get_neighborsParcels that touch or surround a parcel (up to 60), each with its cadastral reference and centre point. Spain from the official cadastre; other countries from our own copy where we hold one. Where neighbours cannot be listed it answers supported=false with an empty list, free. One API call.
| Name | Required | Description | Default |
|---|---|---|---|
| country | No | Optional country code. Omit to auto-detect. | |
| reference | Yes | Official cadastral reference of the parcel |
Changes observed during successful MCP inspections.
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Since there are no annotations, the description carries the entire burden. It discloses critical behavioral traits like the data source limitations (Spain vs. other countries), the hard limit on output (up to 60 neighbors), and the precise failure response format.
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 dense but highly efficient. It front-loads the primary function and then quickly lists constraints (count, source, failure mode) without unnecessary prose.
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 lack of an output schema, the description is extremely complete, detailing both the nature of the data returned (reference, center point) and the operational constraints (max 60, API usage).
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%, meaning the inputs are well-defined. The description provides no additional semantic meaning to the parameters beyond what is already present in the input schema, meeting the baseline for high coverage.
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 clearly defines the action ('Parcels that touch or surround a parcel') and the content of the result (cadastral reference and center point). This immediately tells the agent exactly what information the tool returns.
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 provides strong operational context regarding the data source: 'Spain from the official cadastre; other countries from our own copy.' It also clearly specifies the failure mechanism (returning supported=false when neighbors cannot be found).
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
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