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biothings_query_variants

Search for variants using Lucene queries, such as rsID, gene names, or genomic intervals, and retrieve detailed annotations and query metadata from MyVariant.info.

Instructions

Search variants via Lucene query (e.g., rsID, gene name), returning variant details and query metadata.

    Search for variants using a query string with various filtering options, leveraging the MyVariant.info API.
    **Use this tool for *searching* variants based on criteria.** 
    If you already know the exact variant ID (HGVS, rsID), use the `get_variant` tool for faster direct retrieval.

    **Supported Query Features (Lucene syntax):**
    1. Simple Queries: `q=rs58991260` (Find by rsID)
    2. Fielded Queries: `q=dbsnp.vartype:snp`, `q=dbnsfp.polyphen2.hdiv.pred:(D P)`
    3. Range Queries: `q=dbnsfp.polyphen2.hdiv.score:>0.99`
    4. Wildcard Queries: `q=dbnsfp.genename:CDK*`
    5. Boolean Queries: `q=_exists_:dbsnp AND dbsnp.vartype:snp`
    6. Genomic Interval Queries: `q=chr1:69000-70000`
    

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
qYes
sizeNo
skipNo
sortNo
emailNo
fieldsNoall

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 exist, so description carries full burden. It discloses API dependency (MyVariant.info) and Lucene query features. Could mention pagination or rate limits but is quite transparent for a search tool.

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?

Well-structured with bullet points for query features. Each sentence adds value, no fluff. The description is appropriately sized for the complexity.

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?

Output schema exists. Description covers query capabilities thoroughly and references the API. Could mention how to use 'fields' to restrict output and explain pagination parameters, but overall sufficient for a search tool.

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 coverage is 0%. The description only explains the 'q' parameter with examples. Other parameters like 'size', 'skip', 'sort', 'email', 'fields' are not described. Partial compensation, but significant gaps remain.

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 variants via Lucene query and returns variant details and query metadata. It distinguishes itself from the 'get_variant' tool by specifying when to use each.

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 says 'Use this tool for *searching* variants based on criteria' and recommends 'get_variant' for exact IDs, providing clear when-to-use guidance.

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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