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lzinga

US Government Open Data MCP

by lzinga

fbi_agencies

Read-onlyIdempotent

Find law enforcement agencies in any U.S. state, grouped by county, with ORI codes and NIBRS participation dates. Use the ORI codes to query detailed FBI data across other tools.

Instructions

List law enforcement agencies in a U.S. state from the FBI CDE. Returns agencies grouped by county with ORI codes, coordinates, and NIBRS participation dates. Use ORI codes from this tool to query agency-level data in other FBI tools.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
stateYesTwo-letter state abbreviation (e.g., 'CA', 'TX', 'WA')

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changedv2026.4.11
    • removedInput schema / additionalProperties
      Removed value: -false
  2. First observedv2026.3.9

TDQS

A4/5.0
Behavior4/5

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

Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, so the safety profile is covered. The description adds valuable behavioral context beyond annotations by specifying the return structure (agencies grouped by county, with ORI codes, coordinates, and NIBRS participation dates). It doesn't mention pagination, rate limits, or error behavior, but the additional output details justify a score above the baseline.

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 two sentences, front-loaded with the primary purpose in the first sentence. The second sentence adds essential output details and a usage hint. There is zero fluff; every word serves a function.

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?

For a simple one-parameter list tool, the description covers the purpose, output content, and a usage pattern (ORI codes for other tools). The schema covers the parameter, and annotations cover safety. Minor gaps exist, such as no mention of pagination or result limits, but these are not critical given the tool's simplicity. It is nearly complete.

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 description for the only parameter 'state' is complete (100% coverage) with examples like 'CA', 'TX'. The tool description adds nothing about the parameter itself. Since the schema fully documents the parameter, a baseline of 3 is appropriate – no extra semantic value is provided by the description.

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 states a specific verb ('List'), a clear resource ('law enforcement agencies in a U.S. state from the FBI CDE'), and the output scope (grouped by county, with ORI codes, coordinates, and NIBRS participation dates). This unambiguously distinguishes it from other FBI tools like fbi_crime_summarized or fbi_arrest_data, which cover different data types.

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 gives a clear usage hint: 'Use ORI codes from this tool to query agency-level data in other FBI tools.' This tells the agent when to use it (to obtain ORI codes for downstream queries) but does not explicitly contrast it with sibling tools or state when not to use it. It lacks explicit alternatives or exclusion conditions, so it's adequate but not strong.

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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