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lzinga

US Government Open Data MCP

by lzinga

usa_spending_over_time

Read-onlyIdempotent

Aggregate federal spending by month, quarter, or fiscal year to identify trends and analyze budget patterns.

Instructions

Get federal spending aggregated by time period (monthly, quarterly, or fiscal year). Useful for identifying trends.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
groupNoTime grouping (default: month)
stateNoTwo-letter state code, e.g. 'CA', 'TX'
agencyNoFilter to specific agency name
keywordNoKeyword to filter spending
end_dateNoEnd date YYYY-MM-DD (default: today)
award_typeNoAward type filter
start_dateNoStart date YYYY-MM-DD (default: 3 years ago)

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

A3.8/5.0
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 the core aggregation-by-time-period behavior but no additional behavioral context such as response format, pagination, or rate limits. With annotations carrying most of the burden, a 3 is appropriate.

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 short sentences with no fluff. The action is front-loaded, and the second sentence adds a legitimate use case. Every word earns its place.

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 read-only aggregation tool with 7 fully documented parameters, no required parameters, and no output schema, the description plus schema is sufficient. The absence of return-value details is acceptable given the tool's simplicity, though a quick note about the expected time-series response shape would be a minor improvement.

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% — every parameter (group, state, agency, keyword, end_date, award_type, start_date) has a description, and two parameters have enums. The tool description adds no parameter-level meaning beyond the schema, so the baseline of 3 applies.

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 aggregated by time period'), and clearly differentiates from sibling tools like usa_spending_by_award or usa_spending_by_state by emphasizing temporal aggregation rather than breakdowns by award, agency, state, or recipient. The grouping options (monthly, quarterly, fiscal year) are explicitly stated.

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 says 'Useful for identifying trends,' which implies a use case, but it provides no explicit guidance on when to choose this tool over the sibling spending tools (e.g., usa_spending_by_agency, query_fiscal_data) and does not mention when not to use it. Usage is only implied, not explicitly directed.

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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