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vishalsachdev

Canvas MCP Server

by vishalsachdev
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Python
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get_student_analytics

Read-only

Get per-student engagement metrics including page views, participations, and on-time/late/missing assignment counts, with an engagement score to identify disengaged students in participation-driven courses.

Instructions

Get per-student engagement analytics: page views, participations, and on-time/late/missing assignment counts.

    Uses Canvas's /analytics/student_summaries endpoint to return a ranked table of every
    student in the course with an engagement score (0-100) useful for identifying disengaged
    students in participation/presentation-driven courses.

    Args:
        course_identifier: Course code or Canvas ID
        include_participation: Include participation counts (default: True)
        include_assignment_stats: Include on-time/late/missing counts (default: True)
        include_access_stats: Include page view counts (default: True)
        sort_by: Sort order — "engagement_score" (default, ascending), "page_views", "participations", or "name"

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
course_identifierYes
include_participationNo
include_assignment_statsNo
include_access_statsNo
sort_byNoengagement_score

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Tool Definition Quality

A4.4/5.0
Behavior4/5

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

Annotations already indicate readOnlyHint=true, and the description adds detail about using a specific Canvas endpoint and returning a ranked table with engagement scores. No contradictions. It could mention pagination or limits, but the provided info is sufficient.

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 somewhat lengthy due to the Args block, but it is front-loaded with the purpose and use case. Every sentence adds value, though it could be slightly more compact.

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 an output schema present, the description does not need to explain return values. It covers purpose, usage context, parameters, and the underlying endpoint. It is complete for practical use.

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 includes a detailed 'Args:' section explaining each parameter, including defaults and purpose. This fully compensates for the missing schema descriptions.

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's purpose: 'Get per-student engagement analytics: page views, participations, and on-time/late/missing assignment counts.' It also mentions the engagement score and its use case, distinguishing it from sibling tools like get_assignment_analytics.

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 indicates the tool is 'useful for identifying disengaged students in participation/presentation-driven courses,' providing context for when to use it. However, it does not explicitly state when not to use or mention alternatives, though the sibling list implies differentiation.

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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