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Angeltooth

US Gambling Regulations MCP Server

by Angeltooth

get_license_types

Retrieve detailed gambling license types for a specific US state. Enter a state jurisdiction to see applicable license categories and requirements.

Instructions

Get detailed information about gambling license types for a specific US state

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
stateYesState jurisdiction (use kebab-case: new-jersey, pennsylvania, nevada, etc.)
Behavior1/5

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

No annotations are provided, and the description carries no behavioral disclosure. It does not state whether the operation is read-only, what happens on invalid state inputs, whether any authentication is required, or what kind of 'detailed information' will be returned. The description simply restates the tool's purpose without adding any behavioral context.

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 a single, concise sentence that front-loads the core purpose. There is no unnecessary padding or repetition. For a tool with one parameter and a straightforward function, this length is appropriate.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness2/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

With no output schema and no annotations, the description needs to compensate by explaining what 'detailed information' includes and what the caller can expect. It does not describe the return format, potential errors, or any caveats. The description is too sparse to be considered complete for an agent to reliably invoke and interpret results.

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?

The input schema fully describes the 'state' parameter with examples of kebab-case values, giving 100% coverage. The tool description itself does not add any parameter-specific meaning beyond what the schema provides. Since schema coverage is high, the baseline of 3 applies.

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?

The description clearly states the tool's function: getting detailed information about gambling license types for a specific US state. It uses a specific verb ('Get') and resource ('gambling license types'). While it doesn't explicitly distinguish itself from sibling tools like 'get_compliance_requirements' or 'compare_jurisdictions', the focus on license types is reasonably distinct.

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

Usage Guidelines2/5

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

The description provides no guidance on when to use this tool versus alternatives. It does not mention sibling tools like 'calculate_fees' or 'compare_jurisdictions', nor does it specify any prerequisites or exclusions. Usage is only implicit through the tool name and description.

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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