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uniprot_search_uniref

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Search UniRef clusters by sequence content using a query and identity threshold. Broad homology at 50% identity; near-identical sets at 100%.

Instructions

Search for UniRef clusters by content (not by a known cluster ID — for that, use uniprot_get_uniref directly). Example: query='kinase' identity_tier='90' returns the 90% clusters matching 'kinase'. Use a looser tier (50) to find broad homology groups, a tighter tier (100) to find near-identical sequence sets.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
sizeNoMaximum number of results to return; capped at 500 server-side.
queryYesUniProt query-language expression, e.g. '(gene:TP53) AND (organism_id:9606)'. Field syntax follows https://www.uniprot.org/help/query-fields.
identity_tierNoCluster identity threshold: '50' (loosest grouping), '90', '100' (tightest, only exact-match members), or empty for all tiers. Higher values return more, smaller, tighter clusters.
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?

The description explains response format options (markdown with provenance footer vs. JSON) and the server-side cap on size (500). Combined with annotations (readOnlyHint, openWorldHint), the behavior is well disclosed. Minor missing details like pagination behavior beyond the cap are not critical.

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?

Three sentences efficiently cover purpose, usage distinction, example, and tier guidance. No filler words; every sentence serves a purpose. Front-loaded with the core distinction.

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?

Given the presence of an output schema and 100% parameter coverage, the description adequately covers usage context and parameter semantics. It could mention result ordering or error handling, but the description is sufficient for typical scenarios.

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 all parameters (100% coverage), but the description adds value: explains identity_tier thresholds with examples (50, 90, 100) and their implications, clarifies the response_format options, and gives a query example. This goes beyond the schema's descriptions.

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 the tool searches UniRef clusters by content, contrasting with uniprot_get_uniref for known IDs. An example ('kinase') and tier values solidify the purpose, distinguishing it from sibling search or retrieval 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 advises using uniprot_get_uniref for known cluster IDs and provides guidance on identity tier selection ('looser tier (50) to find broad homology groups, tighter (100) for near-identical sets'). This covers when and why to use different options.

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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