describe_dataset

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

No annotations are provided, so the description carries the full disclosure burden. It lists what fields are inspected (schema, CRS, limits, provenance) which adds some behavioral context, but doesn't disclose whether this is a read-only operation, what happens with missing/unavailable metadata, or any auth/permission requirements.

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?

A single, efficient sentence that fronts the core purpose and enumerates the key inspection areas compactly. No wasted words or 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?

The tool has 2 parameters, no annotations, 0% schema description coverage, and the description is short. The tool inspects data with multiple semantic dimensions (schema, CRS, limits, provenance), and the interaction between dataset_id and layer_id is not fully explained. An output schema exists which offsets some return-value explanation need, but the description remains thin for a tool with this inspection scope.

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 0%, so the description must compensate. The description explains dataset_id's role ('inspect one dataset or layer') at a high level, and layer_id's role is implied by 'or layer', but neither parameter's exact format, constraints, or interaction is clarified. It adds some meaning but not enough to bridge a 0% coverage 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?

The description states a specific verb+resource ('Inspect one dataset or layer') and lists what it covers (schema, CRS, limits, provenance), which is clear. However, with 9 sibling tools including discover_datasets and inspect_coverage, it doesn't explicitly distinguish itself from these related inspection/discovery tools.

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?

No explicit when-to-use or when-not-to-use guidance is given. The description implies it's for inspecting dataset metadata, but doesn't contrast with siblings like discover_datasets (discovery vs. inspection) or inspect_coverage (which may overlap in purpose). The differentiation gap is notable given the tool count.

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