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: billing semantics (free when empty, nothing charged on SUB_001), an error code with a retry prescription, per-country source coverage including the Gipuzkoa-no-outlines caveat, and a size warning on include_geometry. That is exactly the behavioral context an agent needs before calling.

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 identifying purpose and the returned-field list are front-loaded, followed by coverage, billing, and error handling. One sentence is long and enumerative, but nearly every clause carries actionable information; no 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 output schema, the description must explain return contents, and it enumerates the fields fully, plus geometry opt-in behavior, country coverage edge cases, billing, and failure/recovery. An agent can call this correctly and interpret the response without further documentation.

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%, so lang, country, reference, and include_geometry are already documented. The description restates what lang controls (crop name language) and what include_geometry adds (GeoJSON outline), adding little syntax or constraint detail beyond the schema, though the enumerated kind/use_class values do aid interpretation of results. 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?

The description opens with a concrete framing — 'What is on each part of a parcel' — then enumerates exactly what is returned (crop_code, localized crop name, source label, area in m2, kind, use_class, intensity, land type/class, source, optional GeoJSON outline). This lets an agent distinguish it from get_parcel (whole-parcel data) and route code translation to get_crop_catalog without opening a 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?

It states the operational context — one API call, free when the parcel has no subparcels, retry in a few seconds on SUB_001 — and explicitly routes code interpretation to get_crop_catalog. It stops short of an explicit when-not-to-use-this-tool-vs-get_parcel or get_parcel_sigpac statement, so it is clear context rather than full exclusions.

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