taxonomy_lookup

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

With no annotations provided, the description carries the behavioral transparency burden. It clearly describes a read-only lookup behavior, names the data source, lists the returned data fields, and gives concrete input examples. It does not discuss edge cases like no matches or multiple hits, but for a simple lookup tool this is sufficient.

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 short and front-loaded with the action and resource. The bilingual repetition adds length, but it also broadens accessibility and does not obscure the key information. Every meaningful element—purpose, input format, and output fields—is present without fluff.

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 one-parameter lookup tool, the description is complete: it defines the accepted query formats, the data source, the returned fields, and the intended purpose. An output schema exists and no nested/enum complexity is present, so nothing critical is missing for an agent to select and invoke this tool.

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 description coverage is 0%, so the description is the only source of parameter meaning. It fully compensates by explaining that the 'query' parameter accepts either a species name or a NCBI taxid, and provides concrete examples (9606, human). This is exactly what an agent needs to call the tool correctly.

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 uses a specific verb ('Look up') and a clear resource ('NCBI Taxonomy species classification'), and states the returned fields: scientific/common name, rank, and lineage. This makes it easy for an agent to distinguish this tool from the many sibling tools, none of which target NCBI taxonomy classification.

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 description gives a clear use context: confirm the official classification of a species, and specifies accepted inputs (species name or taxid, e.g., 9606, human). It does not explicitly name alternatives or exclusion conditions, but no close taxonomic sibling exists and the context is clear enough.

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