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uniprot_search_keywords

Read-only

Search UniProt keywords by name or definition to find keyword IDs (KW-####) for concepts like acetylation or nucleus.

Instructions

Search UniProt's controlled keyword vocabulary (the KW-#### terms) by name or definition. Use this to discover a keyword ID from a concept; once you have the KW-#### ID, call uniprot_get_keyword for its full record (definition, category, hierarchy, GO cross-references). Returns up to size matches, or an empty list if nothing matches. Examples: 'acetylation', 'nucleus', 'kinase activity'.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
sizeNoMaximum number of results to return; capped at 500 server-side.
queryYesFree-text to match against UniProt keyword names, synonyms, and definitions, e.g. 'acetylation', 'nucleus', 'kinase activity'. Plain words, not a UniProtKB field query.
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
Behavior5/5

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

Annotations already declare readOnlyHint and openWorldHint. The description adds valuable behavioral details: returns up to size matches, server-side cap at 500, response format options, and that query is plain text not field query. No contradictions.

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?

The description is a single paragraph but well-organized: purpose, usage instruction, return behavior, examples. It is concise but could benefit from slightly more structure (e.g., separation of return info). Still effective.

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 tool's complexity and existence of output schema, the description covers all necessary aspects: purpose, usage, parameters, behavior, and output options. No gaps.

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

Parameters4/5

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

Schema covers 100% of parameters with descriptions. The description adds meaning beyond schema by giving examples for 'query', clarifying the size cap, and explaining response_format options. It enriches parameter understanding.

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 searches UniProt's controlled keyword vocabulary, with specific examples and differentiation from the sibling tool uniprot_get_keyword. The verb 'search' and resource 'keyword vocabulary' are specific, and it distinguishes from other search tools.

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?

Explicitly tells when to use: 'Use this to discover a keyword ID from a concept; once you have the KW-#### ID, call uniprot_get_keyword for its full record.' It also explains return behavior (up to size matches, empty list) and mentions cap at 500.

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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