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LearnUs local MCP server

learnus_upcoming

Read-onlyIdempotent

Lists LearnUs calendar events and deadlines within a date range, optionally for one course. Use it to answer schedule or deadline questions for specific dates.

Instructions

Lists canonical LearnUs calendar events and deadlines in a date range, optionally for one course. Use when the user asks for calendar events, schedules or deadlines between specific dates. Do not use it to infer task completion or required attendance; use learnus_get_weekly_tasks for actionable weekly coursework. Date-only values use Asia/Seoul; timestamps require a timezone.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
toYesInclusive range end as YYYY-MM-DD in Asia/Seoul or an ISO 8601 timestamp with timezone.
fromYesInclusive range start as YYYY-MM-DD in Asia/Seoul or an ISO 8601 timestamp with timezone.
limitNoMaximum number of calendar events to return after date and course filtering.
courseIdNoExact Moodle course ID returned by a LearnUs course tool.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A4.3/5.0
Behavior4/5

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

Annotations already declare read-only, idempotent, open-world, non-destructive, so the safety profile is covered. The description adds genuinely useful behavior beyond that: 'canonical' events (implying deduplicated/authoritative source), the date-only Asia/Seoul default, and that timestamps require a timezone. It doesn't disclose return shape or the limit/pagination behavior, keeping it short of a 5.

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?

Four short sentences, front-loaded with purpose then trigger then exclusion then timezone caveat. Slightly redundant since the timezone rule is also encoded in the schema, but every sentence is otherwise doing work.

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?

With 4 fully documented params, no nested objects and no output schema, the description covers what an agent needs to select and call the tool: scope, filtering by course, timezone handling, and the sibling to prefer for tasks. Return format is not specified, but with no output schema that is a minor gap.

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?

Schema description coverage is 100%, and each of the four params is documented in-schema, so the baseline is 3. The description's timezone sentence largely restates what the from/to schema descriptions already say, adding little parameter-level meaning of its own.

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?

States a specific verb (Lists), resource (canonical LearnUs calendar events and deadlines), scope (date range, optionally one course). It names the sibling it is not (learnus_get_weekly_tasks), so an agent can distinguish it without opening any schema.

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

Usage Guidelines5/5

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

Gives an explicit trigger ('user asks for calendar events, schedules or deadlines between specific dates'), an explicit exclusion ('do not use it to infer task completion or required attendance'), and names the correct alternative for that case. Nothing is left to inference.

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