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vep_region_batch

Annotate multiple variants in batch using genomic coordinates. Returns effect predictions, conservation, and pathogenicity scores for specified species.

Instructions

Annotate multiple variants using genomic coordinates in batch

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
speciesYesSpecies name (e.g., 'homo_sapiens', 'mus_musculus')homo_sapiens
regionsYesList of variants in VCF format (e.g., ['1 230710048 . A G', '9 22125504 . G C']). Format: 'CHR POS ID REF ALT' where CHR=chromosome, POS=position, ID=identifier (use '.' if unknown), REF=reference allele, ALT=alternate allele.
canonicalNoInclude only canonical transcripts per gene
hgvsNoInclude HGVS nomenclature
domainsNoInclude protein domain information
ccdsNoInclude CCDS transcript identifiers
proteinNoInclude protein sequence identifiers
AlphaMissenseNoInclude AlphaMissense pathogenicity scores
CADDNoInclude CADD deleteriousness scores
REVELNoInclude REVEL pathogenicity scores
ConservationNoInclude conservation scores
Behavior2/5

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

No annotations provided, so description must disclose behavioral traits. It only states the basic function without mentioning read-only nature, rate limits, limits on variant count, error handling, or response format. This is insufficient for a batch operation.

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?

Single concise sentence that is front-loaded. However, it could include essential usage context without becoming verbose, earning a 4 rather than 5.

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

Completeness2/5

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

Given the complexity of a batch tool with 11 parameters and no output schema, the description is too minimal. It fails to explain return values, batch size limits, error handling, or any operational context beyond the basic purpose.

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 100%, with each parameter having a clear description. The tool description adds no additional meaning beyond the schema. Baseline 3 is appropriate as it neither detracts nor enhances.

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?

Description clearly states it annotates multiple variants using genomic coordinates in batch, which distinguishes it from sibling tools that use HGVS notation (vep_hgvs_batch) or IDs (vep_id_batch) and single-variant tools. Verb 'annotate' and resource 'variants' are specific.

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

Usage Guidelines3/5

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

No explicit guidance on when to use this tool vs alternatives. The name and sibling tool names imply it is for genomic coordinate input, but the description does not clarify prerequisites, exclusions, or compare to other batch tools.

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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