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musharna

plant-genomics-mcp

batch_locus_literature

Run parallel literature searches for up to 50 plant loci using Europe PMC, returning per-locus query details, hit counts, and publication hits.

Instructions

Batch variant of locus_literature. Fans out per-locus Europe PMC searches in parallel (up to 50 loci). Each results[locus] is the full single-locus payload (query + hitCount + returned + hits[]).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
lociYesList of locus identifiers (1–50). Successes land in results[locus]; PlantGenomicsError failures in errors[locus].
organismNoPlant organism — accepts canonical slug (arabidopsis_thaliana), scientific or common name, or NCBI taxidarabidopsis_thaliana
sizeNoMax results per locus (1–25, default 10)

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
toolYesThe batch tool name, e.g. batch_resolve_locus_to_uniprot
countYesNumber of loci in the input list
resultsYeslocus → per-locus result dict (same shape as the single-locus tool)
errorsYeslocus → '[ClassName] message' for PlantGenomicsError failures
Behavior4/5

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

Discloses parallel fan-out, limit of 50 loci, and the split of results and errors. With no annotations provided, this adds valuable behavioral context beyond the schema, though it does not cover potential rate limiting or partial failure behavior.

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?

Two concise sentences, front-loaded with key information. Every word adds value, 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 the tool's complexity (batch, parallel, error handling) and the presence of output schema, the description covers all essential aspects: batch limit, parallel execution, and output structure. It is complete enough for an agent to understand and use the tool.

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%, but description adds meaning for the loci parameter by explaining error handling. This goes beyond the schema definition, justifying a score above the baseline of 3.

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 is a batch variant of locus_literature, specifying parallel per-locus searches and the output structure. Distinguishes itself from the sibling single-locus version.

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?

Implied usage by name and context (batch for multiple loci), but lacks explicit guidance on when to use this vs locus_literature or other batch tools. No 'when not to use' mentioned.

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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