swisstopo_map_query

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

The annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, so the safety profile is covered. The description adds genuinely useful behavioral context beyond those annotations: exactly one operation per call is required, and fields from a different operation are rejected with an error listing allowed fields. This exposes strictness that the annotations do not convey.

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 well-structured with a crisp opening sentence followed by clearly delineated <use_case> and <important_notes> sections. Every sentence carries unique information—there is no filler, repetition, or verbosity. The structure makes the content easy to scan and consume for an AI agent.

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 multi-operation tool with a nested schema and output schema present, the description covers the full decision space: what the tool does, when to use it vs alternatives, how operations chain together, and a critical behavioral constraint. The presence of an output schema means return-value documentation is not necessary, and the description delivers everything else needed for correct invocation.

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?

Although the context signal indicates 0% schema description coverage, the tool description compensates by explaining the operational flow and how operations relate to parameters (e.g., 'features_at_point' for spatial queries, 'features_by_attribute' for attribute-based). The schema itself also contains detailed per-parameter descriptions inside the nested MapQueryInput object, so the description adds semantic sequencing rather than repeating field-level details. The use_case block meaningfully links parameter categories to operations.

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 'Fragt den nationalen Swisstopo-Kartenkatalog ab (500+ Layer): Layer finden, Felder ansehen, Features abfragen', which uses a specific verb and resource and enumerates the tool's core actions. It also distinguishes this tool from siblings by explicitly naming alternative tools for zoning/municipality and for intercantonal/cantonal sources, making its scope unambiguous.

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?

The <use_case> block lays out a clear chain of operations (search_layers → layer_info → features_at_point/features_by_attribute → feature_by_id) and the <important_notes> give explicit when-not-to-use guidance, pointing to swisstopo_zoning_at, swisstopo_municipality_at, swisstopo_list_available_layers, and swisstopo_search_geodata for alternative needs. This is exemplary usage direction.

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