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npi-lookup

Look up any licensed US healthcare provider or organization by NPI number, name, state, or specialty for credentialing, due diligence, and verification.

Instructions

US NPI registry lookup — find any licensed US healthcare provider or organization by NPI number, name, state, or specialty. Returns NPI, entity type, name, credentials, specialty/taxonomy, license states, practice address, and active status. 7M+ records from CMS. Use for provider credentialing, healthcare due diligence, billing verification, or AML/KYB screening on medical payments.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
npiNo10-digit NPI number for direct lookup (fastest, most precise).
last_nameNoProvider last name (individual providers). Supports wildcard with '*' suffix (e.g. 'Smi*').
first_nameNoProvider first name (individual providers only).
organizationNoOrganization name for NPI-2 (group practices, hospitals, labs, etc.).
stateNo2-letter US state code to filter by practice location (e.g. 'CA', 'NY').
postal_codeNo5-digit ZIP code to filter by practice location.
specialtyNoTaxonomy/specialty description to filter (e.g. 'Internal Medicine', 'Cardiology', 'Psychiatry').
limitNoMax results to return (1–50, default 10).
Behavior4/5

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

Since no annotations are provided, the description carries the full burden. It discloses the data source (7M+ records from CMS) and the fields returned (NPI, entity type, name, credentials, etc.), offering good transparency. It lacks details on rate limits or authentication, but for a read-only lookup, this is sufficient.

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 concise with three sentences that front-load the core function, then list return data and use cases. Every sentence adds value without redundancy.

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?

Given the absence of an output schema and the tool's simplicity, the description covers the essential aspects: purpose, search parameters, return data, and use cases. It is complete enough for an agent to understand the tool's capabilities, though it could mention pagination or result limits.

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 baseline is 3. The tool description summarizes the parameters (by NPI, name, state, specialty) but does not add significant meaning beyond what the schema already provides. No extra context like wildcard usage (already in 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?

The description clearly states the tool performs a lookup of US healthcare providers/organizations by various criteria (NPI number, name, state, specialty). It specifies the resource (US NPI registry) and the verb (lookup/find), making the purpose distinct from sibling tools.

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 lists specific use cases (provider credentialing, healthcare due diligence, billing verification, AML/KYB screening), providing clear context for when to use the tool. However, it does not explicitly mention when not to use it or alternatives, missing some guidance.

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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