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gbif_species_metrics

Read-onlyIdempotent

Get quick occurrence statistics for a species without running full searches. Returns total occurrences, datasets, countries, and basis-of-record breakdown.

Instructions

Get quick occurrence statistics for a species without running full searches. Returns total occurrence count, dataset count, country count, and basis of record breakdown. Fast endpoint perfect for species profile pages, dashboards, and quick data availability checks.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
keyYesGBIF species key. The unique identifier of the species whose metrics you want. Example: 5231190 (Panthera leo) returns occurrence count, geographic spread, and data quality metrics.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.1.0

TDQS

A3.9/5.0
Behavior4/5

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 covered. The description adds useful behavioral context by disclosing exactly which aggregates come back and that the endpoint is fast/lightweight, though it says nothing about rate limits or pagination behavior.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Three tight sentences, front-loaded with the core action and output list, followed by usage context. The 'perfect for...' phrasing is slightly promotional but still earns its place as routing guidance.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a single-parameter, read-only aggregate tool with no output schema, the definition is largely complete: it explains what is returned and when to use it, and annotations cover safety. Only minor gaps remain (no mention of what happens with an invalid key or any caching/limits).

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100% and the single 'key' parameter is already fully documented in the schema, including an example. The description adds nothing about the parameter itself, so the baseline 3 applies.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

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 for a species) and enumerates the exact metrics returned, which helps distinguish it from the many search/count siblings. It contrasts with 'full searches' but never names the specific alternative tools (e.g. gbif_occurrence_count or gbif_occurrence_search), so differentiation is implied rather than explicit.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Provides clear usage context ('perfect for species profile pages, dashboards, and quick data availability checks') and implicitly routes away from heavyweight searches. However it never states when NOT to use it or names a concrete alternative endpoint, so it stops short of explicit when/when-not guidance.

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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