vishalsachdev/canvas-mcp

canvas-morning-check

Educator morning course health check for Canvas LMS.

Quelltext ansehen

Verwendung

  1. Installationsbefehl kopieren und das Quellpaket vor der Installation in der eigenen Agentenumgebung prüfen.
  2. Benötigte Werkzeuge, Zugangsdaten und Hosts im Original prüfen.
  3. Eingabe und gewünschtes Ergebnis beschreiben und die Ausgabe mit den Quellen abgleichen.
npx skills add https://github.com/vishalsachdev/canvas-mcp --skill canvas-morning-check

Vor dem Start

  • Die Installation umfasst weder Modellabo noch API-Kontingent oder Dateizugriffsrechte.
  • Sterne und Installationen zeigen Aktivität, keine unabhängige Qualitäts- oder Sicherheitsprüfung.
Originales Skill-Dokument

Aus dem Quell-Repository gerendert; Überschriften, Beispiele, Code, Tabellen, Links und Bilder bleiben erhalten.

Canvas Morning Check

A comprehensive course health check for educators using Canvas LMS. Run it at the start of a teaching day or week to surface submission gaps, students who need support, and upcoming deadlines -- then take action directly from the results.

Prerequisites

  • Canvas MCP server must be running and connected to the agent's MCP client.
  • The authenticated user must have an educator or instructor role in the target Canvas course(s).
  • FERPA-conscious handling: Set ENABLE_DATA_ANONYMIZATION=true in the Canvas MCP server environment to anonymize supported student identity fields in output. When enabled, names render as Student_xxxxxxxx hashes. This control does not by itself establish compliance.

Steps

1. Identify Target Course(s)

Ask the user which course(s) to check. Accept a course code, Canvas ID, or "all" to iterate through every active course.

If the user does not specify, prompt:

Which course would you like to check? (Or say "all" for all active courses.)

Use the list_courses MCP tool if you need to look up available courses.

2. Collect Recent Submission Data

For each target course:

  1. Call list_assignments to find assignments with a due date in the past 7 days.
  2. For each recent assignment, call get_assignment_analytics to collect:
  • Submission rate (submitted / enrolled)
  • Average, high, and low scores
  • Late submission count

3. Identify Struggling Students

Call list_submissions to retrieve student submission records, then flag students based on these thresholds:

UrgencyCriteria
CriticalMissing 3+ assignments in the past 2 weeks, or average grade below 60%
Needs attentionMissing 2 assignments, or average grade 60--70%, or 3+ late submissions
On trackAll submissions current, grade above 70%

Use get_student_analytics for deeper per-student analysis when the user requests it.

4. Check Upcoming Deadlines

Call list_assignments filtered to the next 7 days. For each upcoming assignment, surface:

  • Assignment name
  • Due date and time
  • Point value
  • Current submission count (if submissions have started)

5. Generate the Status Report

Present results in a structured format:

## Course Status: [Course Name]

### Submission Overview
| Assignment | Due Date | Submitted | Rate | Avg Score |
|------------|----------|-----------|------|-----------|
| Quiz 3     | Feb 24   | 28/32     | 88%  | 85.2      |
| Essay 2    | Feb 26   | 25/32     | 78%  | --        |

### Students Needing Support
**Critical (3+ missing):**
- Student_a8f7e23 (missing: Quiz 3, Essay 2, HW 5)

**Needs Attention (2 missing):**
- Student_c9b21f8 (missing: Essay 2, HW 5)
- Student_d3e45f1 (missing: Quiz 3, Essay 2)

### Upcoming This Week
- **Mar 3:** Final Project (100 pts) - 5 submitted so far
- **Mar 5:** Discussion 8 (20 pts)

### Suggested Actions
1. Send reminder to 3 students with critical status
2. Review Essay 2 submissions (78% rate, below average)
3. Post announcement about Final Project deadline

6. Offer Follow-up Actions

After presenting the report, offer actionable next steps:

Would you like me to: 1. Draft and send a message to struggling students (uses send_conversation) 2. Send reminders about upcoming deadlines (uses send_conversation; multiple recipients are a preview + confirmation call) 3. Get detailed analytics for a specific assignment (uses get_assignment_analytics) 4. Check another course

If the user selects option 1, use the send_conversation MCP tool to message the identified students directly through Canvas.

MCP Tools Used

ToolPurpose
list_coursesDiscover active courses
list_assignmentsFind recent and upcoming assignments
get_assignment_analyticsSubmission rates and score statistics
list_submissionsPer-student submission records
get_student_analyticsDetailed per-student performance data
send_conversationMessage students through Canvas inbox

Example

User: "Morning check for CS 101"

Agent: Runs the workflow above, outputs the status report.

User: "Send a reminder to students missing Quiz 3"

Agent: Calls send_conversation to message the identified students with a reminder.

Notes

  • When anonymization is enabled, maintain a local mapping of anonymous IDs so follow-up actions (messaging, grading) still target the correct students.
  • This skill works best as a weekly routine -- Monday mornings are ideal.
  • Pairs well with the canvas-week-plan skill for student-facing planning.

Verwandte Aufgaben

aus demselben Repository

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