get_database_stats

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

No annotations are provided, so the description must carry the behavioral burden. It discloses the content returned and the tool takes no parameters, making its read-only, side-effect-free nature self-evident, but it says nothing about cost of computing diversity metrics, caching, or freshness of the release data.

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 front-loaded sentence that identifies the resource first and then lists the returned metrics. Every clause carries information and there is no 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?

With no output schema, the description must convey the return content, and it does so by enumerating version, release date, counts, and diversity metrics. It stops short of indicating the shape or naming of those metrics, which would help an agent parse results, but the essentials are covered.

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?

The tool has zero parameters, so there is no parameter semantics to explain; the baseline for a parameterless tool is 4. The description correctly makes no parameter claims and focuses on output content instead.

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 names a specific verb+resource ('Get statistics about the GTDB database') and enumerates the content returned: version, release date, genome counts, and taxonomic diversity metrics for bacteria and archaea. No sibling tool (search, get_taxonomy, compare_genomes, etc.) overlaps with this purpose, so it is unambiguously distinguishable.

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?

Usage is implied — an agent should call this when it needs database version or aggregate counts — but the description never states when to use it versus navigating the taxonomy with get_taxonomy or get_taxon_summary. For a zero-parameter tool this is a minor gap, yet no explicit context or exclusion is given.

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