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Dathis

ZHAW Moodle MCP Server

by Dathis

moodle_get_deadlines

Read-onlyIdempotent

Lists upcoming assignment and quiz deadlines across courses, sorted by date, to show what needs submission within a set period. Excludes completed items; optionally includes overdue from last 30 days.

Instructions

Open to-dos with deadlines across all courses (assignment due dates, quiz closing times, ...), sorted by date. Answers "What do I need to submit this week?". Activities already completed are not listed.

    Args:
        days_ahead: how far to look ahead (days)
        course_id: restrict to one course
        include_overdue: also list overdue to-dos from the last 30 days
    

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
course_idNo
days_aheadNo
include_overdueNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
nowYes
noteNoOnly open to-dos are listed; completed activities are omitted by Moodle.
untilYes
deadlinesYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.3.0

TDQS

A4.6/5.0
Behavior4/5

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

Annotations already establish read-only, idempotent, and open-world behavior, so the description adds valuable behavioral details: results are sorted by date, completed activities are omitted, and overdue items are drawn from the last 30 days when enabled. This goes beyond what annotations provide without contradicting them.

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 compact and front-loaded: a one-sentence purpose statement, a clarifying example query, a succinct filtering note, and a clean parameter list. Every sentence earns its place and there is no redundant restatement of the tool name or schema.

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 simple, read-only tool with three optional parameters and an output schema, the description covers scope, filtering behavior, sorting, and the overdue window. Nothing essential is missing to help an agent select and invoke it correctly.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters5/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 0%, but the description fully compensates with an Args block explaining all three parameters in plain language: days_ahead, course_id, and include_overdue. Each parameter's meaning is clear and directly usable by an agent.

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 returns open to-dos with deadlines across all courses, sorted by date, with concrete examples like assignment due dates and quiz closing times. It also frames the purpose with a natural-language question, which distinguishes it from sibling tools like moodle_list_assignments or moodle_get_recent_changes.

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?

The description explicitly tells the agent when to use the tool by tying it to the query 'What do I need to submit this week?' and clarifies that completed activities are excluded. It does not explicitly discuss when not to use it or alternatives, but the usage context is clear and actionable.

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