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lzinga

US Government Open Data MCP

by lzinga

scorecard_query

Read-onlyIdempotent

Search U.S. colleges by applying custom filters for admission rates, tuition, and graduate earnings.

Instructions

Advanced College Scorecard query with custom field filters and ranges.

Filter examples:

  • 'latest.admissions.admission_rate.overall__range=0..0.10' (schools with <10% admission rate)

  • 'latest.cost.tuition.in_state__range=..5000' (tuition under $5K)

  • 'school.degrees_awarded.predominant=3' (bachelor's-granting)

  • 'latest.earnings.10_yrs_after_entry.median__range=80000..' (high-earning graduates)

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
sortNoSort: 'latest.earnings.10_yrs_after_entry.median:desc'
filtersYesSemicolon-separated filter params: 'school.state=CA;latest.admissions.admission_rate.overall__range=0..0.20;school.degrees_awarded.predominant=3'
per_pageNoResults per page (default 20)

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changedv2026.9.14
    • addedInput schema / properties / per_page / default
      Added value: +20
  2. Changed1 schema field changedv2026.4.11
    • removedInput schema / additionalProperties
      Removed value: -false
  3. First observedv2026.3.9

TDQS

A3.7/5.0
Behavior3/5

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

Annotations already provide readOnlyHint, idempotentHint, and destructiveHint false, covering the safety profile. The description adds filter syntax and range semantics, which is helpful but not behavioral disclosure about side-effects, pagination, or limitations. It does not contradict annotations.

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?

One-sentence purpose followed by four bullet examples, each self-explanatory. No wasted words, front-loaded, and easy to scan. Ideal size for the content.

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 3-parameter query tool with no output schema, the description plus schema adequately cover the main usage (custom filters/ranges). The filter examples are critical and well-covered. It lacks explicit description of response format, but annotations and schema handle the rest sufficiently.

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 100%, so baseline is 3. The description adds meaningful semantics for the filters parameter through multiple examples explaining range syntax and dotted field paths, going beyond the schema's single example. It does not mention sort, but the schema already documents it with an example.

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?

Description states 'Advanced College Scorecard query with custom field filters and ranges' – a specific verb, resource, and distinctive capability. It is clear but does not explicitly differentiate from sibling tools like scorecard_search, though the 'Advanced' qualifier hints at the distinction.

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 filter examples imply usage scenarios (e.g., low admission rates, low tuition, bachelor's-granting, high earnings), but there is no explicit statement of when to use this tool versus scorecard_search, scorecard_compare, or scorecard_top. No exclusions or alternative routing.

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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