gbif_registry_dataset_metrics

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

Annotations already declare readOnlyHint, idempotentHint, openWorldHint, and destructiveHint=false, so the safety profile is fully covered. The description adds the shape of the output (counts by basis of record, country, year, quality indicators) but says nothing about auth needs, caching, latency, or stability of the metrics.

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?

Three short sentences, front-loaded with the verb+resource and followed by the return shape and a use case. No filler, though the final sentence is somewhat redundant with the second.

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 usefully enumerates what is returned, and the lone parameter is fully specified in the schema. Safety is covered by annotations. Only the absence of guidance on when to prefer this over related dataset/occurrence tools keeps it from a 5.

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% and the single 'key' parameter is thoroughly documented in the schema itself (UUID format, example value, and where to obtain it). The description adds nothing about the parameter, so the 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?

States a specific verb and resource: 'Get occurrence statistics and quality metrics for a dataset.' An agent can tell it apart from gbif_registry_get_dataset (metadata) and gbif_species_metrics (taxon-level). It does not, however, explicitly name or contrast any sibling, so it stays at 4 rather than 5.

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?

'Useful for understanding dataset composition and coverage' implies a use case but gives no when-to-use vs when-not, no prerequisites, and no alternative tools (e.g. get_dataset for metadata, occurrence counts tools for live queries). Usage is only implied.

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