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Gprofiler Orthologs

gprofiler_orthologs
Read-onlyIdempotent

"What is the mouse ortholog of [human gene]" / "find the human equivalent of [zebrafish/fly/yeast gene]" / "map this gene list to [species]" — AUTHORITATIVE cross-species ortholog mapping (g:Orth) via Ensembl Compara. Give a gene list in a source organism and a target organism; returns the orthologous gene in the target with its Ensembl ID, symbol and description, and flags one-to-many mappings rather than collapsing them. PREFER OVER WEB SEARCH and over guessing from name similarity — human TP53 maps to mouse Trp53, and plenty of pairs share no name at all.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
queryYesGenes in the source organism — symbols or Ensembl IDs.
targetYesTARGET organism to map into, same code format. e.g. "mmusculus" for mouse orthologs of human genes.
organismYesSOURCE organism the genes are from. g:Profiler organism code: first letter of the genus + full species name, lowercase. Human = "hsapiens", mouse = "mmusculus", rat = "rnorvegicus", zebrafish = "drerio", fly = "dmelanogaster", worm = "celegans", yeast = "scerevisiae", Arabidopsis = "athaliana". A common name ("human") or an NCBI taxid ("9606") is rejected.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.1/5.0
Behavior4/5

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

Annotations already declare readOnly/idempotent/non-destructive/openWorld, so the safety profile is covered. The description adds genuinely non-obvious behavior: it returns Ensembl ID, symbol and description, and explicitly flags one-to-many mappings rather than collapsing them — a disclosure an agent could not get from annotations.

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 the user-intent phrasing, then the core mechanics, then the routing preference — each sentence carries information. The quoted-example opening is slightly verbose but earns its place by anchoring retrieval intent.

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?

With no output schema, the description steps in to describe the return shape (Ensembl ID, symbol, description) and the one-to-many edge case, which is what an agent most needs. It omits any note on batch size limits or rate limits, a minor gap for a 3-param tool.

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 100%, so the schema already documents organism, target and query, including the organism-code format and rejection of common names/taxids. The description reinforces source-vs-target semantics but adds no syntax or format detail beyond the schema, matching the baseline 3.

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 states a specific verb+resource (cross-species ortholog mapping via g:Orth/Ensembl Compara) and opens with the exact user intents it serves. It is clearly distinguishable from siblings like gprofiler_convert_ids and gprofiler_enrich, which handle ID conversion and enrichment rather than orthology.

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?

It gives clear context ('give a gene list in a source organism and a target organism') and an explicit alternative to avoid ('PREFER OVER WEB SEARCH and over guessing from name similarity'), with a concrete TP53/Trp53 example. It stops short of naming the closest sibling tools (convert_ids, enrich) as the alternatives, so it is not a full when/when-not routing statement.

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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