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fbi_cde_compare_state_to_national

Read-onlyIdempotent

Compare one state's monthly FBI summarized UCR offense rate with the national rate in LiveDataLink's self-hosted CDE aggregate snapshot, including both reporting-coverage series, rate difference, ratio, pagination, and provenance. Use this for 'California versus U.S. robbery rates in 2023', 'give national context for one state's burglary trend', or 'does state-national comparison have a coverage caveat?'. This deliberately supports only the FBI-recommended state-to-national context—not state rankings, city league tables, causal claims, or individual risk decisions.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNoMaximum monthly observations. Default 24.
stateYesTwo-letter U.S. state or District of Columbia abbreviation; US is not accepted.
offsetNoMonthly observations to skip. Default 0.
offenseYesFBI CDE summarized offense category. Aggregate categories overlap their component offenses.
end_monthYesCalendar month in YYYY-MM format within the hosted snapshot.
start_monthYesCalendar month in YYYY-MM format within the hosted snapshot.
response_formatNoHuman-readable markdown or machine-readable JSON. Default markdown.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Added

TDQS

A4.1/5.0
Behavior4/5

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

Annotations already declare readOnly, idempotent, non-destructive, and open-world, so the safety profile is covered. The description adds useful operational context beyond annotations: both reporting-coverage series, rate difference, ratio, pagination, and provenance are returned, and it flags a coverage caveat. It stops short of detailing pagination behavior limits or snapshot staleness.

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?

Two sentences, front-loaded with the core comparison, then use cases and exclusions. The second sentence is dense but earns its length by listing outputs and boundary conditions; no filler.

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 no output schema, the description carries the burden of describing returns, and it does so by listing the coverage series, difference, ratio, pagination, and provenance. Combined with the exclusion list, an agent has enough to call it correctly; minor gaps remain about exact return shape.

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% and enums document state and offense constraints already. The description reinforces that only state-to-national comparisons are supported (US not accepted per schema) but adds no parameter-level detail beyond the schema, so baseline 3 is appropriate.

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 states a precise verb (compare) and resource (one state's monthly FBI UCR offense rate vs. the national rate) with clear scope. It does not name the adjacent siblings (fbi_cde_state_crime_trend, fbi_cde_national_crime_trend), so the differentiation from those is only implicit in the 'state-to-national' framing.

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 gives concrete triggering examples ('California versus U.S. robbery rates in 2023', 'national context for one state's burglary trend') and explicit exclusions (no state rankings, city league tables, causal claims, or individual risk decisions). This is textbook when-to-use plus when-not-to-use guidance.

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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