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Clinicaltables

by io.github.pipeworx-io
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Conditions

conditions
Read-onlyIdempotent

"What is [condition]" / "look up medical condition by name" / "find a disease called [X]" / "patient-friendly medical term for [Y]" — search the NLM patient-friendly medical conditions vocabulary (~700 common conditions written for lay readers). Returns canonical names like "Migraine", "Type 2 diabetes". Use for symptom-to-condition lookup, intake forms, or simplifying clinical text for patients.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
dfNoComma-separated display fields to use in the `displays` array. Default varies per table; usually the canonical name.
efNoComma-separated extra fields to include per match. Field names vary per table; check NLM docs at clinicaltables.nlm.nih.gov.
countNoMaximum matches to return. Default 7, max 500. Use 1–3 for typeahead UX, 20–50 for browsing.
termsYesSearch query — prefix/contains match against canonical names. Whitespace-split into AND tokens. Example: "migraine".

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changed
    • addedInput schema / examples
      Added value: +[
+  {
+    "count": 3,
+    "terms": "migraine"
+  }
+]
  2. Changed7 schema fields changed
    • addedInput schema / properties / count / default
      Added value: +7
    • addedInput schema / properties / count / description
      Added value: +"Maximum matches to return. Default 7, max 500. Use 1–3 for typeahead UX, 20–50 for browsing."
    • addedInput schema / properties / count / maximum
      Added value: +500
    • addedInput schema / properties / count / minimum
      Added value: +1
    • addedInput schema / properties / df / description
      Added value: +"Comma-separated display fields to use in the `displays` array. Default varies per table; usually the canonical name."
    • addedInput schema / properties / ef / description
      Added value: +"Comma-separated extra fields to include per match. Field names vary per table; check NLM docs at clinicaltables.nlm.nih.gov."
    • addedInput schema / properties / terms / description
      Added value: +"Search query — prefix/contains match against canonical names. Whitespace-split into AND tokens. Example: \"migraine\"."
  3. First observed

TDQS

A4.2/5.0
Behavior4/5

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

Annotations already declare readOnlyHint, openWorldHint, idempotentHint, and destructiveHint=false. The description adds useful behavioral context: the vocabulary size (~700 conditions), the lay-reader audience, and the canonical-name return pattern. It does not cover pagination or exact response shape, but annotations cover the safety profile well.

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 purposeful sentences: query examples come first, followed by resource scope, output shape, and use cases. There is no filler or repetition of schema content, and every clause earns its place.

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 compensates by stating the return style (canonical names) and the intended application contexts. Parameter details are fully covered by the schema, and annotations handle safety. It is complete enough for an agent to call correctly, though explicit sibling routing (e.g., disease_names) is not stated.

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 all four parameters. The description reinforces the 'terms' concept with canonical-name examples and explains the patient-friendly domain, but it does not add syntax-level meaning beyond what the schema provides, so the baseline of 3 applies.

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 uses a specific verb ('search'), names the exact resource ('NLM patient-friendly medical conditions vocabulary'), and states the output ('canonical names like "Migraine"'). It clearly separates this tool from clinical-coding siblings like icd10cm/icd9cm by emphasizing patient-friendly, lay-reader vocabulary.

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 concrete use cases: 'symptom-to-condition lookup, intake forms, or simplifying clinical text for patients.' This is clear context for when to invoke the tool, though it does not explicitly name alternatives or exclusions, so it stops short of a 5.

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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