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LicenseGround

by com.licenseground
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verify_license

Verify an entity's trade contractor license against the official state licensing board (CSLB, DBPR, or TDLR).

Args:
    state: Two-letter US state code ('CA', 'FL', or 'TX'). Required.
    entity_name: The company name, DBA, or contractor name to verify (e.g. 'Apex Roofing LLC').
    license_number: The official state license or certificate ID (e.g. '1058291', 'CCC1330999', 'TACLA29188C').
    trade: Trade category: 'roofing', 'hvac', 'electrical', 'plumbing', 'general_contractor', or 'any'. Default is 'any'.
    city: Optional city to filter geographic disambiguation.

Returns:
    Deterministic, machine-actionable JSON containing verification status, canonical name,
    active standing, disciplinary action count, workers' compensation status, bond status, and confidence score.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
cityNo
stateYes
tradeNoany
entity_nameNo
license_numberNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A3.8/5.0
Behavior3/5

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

No annotations are provided, so the description carries the full burden. It usefully discloses that only CA/FL/TX are supported and that results are 'deterministic, machine-actionable JSON' with a confidence score, but omits auth requirements, failure/not-found behavior, rate limits, and what happens when entity_name and license_number are both absent.

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 purpose followed by clearly labeled Args and Returns blocks with zero fluff, so it is easy to scan. The Returns block is modestly redundant given an output schema exists, costing a point.

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 a formal output schema present, the description needn't explain return values, and it fully covers the parameter space for a 5-param tool. The remaining gap is the absence of any routing guidance against its five siblings.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters5/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 0%, so the description must compensate, and it does: it documents all five parameters, enumerates valid states and trade categories, supplies concrete example IDs and company names, and marks city as optional for disambiguation. This adds real meaning beyond the bare schema types.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

States a specific verb and resource ('Verify an entity's trade contractor license') and names the authoritative sources (CSLB, DBPR, TDLR). It is clear what the tool does but never distinguishes itself from siblings like search_contractors, which an agent could plausibly confuse it with.

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

Usage Guidelines3/5

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

Usage is implied rather than stated: requiring 'state' and supporting 'city' for geographic disambiguation hints at the lookup flow, but there is no explicit when-to-use versus search_contractors or check_compliance_risk, and no exclusions. The only supported states (CA, FL, TX) are buried in the parameter doc.

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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