---
name: Canvas Morning Check
slug: canvas-morning-check
category: Automation
description: Canvas Morning Check runs a start-of-day Canvas LMS review for educators. It summarizes submission rates, struggling students, grade patterns, and upcoming deadlines so you can follow up quickly.
github: "https://github.com/vishalsachdev/canvas-mcp/tree/main/skills/canvas-morning-check"
language: Python
stars: 226
forks: 76
install: "npx degit https://github.com/vishalsachdev/canvas-mcp/tree/main/skills/canvas-morning-check ~/.claude/skills/canvas-morning-check"
installs_to: ~/.claude/skills/canvas-morning-check
source_path: skills/canvas-morning-check/SKILL.md
collection_size: 8
category_size: 1860
collection_url: "https://dirskills.com/collections/vishalsachdev/canvas-mcp"
added: 2026-09-04T05:24:49.137Z
last_synced: 2026-09-04T05:24:49.137Z
canonical_url: "https://dirskills.com/skills/canvas-morning-check"
---

# Canvas Morning Check

Canvas Morning Check runs a start-of-day Canvas LMS review for educators. It summarizes submission rates, struggling students, grade patterns, and upcoming deadlines so you can follow up quickly.

**Install:**

```bash
npx degit https://github.com/vishalsachdev/canvas-mcp/tree/main/skills/canvas-morning-check ~/.claude/skills/canvas-morning-check
```

## README

# 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:

| Urgency | Criteria |
|---------|----------|
| **Critical** | Missing 3+ assignments in the past 2 weeks, or average grade below 60% |
| **Needs attention** | Missing 2 assignments, or average grade 60--70%, or 3+ late submissions |
| **On track** | All 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_peer_review_inbox_messages` or `send_conversation`)
> 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

| Tool | Purpose |
|------|---------|
| `list_courses` | Discover active courses |
| `list_assignments` | Find recent and upcoming assignments |
| `get_assignment_analytics` | Submission rates and score statistics |
| `list_submissions` | Per-student submission records |
| `get_student_analytics` | Detailed per-student performance data |
| `send_conversation` | Message 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.