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by io.github.pipeworx-io
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Search Descriptors

search_descriptors
Read-onlyIdempotent

Search NLM MeSH descriptors by a disease/drug/concept term (e.g. "diabetes", "aspirin", "myocardial infarction"). Returns the matching MeSH descriptor IDs (Dxxxxxxx) — the controlled-vocabulary headings used to index PubMed. The core free-text-to-MeSH lookup. Keyless.

Example tool call

This call uses example arguments supplied in the tool’s input schema.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "text": "diabetes"
    },
    "name": "search_descriptors"
  }
}

Input Schema

NameRequiredDescriptionDefault
textYesA disease, drug, or biomedical concept term, e.g. "diabetes", "aspirin", "myocardial infarction".
limitNoMax results (default 10, max 25).
matchNoMatch mode against descriptor labels: "exact", "contains", or "startswith". Default "contains".

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changed
    • addedInput schema / examples
      Added value: +[
+  {
+    "text": "diabetes"
+  },
+  {
+    "limit": 5,
+    "match": "exact",
+    "text": "myocardial infarction"
+  }
+]
  2. First observed

TDQS

A4.3/5.0
Behavior4/5

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

Annotations already indicate readOnlyHint=true, openWorldHint=true, idempotentHint=true, and destructiveHint=false. The description adds value by clarifying the input domain (disease/drug/concept), return format (descriptor IDs), and that no API key is needed (Keyless). No contradictions with annotations.

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?

The description is two sentences long, front-loads the core purpose, includes examples, and states key attributes (returns, Keyless). No redundant or unnecessary 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?

Given the tool's simplicity (3 parameters, no output schema, strong annotations), the description fully covers what an agent needs: input semantics, output type, authentication status, and use case examples. No gaps remain.

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 coverage is 100% with clear descriptions for all three parameters. The tool description adds little new semantic information beyond the schema, only providing example terms ('diabetes', 'aspirin'). Thus, a baseline score of 3 is appropriate.

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 clearly states the tool's purpose: 'Search NLM MeSH descriptors by a disease/drug/concept term' and specifies the return type 'MeSH descriptor IDs (Dxxxxxxx)'. It distinguishes itself from siblings like 'get_descriptor' by calling itself 'The core free-text-to-MeSH lookup' and notes it's 'Keyless', adding unique context.

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?

The description implies this is the primary tool for searching MeSH by free text, and mentions 'Keyless' as a usage condition. However, it does not explicitly state when to avoid this tool or name alternatives, leaving some ambiguity for an agent.

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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