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lzinga

US Government Open Data MCP

fbi_agencies

Retrieve FBI law enforcement agency listings by U.S. state, including ORI codes, county groupings, and NIBRS participation data for cross-referencing with other FBI 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')
Behavior4/5

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

With no annotations provided, the description carries the full burden. It discloses key behavioral traits: it returns data grouped by county with specific fields (ORI codes, coordinates, NIBRS participation dates), and mentions that ORI codes are used for other FBI tools. However, it doesn't cover potential limitations like rate limits, error handling, or data freshness.

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 front-loaded with the core purpose, followed by return details and usage guidance in two efficient sentences. Every sentence adds value 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?

Given no annotations, no output schema, and a simple parameter schema, the description is fairly complete: it explains what the tool does, what it returns, and how to use the output. However, it could improve by mentioning data format or any constraints on the state parameter beyond abbreviation.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The input schema has 100% description coverage for the single parameter 'state', but the description adds context by specifying it's for 'U.S. state' and implies the tool filters agencies by state. This enhances understanding beyond the schema's technical definition.

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 verb ('List') and resource ('law enforcement agencies in a U.S. state from the FBI CDE'), specifying the scope (U.S. state) and source (FBI CDE). It distinguishes from sibling tools by focusing on FBI agencies, unlike BEA, BLS, or other data tools in the list.

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

Usage Guidelines5/5

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

It explicitly states when to use this tool ('to query agency-level data in other FBI tools') and provides an alternative usage context by mentioning ORI codes for other FBI tools, though it doesn't name specific sibling alternatives. The guidance is clear for its intended workflow.

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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