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Glama

Mydisease

by io.github.pipeworx-io

Disease

disease
Read-onlyIdempotent

Fetch the full aggregated annotation object for a single disease id. Accepts MONDO ("MONDO:0015967"), DOID ("DOID:9351"), OMIM ("OMIM:125853") and other supported ontology ids. Returns cross-referenced data including MONDO ontology (labels, synonyms, xrefs, parents/children), gene-disease associations from DisGeNET, phenotypes from HPO, and chemical-disease relationships from CTD. Resolve a name to an id first via the "query" tool.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
idYesA disease id such as "MONDO:0015967", "DOID:9351", or "OMIM:125853".
fieldsNoComma-separated list of annotation fields to return (default: all fields).

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. Changed1 schema field changed
    • addedInput schema / examples
      Added value: +[
+  {
+    "id": "MONDO:0005148"
+  },
+  {
+    "fields": "mondo,disgenet,hpo",
+    "id": "DOID:9351"
+  }
+]
  2. First observed

TDQS

A4.7/5.0
Behavior5/5

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

Adds significant context beyond annotations: details cross-referenced data sources (MONDO, DisGeNET, HPO, CTD). No contradiction with readOnlyHint or idempotentHint.

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?

Three sentences, front-loaded with purpose, then id details, then return data, then usage tip. 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?

For a complex multi-source fetch tool, description covers input, return contents, and usage flow. No output schema but return described adequately.

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 coverage 100% (baseline 3). Description adds meaning: explains id prefix examples and fields as comma-separated with default. Goes beyond 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?

Clearly states 'Fetch the full aggregated annotation object for a single disease id.' with specific verb and resource. Distinguishes from sibling 'query' by noting that tool resolves name to id.

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?

Explicitly says when to use (have a disease id) and recommends prerequisite step (use 'query' to resolve name). No explicit when-not, but clear context.

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

All Mydisease toolsInspect
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TDQS

A3.9/5.0
Disambiguation2/5

Multiple research/query entry points overlap heavily: ask_pipeworx and ask_pipeworx_beta are currently identical, ask_pipeworx_grounded and deep_research sit on the same routing core, and validate_claim/bet_research/entity_profile all wrap lookup-and-analyze behavior. The detailed descriptions help within specialized clusters, but the central ask_pipeworx family alone creates real selection ambiguity.

Naming Consistency3/5

All names are lower_snake_case and several families are consistent (ask_pipeworx_*, polymarket_*, remember/recall/forget), but the overall set mixes bare verbs, nouns, and verb_noun composites with no global pattern (disease, metadata, query, entity_profile, generate_llms_txt, validate_claim). It is readable but not predictable across the full 34-tool surface.

Tool Count2/5

34 tools is over the 25+ threshold and the set bundles several distinct domains—disease ontology, Pipeworx data access, prediction markets, AI visibility, npm scanning, memory, and subscriptions—into one server. Each subfamily may be justified, but the combined surface is heavy and makes tool selection harder than the underlying tasks require.

Completeness4/5

The disease domain has query/disease/metadata for search-and-fetch read coverage, and the broader research side has lookup, grounded verification, deep research, entity profiles, comparisons, subscriptions, and memory lifecycle tools. Minor gaps exist (no direct tool to fetch pipeworx:// citation URIs, no disease browsing/pagination), but these are workable rather than blocking.

Resources