Skip to main content
Glama

unw_audit

Inspect structured degree-audit requirement trees with groups, blocks, course options, and applied/in-progress/transfer flags, optionally filtering by group to locate remaining requirements.

Instructions

Structured degree-audit requirement tree (groups -> blocks -> course options, with applied/in-progress/transfer flags). group filters by a case-insensitive substring of a group title/kind or block label.

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_audit"
  }
}

Input Schema

NameRequiredDescriptionDefault
groupNo

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 and does disclose the return shape (a tree with per-course status flags), which is valuable given there is no output schema. It does not state that the operation is read-only, whether the full tree is returned when unfiltered, or anything about result size or permissions.

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?

Two tight sentences that lead with what the tool returns and follow with the filter semantics; no filler. The parenthetical hierarchy notation is dense but efficient.

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?

For a single-parameter read tool with no output schema, the description covers the return structure and the filter well, but leaves open what happens with no filter and how large the response can be. Adequate, with a clear remaining gap.

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 0% for the single 'group' parameter, so the description must compensate, and it does: it specifies case-insensitive substring matching and the exact fields matched (group title/kind or block label). That is meaningfully more than the schema's bare 'Group' string.

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?

The description names the specific resource: a structured degree-audit requirement tree with an explicit hierarchy (groups -> blocks -> course options) and status flags (applied/in-progress/transfer). That is far more informative than the bare name 'unw_audit', though no verb (retrieve vs. compute) is stated and no sibling such as unw_remaining or unw_roadmap is contrasted.

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?

There is no statement of when to call this versus alternatives like unw_remaining, unw_roadmap, or unw_conflicts, and no preconditions (e.g., whether the student must have a declared program). The only usage signal is implicit in the word 'audit'.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.