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annotate_protein

Fetch functional annotations for an eggNOG protein ID (taxid.seqid), returning KEGG KO terms, GO terms, Pfam domains, protein families, and orthologous groups.

Instructions

Annotate a protein with functional information from eggNOG.

Returns a structured functional annotation for the given protein, including KEGG KO terms, GO slim terms, protein family, Pfam domains, and orthologous groups. This is a higher-level convenience wrapper around get_protein that emphasises the annotation results.

Parameters

protein_id : str The eggNOG protein identifier in the format taxid.seqid. Examples: - 9606.ENSP00000269305 (human P53) - 4932.YJR154W (yeast)

Returns

str JSON string with KEGG KO terms, GO terms, and cross-references.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
protein_idYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A4.2/5.0
Behavior3/5

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

No annotations are provided, so the description carries the full behavioral burden. It does disclose that this is a wrapper delegating to get_protein and lists the annotation categories returned, but it says nothing about read-only safety, authentication, rate limits, or error behavior for an unknown protein_id.

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 and return content, then a compact parameter block. Slightly redundant: the 'Parameters' and 'Returns' sections restate the input schema and output schema rather than adding new information, which costs a little space.

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 single-parameter read tool with an existing output schema, the description covers purpose, the identifier format, the wrapper relationship, and return categories. Only minor behavioral detail (safety/permissions, failure on malformed IDs) is absent, which is acceptable given the simplicity.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters5/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 0% and the schema gives only a bare 'string' title, so the description must compensate — and it does fully: it defines the required 'taxid.seqid' format and supplies two concrete examples (human P53, yeast). An agent can construct a valid identifier from the description alone.

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?

States a specific verb and resource ('Annotate a protein with functional information from eggNOG') and enumerates the annotation content (KEGG KO, GO slim, family, Pfam, orthologous groups). It also distinguishes itself from the sibling 'get_protein' by declaring it is a higher-level convenience wrapper that emphasises annotation results.

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?

Names the sibling it overlaps with ('get_protein') and implies the selection criterion: use this when you want the annotation results surfaced. It stops short of an explicit when-not or a fuller routing rule among the other siblings (get_orthologs, get_protein_family, get_orthologous_group).

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