Skip to main content
Glama

search_courses

Read-only

Find University of Vienna courses by keyword, course number, lecturer, or semester. Use free-text queries to discover what is taught or who teaches a specific subject.

Instructions

Free-text search over all u:find courses (Lehrveranstaltungen).

Matches titles, LV numbers, lecturer names and semester codes. Use for "is there a course about X" or "what does lecturer Y teach".

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNoMaximum courses.
queryYesKeywords, e.g. "logik", "180013", "Schnieder sprachphilosophie".
semesterNoSemester code such as "2026W" (winter 2026/27) or "2027S". Also accepts "current", "next", "previous". Defaults to the current semester. Pass "" to search all semesters.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A4.2/5.0
Behavior4/5

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

The description mentions that it searches over multiple fields and defaults to the current semester, which is useful. It also notes that passing an empty semester searches all semesters knowledge not in annotations. However, it doesn't detail result ordering or that it's a free-text fuzzy search, but the annotation openWorldHint=true indicates infeasible queries may return empty results.

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 concise, with three well-structured lines. It front-loads the primary purpose and then provides field scope and usage examples. Every sentence delivers value without redundancy.

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?

The tool is relatively simple with 1 required parameter, and the schema covers all parameters. The description gives enough context for an agent to construct queries and handle the semester filter. However, it doesn't mention what the output contains (though an output schema exists), nor discuss potential latency or rate limits, but that's acceptable given the output schema exists and the operational context is not critical.

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?

All three parameters are described in the schema with examples (e.g., 'logik', '180013', semester codes). The description adds minimal extra meaning beyond the schema because the schema already covers coverage 100%. The description's mention of semester defaults and the empty string for all semesters is also found in the schema, so the extra value is limited.

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 the tool's purpose: free-text search over u:find courses, matching titles, LV numbers, lecturer names, and semester codes. It distinguishes itself from sibling tools by specifying the search scope and fields, and contrasts with structured lookups like get_course.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

It provides specific use cases ('is there a course about X' or 'what does lecturer Y teach'), which helps an agent know when to invoke it. However, it doesn't explicitly state when not to use it or mention alternatives like get_course for exact lookups, but the examples are sufficient for many scenarios.

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