirmed ok'), discloses the dataset's recall limitation (~0.6) and that absence of a detection is not absence of an installation, flags kwp/surface/tilt/azimuth as model estimates, and explains quality_filter's 2+-source semantics. These are substantive behavioral facts an agent could not infer elsewhere.

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?

Purpose and scope are front-loaded and every sentence is informative, but the paragraph is dense and includes a data-quality aside (kwp, surface, tilt, azimuth model estimates) that concerns fields this tool does not report on. Slightly overstuffed rather than wasteful.

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 a no-annotation, no-output-schema, single-parameter tool, the description covers what is returned (counts and percentages per field), how to read nulls, geographic scope, and pointers to the related reference tools. Nothing an agent needs to call it 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 schema documents the single dpt parameter at 100% coverage, so the baseline is 3. The description reinforces the scoping ('for France or one département') and the omit-for-all-of-France behavior, but adds no format or validation detail beyond the schema, so no credit above baseline.

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: a completeness report giving, for each optional registry field (rnb_id, frpv_proba, false_positive, false_positive_source), how many detections have it filled and at what percentage. It names the sibling it is not (count_detections) and scopes the geography (France or one département), so an agent can distinguish it from count_detections, get_field_distribution, and get_source_breakdown.

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 an explicit trigger question ('how many installations have an RNB id / an FRPV comparison / a false-positive flag?') and an explicit exclusion routing to count_detections for a single filtered count. It also advises calling get_data_quality_reference before judging fitness, so when-to-use, when-not, and a prerequisite are all present.

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