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dathere

FBI Crime Data MCP Server

by dathere

get_leoka_data

Fetch LEOKA data on law enforcement officers killed and assaulted, including weapons, circumstances, officer and offender demographics. Supports monthly or year-to-date reports.

Instructions

Get LEOKA data on law enforcement officers killed and assaulted, including weapons used, circumstances, officer demographics, and offender demographics.

Args: report_type: "monthly" for a specific month or "ytd" for year-to-date summary year: Year for the data (e.g., 2022) month: Month number 1-12 (January=1, December=12). Required when report_type is "monthly".

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
yearYes
monthNo
report_typeYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior3/5

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

No annotations provided, so description carries full burden. Discloses data content but omits behavioral traits like authentication, rate limits, or side effects. Adequate for a read-only retrieval tool.

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?

Description is concise with a brief overview and structured parameter list. Front-loaded with key information, no redundant sentences.

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

Completeness3/5

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

Output schema exists but isn't shown; description mentions data categories but not structure or field names. Complete enough for basic use but could detail return format given 3 parameters and no output schema in description.

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 0%, so description compensates well. Explains each parameter clearly: report_type values, year, month dependency on report_type. Adds meaning beyond schema.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool retrieves LEOKA data on law enforcement officers killed and assaulted, specifying the resource and verbs. It distinguishes from siblings by focusing on a specific dataset, though it could explicitly differentiate from similar tools.

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 on when to use this tool versus alternatives or prerequisites. The description explains parameters but lacks context on when to choose this tool over siblings.

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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