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AI caller disclosure by state

ai_caller_disclosure
Read-only

What a US state requires when an automated or AI voice assistant answers a dealership's missed calls or places an approved outbound call: the AI disclosure rule, the consent rule for automated calls, the statute, the federal baseline, and what the assistant should say. All 50 states and DC. General information, not legal advice.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
stateYesState name or two-letter abbreviation
dealershipNoDealership name for the scripts

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A3.9/5.0
Behavior4/5

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

Annotations already declare readOnlyHint=true, indicating no side effects. The description adds that it covers all 50 states and DC, is general information, and not legal advice—useful context for an agent. However, it does not disclose behavior for invalid states or output format details, which are minor given the read-only nature.

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?

The description is a single, well-structured sentence that front-loads the core purpose ('What a US state requires') and uses a colon to enumerate the specific outputs. It is concise but packs necessary information 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?

With no output schema, the description lists what the agent can expect (rule, consent, statute, federal baseline, script guidance), which is sufficient for a simple lookup tool. It does not mention error handling for invalid states, but that is a minor gap given the read-only nature and clear parameter validation implied by the schema.

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 descriptions already cover both parameters ('State name or two-letter abbreviation' and 'Dealership name for the scripts'). The description adds context that the dealership name is used for scripts ('what the assistant should say'), but it does not clarify the optionality of the dealership parameter or provide additional format details beyond the 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's purpose: it provides state-specific requirements for AI caller disclosure, including the rule, consent rule, statute, federal baseline, and script guidance. This is specific and distinct from sibling tools that handle call scoring, follow-ups, or other topics.

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?

The description implies usage when a user needs state-specific disclosure rules, but it does not explicitly state when to use this tool versus alternatives or when not to use it. The caveat 'General information, not legal advice' is a disclaimer rather than usage 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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