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Who Represents This Address

Find representatives for up to 40 U.S. addresses

find_representatives_batch

Operated by an AI (RJH Signal Technologies LLC). Same as find_representatives for a list of 1 to 40 U.S. street addresses in one call (send it as a single JSON-RPC message, not inside a JSON-RPC array); returns {results:[...one lookup result (including state_executives and local.mayor) or error per address, in order], count, usage}. Each address counts as one lookup: the free tier (50 per day per IP address) refuses a batch larger than what is left today; Pro (X-API-Key) counts against the monthly quota.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
addressesYesU.S. street addresses including city, state and ZIP

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changed
    • changedInput schema / properties / addresses / maxItems
      Previous value: -100New value: +40
  2. Added

TDQS

A4.3/5.0
Behavior5/5

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

With no annotations, the description fully carries the behavioral burden. It discloses the operator, per-address lookup counting, free tier limits and refusal behavior, Pro quota behavior, the single-message JSON-RPC requirement, and the approximate return structure including per-address results/errors, count, and usage.

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 dense and information-rich, covering operator disclosure, batch usage, result shape, and quota rules in three sentences. The operator disclosure is somewhat auxiliary for tool selection, but overall there is no wasted repetition.

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?

Given that there is no output schema and no annotations, the description appropriately covers invocation format, auth/quota modes, top-level return shape, and per-address error behavior. It does not enumerate every field in a lookup result, but the provided structure is sufficient for an agent to call the tool 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?

The schema already fully describes the single 'addresses' parameter with item constraints, min/max items, and a description. The tool description adds batch-level context and quota semantics, but it does not need to explain the parameter further, so the baseline of 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?

The description opens with 'Same as find_representatives for a list of 1 to 40 U.S. street addresses in one call,' clearly identifying the operation, resource, and batch scope. It also differentiates this tool from the sibling find_representatives by emphasizing the list/one-call behavior and not being inside a JSON-RPC array.

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?

The description clearly frames the tool as the batch counterpart to find_representatives and gives specific invocation constraints such as sending it as a single JSON-RPC message. It does not explicitly state a decision rule like 'use find_representatives for a single address,' but the context strongly implies the appropriate use case.

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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