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uniprot_taxonomy_search

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Resolve an organism name to its NCBI taxonomy ID by searching scientific and common names. Returns the numeric ID needed for other UniProt tools.

Instructions

Resolve an organism name to its NCBI taxonomy ID(s) — the numeric ID other UniProt tools expect (e.g. the organism parameter of uniprot_search, or organism_id: in a query string). Returns each match's taxonomy ID, scientific name, common name, and rank (species / genus / etc.); a name can resolve to multiple IDs when it's ambiguous (e.g. a genus with several species), so inspect the rank and full scientific name before picking one. Use this before filtering any other search by organism if you only know the name, not the numeric ID.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
sizeNoMaximum number of results to return; capped at 500 server-side.
queryYesOrganism name or partial name to search for, e.g. 'Homo sapiens' or 'coli'. Matches against scientific and common names.
response_formatNo'markdown' (default) for a human-readable report with a provenance footer, or 'json' for a machine-parseable structured payload with the same data. Any other value is rejected.markdown

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior4/5

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

Annotations already declare readOnlyHint=true and openWorldHint=true, so the description does not need to cover safety. It adds important behavioral details: returns multiple matches for ambiguous names, requires inspecting rank and scientific name. It does not mention rate limits or quotas, but the annotations and description together are sufficient.

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

Conciseness5/5

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

The description is a single paragraph of four sentences, each serving a purpose: primary function, output details, ambiguity handling, and usage guidance. No wasted words, front-loaded with the core action.

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

Completeness5/5

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

Given the presence of an output schema, the description does not need to detail return values, but it already lists the returned fields. It covers ambiguity, response formats, and usage context, making it complete for an agent to decide to invoke this tool.

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

Parameters5/5

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

Schema description coverage is 100%, but the description adds significant value beyond the schema: explains that query matches against scientific and common names, details the response_format options ('markdown' with provenance footer, 'json' for machine-parseable), and notes that size is capped at 500 server-side.

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

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states it resolves an organism name to NCBI taxonomy IDs, which is a specific verb+resource. It distinguishes itself from sibling search tools by focusing on taxonomy resolution and explains the context of use (other UniProt tools expect numeric IDs).

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

Usage Guidelines5/5

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

The description explicitly says 'Use this before filtering any other search by organism if you only know the name, not the numeric ID.' It also provides guidance on handling ambiguous results and mentions the response format options, giving clear when-to-use and when-not-to-use context.

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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