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unw-mcp

unw-mcp

by HenryGetz
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Local

unw_profile

Retrieves a student's Degree Works profile, including majors, credits, GPA, academic standing, and graduation outlook, so agents can inspect advising and audit context.

Instructions

Student profile from Degree Works: name, id, classification, degree/school, catalog year(s), majors, minors, programs, college, advisors, credits earned and in progress, GPA, percent complete, anticipated graduation, academic standing and holds. Holds are not exposed by the mapped APIs: null = unknown.

Tool call template

This tool declares no required parameters. Add optional parameters from the input schema as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {},
    "name": "unw_profile"
  }
}

Input Schema

NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

B3.3/5.0
Behavior3/5

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

With no annotations, the description carries the full burden. It does disclose a genuine behavioral caveat beyond structured data: holds are not exposed by the mapped APIs, and null means unknown rather than 'no holds.' However, it never states whose profile is returned (no parameters exist), nor whether authentication or student-context is required, leaving key invocation behavior unstated.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

A single dense sentence lists the returned fields, front-loaded with the source system, followed by one short caveat sentence about holds. There is little waste, though the flat field list is long and could be grouped more readably.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness3/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

With no output schema, the description must describe returns, and it does so thoroughly, plus it flags the holds data gap. It falls short on the implicit input question: with zero parameters, the description never explains whose profile is fetched or what happens when no student context exists.

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?

The tool takes zero parameters, so there is nothing to document and the baseline is 4. The description's field inventory usefully frames what the implicit (current-student) input resolves to.

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?

Names a specific resource ('Student profile from Degree Works') and enumerates the fields it returns (classification, majors, GPA, holds, etc.), so an agent knows exactly what data comes back. It does not distinguish itself from siblings like unw_audit or unw_remaining, which return overlapping academic-progress data.

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?

The description contains no when-to-use guidance, no exclusions, and no mention of any alternative. Because siblings such as unw_audit and unw_remaining also surface academic standing and progress, an agent gets no help deciding which to call for a given question.

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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