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lzinga

US Government Open Data MCP

by lzinga

usa_spending_by_state

Read-onlyIdempotent

Find federal spending totals and per-capita awards for any state or territory by fiscal year.

Instructions

Get federal spending by state or territory. Shows total awards and per-capita spending.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
stateNoTwo-letter state code (e.g. 'CA'). Omit for all states.
fiscal_yearNoFiscal year (default: most recent)

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changedv2026.4.11
    • removedInput schema / additionalProperties
      Removed value: -false
  2. First observedv2026.3.9

TDQS

A3.6/5.0
Behavior3/5

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

Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, covering the safety profile. The description adds that the tool returns total awards and per-capita spending, but does not disclose data freshness, update frequency, or any other behavioral quirks. With annotations present, this is adequate but not exceptionally informative.

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?

Two concise sentences front-load the main action and expected output, with no redundant phrases or unnecessary details. Every word contributes to the agent's understanding.

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?

For a simple two-parameter, read-only tool with annotations and a complete schema, the description covers the essential purpose and output metrics. However, since there is no output schema and the response structure is not detailed beyond the two metrics, it is not fully comprehensive.

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?

Both parameters are fully described in the input schema, including the two-letter state code example and the default for fiscal_year. The description does not add extra meaning beyond the schema, so it meets the baseline of 3 for high schema description coverage.

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 uses a specific verb ('Get') and resource ('federal spending by state or territory'), and clarifies the output ('total awards and per-capita spending'). This clearly distinguishes it from sibling USAspending tools like usa_spending_by_award, usa_spending_by_agency, and usa_spending_by_recipient, which focus on different dimensions.

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 the sibling USAspending tools (by_award, by_agency, by_recipient, over_time). The description does not mention any exclusions, alternatives, or criteria for selection, leaving the agent to infer the right choice from tool names alone.

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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