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plant-genomics-mcp

by musharna

1001 Genomes: Natural Variation

arabidopsis_natural_variation
Read-onlyIdempotent

Retrieve per-SNP effect data from 1001 Genomes for an Arabidopsis locus, showing variation across 1135 natural accessions. Returns effects, impacts, and amino-acid changes.

Instructions

Fetch 1001 Genomes natural-variation SNP effects for an Arabidopsis locus (tools.1001genomes.org; free, no key) — the variation observed across 1135 resequenced natural accessions. Returns per-SNP effect rows (chromosome, position, accession id, effect, impact, amino-acid change, transcript) plus the gene's genomic span. variant_count is the true row total even when capped. ARABIDOPSIS-ONLY — any other organism raises OrganismNotSupported. Defaults to arabidopsis_thaliana.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
locusYesArabidopsis AGI locus, e.g. AT1G01060 (a bare AGI is transcript-scoped to .1)
organismNoArabidopsis only (the 1001 Genomes panel is A. thaliana)arabidopsis_thaliana

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
foundYesTrue once the effects endpoint returned 200
locusYes
regionNoGenomic span, e.g. 'Chr1:33666..37840'
organismYesAlways arabidopsis_thaliana
returnedYesEffect rows returned (post-cap)
variantsNoPer-effect {chr, position, accession_id, effect, impact, amino_acid_change, …}
truncatedYesTrue if the effect list was capped
transcriptYesTranscript-scoped gene id used (e.g. AT1G01060.1)
variant_countYesTotal effect rows (pre-cap)
Behavior5/5

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

Beyond annotations (readOnly, idempotent), it adds behavioral details: free, no key, per-SNP return, variant_count behavior, scoping of locus with .1, and error condition. Adds significant value.

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?

Description is concise and well-structured, front-loading purpose. Every sentence adds essential information with no redundancy.

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 full schema coverage, annotations, and output schema presence, the description is complete. It covers purpose, usage constraints, parameter details, and return structure adequately.

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 coverage is 100%, so baseline 3. The description adds details: locus expects AGI format with transcript scoping, organism defaults and is Arabidopsis-only. Adds meaningful guidance beyond schema.

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 fetches '1001 Genomes natural-variation SNP effects for an Arabidopsis locus', with a specific verb and resource. It distinguishes from siblings by focusing on variation data, unlike motif, homolog, expression tools.

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

Usage Guidelines4/5

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

It explicitly states the tool is Arabidopsis-only and provides the default organism. It does not directly compare to siblings but the context makes it clear when to use (for variation). No explicit when-not-to-use, but strong context.

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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