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ShearQuery — Barber & Beauty Industry Data

Check a Texas barber or cosmetology licence against the TDLR record

verify_texas_license
Read-only

Look up a Texas barber, cosmetology, school or establishment licence in the state regulator's own licensee record — by licence number, or by name with an optional city. Returns the licence type, number, expiry and whether it had expired as of the data snapshot. Texas only. This reports what TDLR published on the snapshot date; it is not a live check and it does not report disciplinary action or continuing-education status.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
cityNoOptional city to narrow a name search.
nameNoPerson or business name, e.g. "Smith" or "Baytown Beauty". TDLR stores people as "LAST, FIRST".
limitNoHow many matches to return (1-25, default 10).
license_numberNoThe licence number, if known. Exact match. Fastest and least ambiguous.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Added

TDQS

A4.5/5.0
Behavior5/5

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

Annotations already declare readOnlyHint=true and openWorldHint=false, and the description adds meaningful behavioral context: results reflect the TDLR snapshot date rather than live data, and disciplinary/CE status is intentionally excluded. No contradiction 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.

Conciseness5/5

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

Two sentences front-load the actionable purpose and return values, then concisely state limitations. Every clause adds information; there is no filler or redundant restatement of the annotations.

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?

For a zero-required-parameter read-only tool with no output schema, the description adequately states what it returns, the search methods, the Texas scope, and important caveats. An agent has enough to select and invoke it correctly without ambiguity.

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 coverage is 100%, with all four parameters described in the input schema. The description restates the key search modes (licence number, name, optional city) but adds no semantic detail beyond what the schema already provides, so the baseline 3 is appropriate.

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 concrete lookup action ('Look up...') against a specific resource (the TDLR licensee record) and clearly scopes it to Texas barber, cosmetology, school, or establishment licences. It distinguishes itself from sibling comparison/count tools by describing individual licence-record verification.

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?

Provides clear usage context: Texas-only, by licence number or name/city, and explicitly warns it is not a live check and does not report disciplinary action or continuing-education status, which tells an agent when not to use it. However, it does not name alternative sibling tools for those missing capabilities, 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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