Every dated teaching activity (lectures, labs) for a course in a year, with Oslo-local times and rooms. Long output for large courses — prefer get_weekly_timetable for a compact recurring-week overview.
| Name | Required | Description | Default |
|---|---|---|---|
| year | Yes | ||
| course_code | Yes |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided. Description warns about long output for large courses but does not disclose whether it is read-only, requires auth, or any other behavioral traits. Lacks full transparency expected without annotations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Two succinct sentences, front-loaded with core purpose, followed by a helpful usage hint. No unnecessary words.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given no output schema and incomplete parameter info, the description lacks details on output structure, pagination, time zone handling, or date formats. The hint about long output is useful but overall incomplete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0% and the description adds no information about the parameters (course_code, year) beyond their names. No mention of format, range, or examples, leaving the agent with insufficient guidance.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
Description explicitly states the tool retrieves all dated teaching activities (lectures, labs) for a course in a year with Oslo-local times and rooms. It clearly distinguishes from sibling get_weekly_timetable by noting the long output and suggesting the alternative for compact overview.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
Provides clear context: use for detailed schedule, prefere get_weekly_timetable for compact recurring-week overview. However, no explicit when-not or prerequisites beyond this single alternative.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.
Each tool targets a distinct aspect of NTNU course data: scheduling, exams, grades, comparisons, search, etc. Overlaps like get_course_schedule and get_weekly_timetable are clearly differentiated by granularity, with descriptions guiding usage.
All tools follow a verb_noun pattern in snake_case, using simple verbs like 'get', 'search', 'check', and 'compare'. The naming is uniform and predictable across all 12 tools.
12 tools is well-scoped for an informational server covering courses, schedules, exams, grades, study plans, and search. Each tool serves a clear purpose without unnecessary redundancy.
The tool set covers core CRUD-like operations for course data, including search, info retrieval, scheduling, exams, grades, and study plans. Minor gaps exist, such as no dedicated tool for study program details or room information, but overall the surface is comprehensive for the domain.