Skip to main content
Glama
musharna

plant-genomics-mcp

analyze_locus_synth

Resolves a plant locus through Ensembl Plants, then cross-references UniProt, Europe PMC, and QuickGO in parallel, returning a reconciled summary with per-step status and cross-source disagreements.

Instructions

Synthesis: one-call equivalent of the analyze_locus prompt. Resolves a locus through Ensembl Plants, then fans out to xrefs, UniProt, Europe PMC, and QuickGO in parallel. Returns a SynthesisEnvelope with per-step status and a reconciled summary flagging cross-source name/accession disagreements.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
locusYesLocus name, e.g. AT1G01010
organismNoPlant organism — accepts canonical slug (arabidopsis_thaliana), scientific or common name, or NCBI taxidarabidopsis_thaliana

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
toolYesSynthesis tool name, e.g. analyze_locus_synth
inputYesEchoed input arguments
started_atYesISO 8601 UTC timestamp
elapsed_sYesTotal orchestrator wall time
stepsYesPer-backend execution rows
resultNoComposed cross-source result; None if root step failed
Behavior3/5

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

Without annotations, the description carries the burden of behavioral disclosure. It explains the parallel fan-out and disagreement flagging, but does not state whether the operation is read-only, idempotent, or any potential side effects. It lacks clarity on safety and error behavior, though it does outline the high-level process.

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, front-loaded with the key concept 'Synthesis: one-call equivalent', and efficiently conveys the tool's operation and output. No wasted words.

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?

For a synthesis tool with an output schema, the description covers the workflow and output type, but lacks mention of failure handling or partial results. It is complete enough for an agent to understand the high-level behavior, though additional caveats would improve it.

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?

The input schema has 100% description coverage, so the tool description provides little additional meaning. The description mentions 'resolves a locus' which aligns with the 'locus' parameter, but does not add new semantic detail beyond the schema. Baseline 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 specifies the tool's purpose: it is a synthesis tool that resolves a locus via Ensembl Plants and fans out to multiple sources (xrefs, UniProt, Europe PMC, QuickGO) in parallel, returning a SynthesisEnvelope. This distinguishes it from sibling tools like ensembl_plants_lookup_locus or get_gene_xrefs, which perform only single steps.

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 states 'one-call equivalent of the analyze_locus prompt' implying it replaces a multi-step process, but it does not explicitly specify when to use this tool versus the individual components or provide scenarios for when-not to use it. Usage context is implied but not detailed.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Install Server

Other Tools

Latest Blog Posts

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/musharna/plant-genomics-mcp'

If you have feedback or need assistance with the MCP directory API, please join our Discord server