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lzinga

US Government Open Data MCP

fbi_expanded_property

Read-only

Retrieve expanded FBI property crime data including value and type of stolen/recovered property, premises involvement, for burglary, larceny, motor vehicle theft, and robbery offenses.

Instructions

Get expanded property crime details from the FBI (Supplemental Return / Return A data). Provides additional breakdowns beyond summarized counts: value of stolen/recovered property, type of property, premises involved. Available for burglary (NB), larceny (NL), motor vehicle theft (NMVT), and robbery (NROB).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
offenseYesOffense code: 'NB' (Burglary), 'NL' (Larceny), 'NMVT' (Motor Vehicle Theft), 'NROB' (Robbery)
stateNoTwo-letter state abbreviation for state-level data
oriNoAgency ORI code for agency-level data
typeNoData type (default: counts)
from_yearNoStart year
to_yearNoEnd year
Behavior3/5

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

Annotations already provide readOnlyHint=true, and the description is consistent. It adds context about the data source (Supplemental Return / Return A) and breakdown categories, but lacks details on rate limits, pagination, or any constraints like minimum year range. No contradiction.

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 with no wasted words. It front-loads the main purpose and then lists specific breakdowns and applicable offenses, making it easy to scan.

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 6 parameters and no output schema, the description provides sufficient context for the tool's purpose and data type. It covers the source (FBI Supplemental Return), breakdowns, and offense categories. It could mention the output format or limitations, but overall it is fairly complete for an API tool.

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 description coverage is 100%, so baseline is 3. The description adds value by explaining the overall breakdown categories and the meaning of offense codes (e.g., 'NB' for Burglary) which complements the enum descriptions. However, it does not elaborate on other parameters like state, ori, or type beyond what the schema already provides.

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 it retrieves 'expanded property crime details' from the FBI, specifying the type of data (value of stolen/recovered property, type of property, premises involved) and the applicable offenses (burglary, larceny, motor vehicle theft, robbery). This distinguishes it from sibling tools like fbi_crime_summarized which provide summarized counts.

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 it is for detailed breakdowns 'beyond summarized counts', but does not explicitly state when to use this tool over siblings. There is no guidance on when not to use it or alternatives, such as fbi_crime_summarized for higher-level aggregates.

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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