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Glama

get_pathways

Fetch biological pathways linked to a gene or protein from Reactome, returning pathway names, stable IDs, and links for annotation and enrichment analysis.

Instructions

Fetch biological pathways involving a gene or protein from Reactome.

Args: query: Gene symbol (e.g. 'TP53'), alias, or UniProt accession (e.g. 'P04637'). taxon_id: NCBI Taxonomy ID (default: 9606 for human). species: Species name (default: 'Homo sapiens'). limit: Maximum number of pathways to return (default: 20).

Returns: JSON string containing the list of pathways with names, stable IDs, and Reactome links.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNo
queryYes
speciesNoHomo sapiens
taxon_idNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. Addedv0.7.0

TDQS

B3.4/5.0
Behavior3/5

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

No annotations are provided, so the description bears full disclosure duty. 'Fetch' implies a read-only lookup and it describes the return payload (names, stable IDs, Reactome links), which is useful. However it says nothing about rate limits, network/auth requirements, error behavior, or pagination, leaving gaps for a tool with no annotation coverage.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Front-loaded with purpose, then a clean Args/Returns structure. The formatting is verbose but every line carries information; the Args block is arguably redundant with the schema, but as plain text it remains readable and scannable.

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?

An output schema exists, so a full return description is not required, yet the summary of returned fields adds orientation. For a read-only lookup with four well-documented params, the definition covers what an agent needs, with the only real gap being usage routing relative to siblings.

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 description coverage is 0%, so the description must carry the parameter burden, and it does: it gives the query format with concrete examples ('TP53', 'P04637'), explains taxon_id as an NCBI ID with the human default, and gives defaults for species and limit. This is more than the bare schema provides.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

States a specific verb and resource ('Fetch biological pathways involving a gene or protein from Reactome'), so an agent immediately knows what it does. It does not explicitly distinguish itself from the sibling get_pathway_details (which presumably takes a pathway ID rather than a gene query), so it stops short of a 5.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description says nothing about when to use this tool versus alternatives like resolve_gene, get_pathway_details, or annotate_function. It only documents parameters and defaults, leaving the routing decision entirely to inference.

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