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musharna

plant-genomics-mcp

by musharna

Batch: BAR Predicted Interactions

batch_bar_aiv_interactions
Read-onlyIdempotent

Batch retrieve gene regulatory network papers for Arabidopsis or protein-protein interaction partners for rice across up to 50 loci.

Instructions

Batch variant of bar_aiv_interactions. Fans out per-locus BAR AIV calls in parallel (up to 50 loci); all loci in a single call share the same organism. Each results[locus] is the full single-locus payload (kind=grn_papers for Arabidopsis with papers list, kind=ppi_predictions for rice with partners list).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
lociYesList of locus identifiers (1–50). Successes land in results[locus]; PlantGenomicsError failures in errors[locus].
organismNoarabidopsis_thaliana or oryza_sativa — slug, scientific/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?

The description adds context beyond annotations: parallel execution, 50-locus limit, organism constraint per call, and the varying result payload per organism (papers vs partners). It does not contradict annotations.

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 sentences efficiently convey purpose, constraints, and result structure without redundancy. Every sentence adds value.

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 batch complexity and existing output schema, the description covers parallelism, limit, organism sharing, and result structure. Minor gap: no explicit error handling beyond mentioning errors[locus], but overall sufficient.

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 coverage is 100%, so baseline is 3. The description adds that loci are identifiers with success/failure mapping in results and errors, but does not significantly extend schema-provided parameter meanings.

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 bar_aiv_interactions, outlines the parallel fan-out for up to 50 loci, and specifies the result structure per locus. It distinguishes itself from the single-locus sibling by focusing on batch processing.

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 when querying multiple loci, noting the constraint that all loci share the same organism. It distinguishes from the single-locus variant but does not explicitly compare with other batch tools or state when not to use it.

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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