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biothings_query_genes

Search for genes using structured Lucene queries with field-specific terms like symbol, name, or taxid. Returns gene details including symbol, name, taxid, and entrezgene.

Instructions

Search genes via Lucene query, returning gene details and query metadata.

    **IMPORTANT:** This endpoint requires structured queries using specific field names. 
    Simple natural language queries like "CDK2 gene" or "human kinase" will **NOT** work.
    You **MUST** specify the field you are querying, e.g., `symbol:CDK2`, `name:"cyclin-dependent kinase 2"`, `taxid:9606`.
    Use this tool when you need to *search* for genes based on criteria, not when you already know the specific gene ID.
    If you know the exact Entrez or Ensembl ID, use the `get_gene` tool instead for faster retrieval.
    
    **Supported Query Features (based on Lucene syntax):**
    1. Simple Term Queries: `q=cdk2` (Searches across default fields)
    2. Fielded Queries: `q=symbol:CDK2`, `q=name:"cyclin-dependent kinase 2"`
    3. Range Queries: `q=taxid:[9606 TO 10090]`
    4. Boolean Queries: `q=symbol:CDK2 AND taxid:9606`
    5. Wildcard Queries: `q=symbol:CDK*`
    
    Returns gene details including symbol, name, taxid, and entrezgene.
    

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
qYes
sizeNo
skipNo
sortNo
emailNo
fieldsNoall
speciesNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
hitsYes
tookNo
totalNo
max_scoreNo
Behavior4/5

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

No annotations provided, so description carries full burden. It discloses that queries must be structured Lucene queries, lists supported query features, and mentions return fields. However, it does not discuss rate limits, authorization, or side effects.

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?

Description is well-structured with bold warnings, bullet points for query features, and clear examples. It is informative but not excessively long. Minor redundancy could be trimmed.

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

Completeness3/5

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

With 7 parameters and an output schema, the description covers the critical 'q' parameter thoroughly but leaves other parameters unexplained. Output schema handles return values, but parameters like sort, fields, email need more context.

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

Parameters3/5

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

Schema description coverage is 0%. Description adds significant value for the 'q' parameter with examples, but provides minimal guidance for other parameters like size, skip, sort, fields, email, and species. Partially compensates.

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 genes via Lucene query and returns gene details and metadata. It uses a specific verb 'search' and resource 'genes', and distinguishes from sibling tool 'biothings_get_gene' for exact 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?

Explicitly states when to use (searching by criteria) and when not to use (exact ID known, use get_gene instead). Warns against natural language queries and provides examples of correct query syntax.

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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