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dathere

FBI Crime Data MCP Server

by dathere

get_nibrs_data

Query NIBRS incident-based crime statistics for 70+ offense types at national, state, or agency level, filtered by date range and aggregated by year or month.

Instructions

Get NIBRS incident-based crime data for 70+ offense types.

Args: offense: NIBRS offense code (e.g., "13A" for aggravated assault, "09A" for murder, "11A" for rape, "120" for robbery, "220" for burglary). Use get_reference_data for full list. level: Geographic level — "national", "state", or "agency" from_date: Start date in mm-yyyy format (e.g., "01-2020") to_date: End date in mm-yyyy format (e.g., "12-2022") data_type: "counts" for time series data or "totals" for aggregate breakdowns (default: "counts") state: Two-letter state abbreviation (required when level is "state") ori: Agency ORI code (required when level is "agency") aggregate: Aggregation level — "yearly" (default, sums monthly into yearly) or "monthly" (monthly granularity). Only applies when data_type is "counts".

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
oriNo
levelYes
stateNo
offenseYes
to_dateYes
aggregateNoyearly
data_typeNocounts
from_dateYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior3/5

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

No annotations are provided, so the description carries full burden. It describes the data retrieval operation but does not explicitly state side effects, permissions, or read-only nature. The description implies a safe read operation but lacks explicit behavioral disclosure beyond data format.

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 well-structured with a clear purpose and Args section. While it is somewhat lengthy, every sentence provides value. Minor fluff could be trimmed, but overall it is effective and well-organized.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the presence of an output schema (context signals indicate 'Has output schema: true'), the description focuses on input parameters and usage. It covers all 8 parameters, required vs optional, defaults, and links to reference data, making it complete for the tool's complexity.

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

Parameters5/5

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

Schema description coverage is 0%, so the description must compensate. It does so thoroughly by explaining each parameter with examples, default values, conditional requirements, and data format constraints. This adds significant meaning beyond the schema structure.

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 'Get NIBRS incident-based crime data for 70+ offense types.' It uses a specific verb and resource, and distinguishes from sibling tools like get_arrest_data and get_hate_crime_data by focusing on NIBRS data.

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 provides detailed parameter guidance, including examples for offense codes and conditional requirements for level. It also references get_reference_data for a full offense list. However, it does not explicitly compare when to use this tool versus similar siblings like get_crime_trends or get_summarized_crime_data.

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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