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topai_healthcare_validator

Read-onlyIdempotent

Validates 10-digit US NPIs via Luhn 80840 checksum and returns license status and specialty metadata for healthcare practitioner, facility, and compliance onboarding checks.

Instructions

Validates 10-digit US National Provider Identifiers (NPI) using the ISO Luhn 80840 prefix checksum algorithm and returns provider license status and specialty metadata. Use when verifying healthcare practitioners, medical facilities, or compliance onboarding records. Do not use for looking up drug patent expiration dates (use topai_pharmapatent_watcher instead). Stateless, read-only, idempotent verification.

Input Schema

NameRequiredDescriptionDefault
stateNoOptional two-letter US state postal code (e.g., 'CA', 'NY', 'TX').
npi_numberYes10-digit US National Provider Identifier string to validate via Luhn 80840 check (e.g., '1234567893').
provider_nameNoOptional physician surname or healthcare organization name for cross-matching.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.0.2

TDQS

A4.4/5.0
Behavior4/5

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

Annotations already declare readOnlyHint/idempotentHint/destructiveHint=false, so the closing 'Stateless, read-only, idempotent verification' largely restates structured data and earns little. The description does add genuinely new context: the ISO Luhn 80840 checksum rule and the fact that license status and specialty metadata are returned, which matters because there is no output schema.

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?

Front-loaded with the core action and algorithm, then usage, then the exclusion. The drug-patent exclusion is mildly tangential but functions as a real routing guard, so it earns its place; density is good with minimal waste.

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?

With no output schema, the description compensates by stating what is returned (license status, specialty metadata) and how validation works. Combined with full schema coverage and existing annotations, an agent has everything needed to invoke this correctly.

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 all three parameters are already documented at the schema level, and the description adds no param-level syntax or constraint beyond restating that the NPI is 10 digits. Baseline 3 applies; naming 'provider license status and specialty metadata' hints at output rather than parameter meaning.

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?

States a specific verb and resource ('Validates 10-digit US National Provider Identifiers (NPI)') plus the exact algorithm used, and explicitly distinguishes itself from the closest sibling by naming topai_pharmapatent_watcher. An agent can select this tool without opening any schema.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines5/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Gives explicit when-to-use scenarios ('verifying healthcare practitioners, medical facilities, or compliance onboarding records') and an explicit when-not with the alternative named. Both directions of routing are covered with no inference required.

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