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musharna

plant-genomics-mcp

by musharna

Batch: Literature

batch_locus_literature
Read-onlyIdempotent

Search Europe PMC literature for up to 50 plant locus identifiers in parallel, returning per-locus results including query details and 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].
sizeNoMax results per locus (1–25, default 10)
organismNoPlant organism — accepts canonical slug (arabidopsis_thaliana), scientific or common name, or NCBI taxidarabidopsis_thaliana

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
toolYesThe batch tool name, e.g. batch_resolve_locus_to_uniprot
countYesNumber of distinct loci queried, returned (== len(results) + len(errors)). The input list is de-duplicated first, so this is LOWER than the number of loci you sent if you sent a duplicate — that is de-duplication, not a dropped locus.
errorsYeslocus → '[ClassName] message' for PlantGenomicsError failures
resultsYeslocus → per-locus result dict (same shape as the single-locus tool)
Behavior4/5

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

Annotations already provide readOnlyHint, openWorldHint, idempotentHint, and destructiveHint=false. The description adds value by explaining parallel execution and error handling (successes in results, errors in errors), going beyond what annotations offer.

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?

The description is two sentences with no wasted words. It front-loads the purpose ('Batch variant of locus_literature') and efficiently covers parallelism, limits, and result structure.

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), the description covers all key aspects: it's a batch, fan-out, max 50 loci, per-locus response payload. Output schema exists, so return values are covered. No gaps.

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%, and the description does not add significant meaning beyond what the schema already provides. It mentions 'up to 50 loci' which is already in schema maxItems. Baseline score of 3 is appropriate.

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 is a batch variant of locus_literature, specifies parallel per-locus searches for up to 50 loci, and describes the results structure. This distinguishes it effectively from the single-locus sibling.

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?

The description implies usage when multiple loci are involved but does not explicitly state when to use this tool versus other batch tools like batch_locus_go_annotations or alternatives. No direct comparison or exclusion criteria are provided.

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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