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by io.github.whiteknightonhorse
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Search US Colleges

education.colleges.search
Read-onlyIdempotent

Search US colleges and universities — admissions, tuition, enrollment, earnings, completion rates (College Scorecard)

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
nameNoSchool name to search for (e.g. "MIT", "Stanford", "Community College").
limitNoNumber of results to return (1-50). Default: 10.
stateNoUS state abbreviation (e.g. "CA", "NY", "TX").
programNoField of study filter (e.g. "Computer Science", "Nursing", "Business").
degree_typeNoFilter by predominant degree type awarded.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
errorNoPresent only when the call failed. Includes error code, message, request_id, and any provider-specific extras.
resultNoTool response payload. Shape varies per tool — consult the tool description and inputSchema. May be an object, array, string, or number depending on the upstream provider response.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Added
  2. Removed
  3. First observed

TDQS

A3.8/5.0
Behavior4/5

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

Annotations already indicate read-only, non-destructive, idempotent, and open-world behavior. The description adds context about the data source (College Scorecard) and specific metrics, enhancing transparency.

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?

The description is a single, informative sentence with no wasted words, front-loaded with the verb and specific data points.

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?

Given the rich annotations, complete schema coverage, and output schema, the description adequately covers purpose and data types, though it misses usage guidelines.

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%, so the baseline is 3. The description does not add additional meaning beyond what the schema already provides for the parameters.

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 clearly states it searches US colleges and universities and lists specific data categories (admissions, tuition, etc.), distinguishing it from sibling tools like education.colleges.details.

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 on when to use this tool versus alternatives (e.g., education.colleges.details) or exclusions. The description lacks explicit usage context.

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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