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Clinicaltables

by io.github.pipeworx-io
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Npi Individual

npi_individual
Read-onlyIdempotent

"Find a doctor / clinician / physician by name" / "look up NPI for [provider]" / "verify a doctor's credentials" / "what's [Dr. X]'s NPI" — search the NPPES National Provider Identifier registry for individual US healthcare providers (~5M entries). Returns NPI numbers + provider names. terms can be a name fragment, NPI, or specialty. Use ef to include address, specialty, gender.

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. Known fields: name.first,name.last,addr_practice.full,licenses.taxonomy.classification.
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: "smith pediatrics".

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changed
    • addedInput schema / examples
      Added value: +[
+  {
+    "count": 3,
+    "terms": "smith"
+  }
+]
  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. Known fields: name.first,name.last,addr_practice.full,licenses.taxonomy.classification."
    • addedInput schema / properties / terms / description
      Added value: +"Search query — prefix/contains match against canonical names. Whitespace-split into AND tokens. Example: \"smith pediatrics\"."
  3. First observed

TDQS

A4.3/5.0
Behavior4/5

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

Annotations already declare readOnly, idempotent, and non-destructive hints. The description adds useful behavioral detail: it searches a registry (~5M entries), accepts name fragments, NPI, or specialty as terms, and ef can include address/specialty/gender. 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.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is front-loaded with example queries, then states the resource and return, then clarifies terms and ef. It is somewhat dense but each clause contributes information; there is no filler. Structure is logical and efficient.

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 search tool with no output schema, the description covers purpose, usage, behavior, and parameter semantics sufficiently. It mentions returns (NPI numbers + names) and optional fields via ef. It doesn't detail result formatting or pagination, but that is not essential for an agent to invoke it correctly.

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 description coverage is 100%, so all parameters are documented. The description adds extra semantic value: terms can also be an NPI or specialty (beyond the schema's 'prefix/contains match against canonical names'), and ef can include address/specialty/gender. This enriches the schema context meaningfully.

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 it searches the NPPES registry for individual US healthcare providers, lists concrete example queries, and distinguishes from organizational providers via the 'individual' qualifier. It names the specific resource and return values (NPI numbers + provider names), making it unambiguous and differentiable from npi_organization.

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 provides clear context by scoping to individual providers and giving example use cases (find by name, verify credentials, look up NPI). However, it does not explicitly name the sibling npi_organization or state 'use npi_organization for organizations', so the when-not-to-use guidance is implied rather than explicit.

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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