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musharna

plant-genomics-mcp

batch_locus_go_annotations

Batch query of Gene Ontology annotations for up to 50 plant loci. Each locus is resolved through UniProt and then queried in QuickGO, with per-locus error reporting.

Instructions

Batch variant of locus_go_annotations. Two-stage fanout — each locus is resolved to UniProt and then queried in QuickGO. Per-locus NotFoundError from either stage lands in errors[] with the typed prefix preserved. Capped at 50 loci.

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
limitNoMax annotations per locus from QuickGO (1–100, default 50)

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?

With no annotations provided, the description carries full burden. It discloses the two-stage fanout, error handling (per-locus NotFoundError in errors[] with typed prefix), and the 50-locus limit. It lacks details on rate limits or side effects, but for a read-like batch query this is adequate.

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 redundancy, front-loading the key purpose ('Batch variant'). Every word adds value, and it is well-structured for quick comprehension.

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?

Given the output schema exists and all parameters are well-described in the schema, the description adequately covers the process and error handling. It might be missing behavioral nuance like whether partial failures return partial results, but the error handling description implies this.

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% with good descriptions, but the description adds value by explaining error handling details (successes and failures in results/errors) and the two-stage process, going beyond what the schema provides.

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_go_annotations, explaining the two-stage process (resolve locus to UniProt then query QuickGO) and mentioning error handling and the 50-locus cap. This distinguishes it from the sibling single-locus tool.

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?

The description implies usage for multiple loci via 'Batch variant' and mentions the cap, providing clear context. However, it does not explicitly state when not to use it or mention alternative tools beyond the single-locus variant, which would justify a perfect score.

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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