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cyntrica

Gov Data MCP

by cyntrica

fbi_crime_summarized

Read-only

Retrieve summarized FBI UCR crime data by offense, location, and year. Provides counts and rates for violent crime, property crime, and specific offenses at national, state, or agency level.

Instructions

Get summarized UCR crime data from the FBI at national, state, or agency level. Covers 10 offense categories: V (violent crime), P (property crime), HOM (homicide), RPE (rape), ROB (robbery), ASS (aggravated assault), BUR (burglary), LAR (larceny/theft), MVT (motor vehicle theft), ARS (arson). Returns year-by-year data with counts and rates.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
oriNoAgency ORI code for agency-level data (e.g., 'WASPD0000')
stateNoTwo-letter state abbreviation for state-level data
offenseYesUCR offense code: 'V' (Violent Crime), 'P' (Property Crime), 'HOM' (Homicide), 'RPE' (Rape), 'ROB' (Robbery), 'ASS' (Aggravated Assault), 'BUR' (Burglary), 'LAR' (Larceny/Theft), 'MVT' (Motor Vehicle Theft), 'ARS' (Arson)
to_yearNoEnd year (default: current year)
from_yearNoStart year (default: 5 years ago)
Behavior4/5

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

The description adds behavioral context beyond the readOnlyHint annotation by specifying that it returns year-by-year data with counts and rates. It also clarifies the scope levels. However, it doesn't mention how conflicting parameters (e.g., both state and ori) are handled, which is a minor gap.

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 three sentences, front-loaded with the core purpose, and every sentence provides useful information (levels, offense codes, return format). No wasted words or 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 output schema, the description adequately explains return values (year-by-year counts and rates). It covers the required offense parameter and the optional level selectors. It could be slightly more complete by noting potential default year ranges, but the schema already handles those details.

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?

Schema coverage is 100%, so baseline is 3. The description adds semantic value by implying that national level is the default when neither state nor ori is provided, which is not explicitly stated in the schema. This helps the agent understand the parameter selection behavior.

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 gets summarized UCR crime data at national, state, or agency level, with a specific verb ('Get') and resource. It lists the 10 offense categories, making it distinct from sibling FBI tools like fbi_arrest_data or fbi_nibrs.

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?

No guidance is provided on when to use this tool versus alternatives such as fbi_arrest_data or fbi_nibrs. It doesn't state exclusions or prerequisites, leaving the agent to infer from the word 'summarized' without explicit direction.

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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