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lzinga

US Government Open Data MCP

by lzinga

scorecard_compare

Read-onlyIdempotent

Compare colleges side-by-side on cost, graduation rate, earnings, and debt. Enter school names to get a direct comparison.

Instructions

Compare specific colleges side-by-side on cost, graduation rate, earnings, and debt. Provide school names to search and compare.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
schoolsYesComma-separated school names to compare: 'Harvard,MIT,Stanford' or 'Ohio State,Michigan'

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 carry readOnlyHint=true, idempotentHint=true, and destructiveHint=false, so the safety profile is covered. The description adds modest behavioral context by naming the exact comparison dimensions (cost, graduation rate, earnings, debt), but doesn't disclose output format, result limits, or data source behavior. No contradiction with 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?

Two sentences with zero waste: the first front-loads the core purpose with specific metrics, the second gives the input requirement. Every sentence 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 single-parameter, read-only comparison tool with full annotation coverage and a fully documented schema, the description is nearly complete. The listed comparison dimensions hint at the return content since there's no output schema. Minor gap: no mention of how many schools can be compared or the result format.

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% — the schema already documents the schools parameter with concrete format examples ('Harvard,MIT,Stanford'). The description only echoes 'Provide school names' without adding format, delimiters, or edge-case semantics beyond what the schema provides, so baseline 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?

States a specific verb ('compare') with a specific resource ('specific colleges') and scope ('side-by-side on cost, graduation rate, earnings, and debt'). This clearly distinguishes it from the other scorecard siblings (scorecard_search, scorecard_top, scorecard_query) whose purposes are find/rank/query rather than direct comparison.

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 phrase 'Provide school names to search and compare' implies the usage context — you should already have specific schools in mind rather than needing discovery. However, it never names alternatives or states when NOT to use it (e.g., scorecard_search for finding schools, scorecard_top for rankings), leaving routing to inference.

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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