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ahnopologetic

Canvas LMS MCP Server

list_calendar_events

Fetch calendar events for Canvas courses by providing course context codes. Optionally filter by start and end dates, and paginate through results to view assignments, deadlines, and course events.

Instructions

List calendar events for courses.

Args: context_codes: List of context codes (e.g., ["course_4538"]) start_date: Optional start date in ISO 8601 format end_date: Optional end date in ISO 8601 format page: Page number (1-indexed) items_per_page: Number of items per page

Returns: PaginatedResponse containing calendar events

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
context_codesYes
start_dateNo
end_dateNo
pageNo
items_per_pageNo
Behavior2/5

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

With no annotations, the description must disclose behavioral traits. It barely does: it mentions pagination (returns PaginatedResponse) and parameter formats, but omits crucial details like date inclusivity, timezone handling, authentication requirements, rate limits, or what happens on invalid input. The behavioral disclosure is insufficient.

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?

The description is a concise docstring with clear Args and Returns sections. It is front-loaded and efficient, though the parameter descriptions could be slightly more compact. Overall, it uses space well without redundancy.

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

Completeness3/5

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

Given the complexity (5 parameters, no output schema, no annotations), the description covers basic parameter info and return type. However, it lacks completeness on edge cases, error behavior, and the precise meaning of date range. It is adequate but has notable gaps for a tool with no annotations.

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?

Schema description coverage is 0%, so the description must add meaning. It provides format hints for dates (ISO 8601), an example for context_codes, and defaults for page and items_per_page. These additions help the agent construct proper parameters beyond the raw schema.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description states the purpose as 'List calendar events for courses', which clearly indicates the verb (list) and resource (calendar events). However, it does not differentiate this tool from sibling list tools like list_announcements or list_assignments, missing an opportunity to specify scope.

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

Usage Guidelines2/5

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

The description provides no guidance on when to use this tool versus alternatives. It does not mention prerequisites, conditions, or situations where a different tool would be more appropriate. This lack of usage direction makes it less helpful for an AI agent to decide correctly.

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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