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musharna

plant-genomics-mcp

atted_coexpression

Fetch co-expressed gene neighbors for a plant locus from ATTED-II. Returns top-ranked genes with z-scores to identify functional partners based on co-expression patterns.

Instructions

Fetch co-expressed gene neighbors from ATTED-II (atted.jp, API v5) for a plant locus. Returns top_n neighbors with target locus + NCBI Entrez gene ID + z-score (higher = stronger coexpression). The ATTED-II release (e.g. Ath-u.c4-0 for Arabidopsis, Osa-u.c1-0 for rice) is resolved per-organism; wheat, sorghum, barley, poplar, and brachypodium have no published release and raise OrganismNotSupported. Pairs with string_interactions to surface high-confidence functional partners (interactors that are also coexpressed).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
locusYesPlant locus, e.g. AT1G01010 (Arabidopsis) or Os01g0100100 (rice)
organismNoPlant organism — accepts canonical slug (arabidopsis_thaliana), scientific or common name, or NCBI taxidarabidopsis_thaliana
top_nNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
locusYes
atted_releaseYesATTED-II DB identifier, e.g. Ath-u.c4-0 (release version included)
neighborsYes
Behavior4/5

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

No annotations are provided, so the description carries full burden. It discloses API version (v5), release resolution per organism, error for unsupported organisms, and pairing with another tool. This is fairly transparent, though rate limits or authentication are not mentioned.

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 only two sentences, front-loaded with the core purpose and immediately followed by important behavioral details. No wasted words.

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?

An output schema exists, so return values need not be detailed. The description covers the tool's main behavior, error conditions, and relationship to a sibling tool, making it complete for an agent to understand usage.

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 67%, meaning the schema already provides good parameter descriptions. The description adds that the z-score measures coexpression strength and that some organisms are unsupported, but does not significantly enhance parameter semantics beyond the schema.

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 the tool fetches co-expressed gene neighbors from ATTED-II for a plant locus. It specifies the output (top_n neighbors with locus, Entrez ID, z-score) and distinguishes itself from sibling tools like string_interactions by noting they can be paired together.

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 provides clear context for when to use this tool, including explicit unsupported organisms (wheat, sorghum, etc.) that raise an error. It also hints at usage with string_interactions, but does not explicitly state when to use this versus other expression or interaction tools.

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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