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Glama

mgnify_analysis_annotations

Retrieve annotation tables for an MGnify analysis by providing the accession and annotation type (e.g., taxonomic or protein-family). Supports pagination for large result sets.

Instructions

Fetch a typed annotation table for an analysis. annotation_type must be one of: taxonomies__ssu, taxonomies__lsu, taxonomies__its_one_db, taxonomies__unite, taxonomies__pr2, taxonomies__dada2_pr2, taxonomies__dada2_silva, pfams. Pick taxonomies__ssu for 16S/18S ribosomal taxonomy, pfams for protein-family annotation.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
paramsYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.2.0

TDQS

B3/5.0
Behavior1/5

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

No annotations are provided, so the description carries the full burden of disclosing behavioral traits. It does not mention read-only status, side effects, permissions, rate limits, or error conditions. The verb 'Fetch' implies a read operation, but this is not explicit.

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?

The description is concise, starts with the primary action, and avoids unnecessary fluff. The enumeration of annotation types is slightly redundant with the schema, but overall it is well-structured and to the point.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness3/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the moderate complexity (multiple annotation types, pagination), the description is adequate but not complete. It does not mention output format, pagination behavior, or any caveats, though the schema provides some of this detail. The description covers the core purpose but leaves gaps.

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 schema already provides descriptions for accession and annotation_type, including the meaning of each enum value. The description repeats the enum and adds a helpful 'Pick...' recommendation, but does not significantly expand on the schema's parameter semantics. The optional page and size parameters are not addressed in the description.

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?

The description clearly states the action ('Fetch') and the resource ('typed annotation table for an analysis'), and it enumerates the valid annotation types. It does not explicitly name or contrast sibling tools, but the purpose is unmistakable.

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 gives partial usage guidance by recommending which annotation_type to choose (e.g., 'Pick taxonomies__ssu for 16S/18S ribosomal taxonomy, pfams for protein-family annotation'). However, it does not explain when to use this tool as opposed to related tools like mgnify_get_analysis or mgnify_run_analyses.

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