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Check Watched Course Sections

check_watched_course_sections

Checks OBS schedule for watched sections, reporting capacity, enrollment, free seats, and status changes (opened, filled). First check sets baseline; cached data may delay updates.

Instructions

Read the public OBS schedule now for the watched sections (one request per branch, no login) and report per section: capacity, enrolled, seats free, and what changed since the previous check ('opened', 'filled', 'capacity_raised', 'delisted', ...). The first check of a section only sets a baseline. Status 'unknown' means OBS gave no usable numbers (missing values, or the enrolled column not populated yet) and is never a free seat; 'not_listed' means the CRN is absent from the schedule, which is not the same as full. Entries from a past term are reported as 'stale_term' and not compared. This is a one-shot check: the server cannot run in the background and sends no notifications, so a periodic check must be driven by the user or by a scheduled task on the client. Schedule reads are cached for a short time; when 'freshness.all_from_cache' is true the numbers were not re-read, so wait 'retry_after_seconds' instead of calling again in a loop.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. Addedv1.2.1

TDQS

A4.6/5.0
Behavior5/5

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

Goes well beyond annotations with concrete semantics: status meanings ('unknown' is never a free seat, 'not_listed' ≠ full, 'stale_term' is not compared), first-check baseline behavior, no background execution/notifications, and short-lived schedule caching with a freshness flag and retry delay. This is exactly the kind of state/caching disclosure the structured fields cannot carry.

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?

Front-loaded with the core action, then status semantics, then one-shot/caching constraints. It is dense but every sentence carries operational information; slightly long, yet no filler or repetition to cut.

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

Completeness5/5

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

For a zero-parameter check with an output schema, the description supplies everything an agent needs: what to expect, how to read the statuses, and how to behave under caching. Return-value structure is covered by the output schema, so no gap remains.

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 per the rules the baseline is 4; the description correctly implies the operation is parameterless and identifies the watched set as the implicit input. Nothing further is needed on parameter semantics.

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?

Opens with a specific verb+resource+scope: 'Read the public OBS schedule now for the watched sections (one request per branch, no login).' It immediately names what is reported per section (capacity, enrolled, seats free, changes), which distinguishes it from sibling watch/unwatch/list-watched tools. No ambiguity about what the call does.

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?

Gives clear operating context: it is a one-shot check, cannot run in the background, and 'a periodic check must be driven by the user or by a scheduled task on the client.' It also tells the caller not to loop when 'freshness.all_from_cache' is true and to wait 'retry_after_seconds' instead. It stops short of explicitly naming a sibling alternative (e.g., watch_course_sections to add sections first), so not a 5.

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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