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Canvas Morning Check

  • 116 installs
  • 176 repo stars
  • Updated August 4, 2026
  • vishalsachdev/canvas-mcp

Helps with ai & agent building tasks.

About

canvas-morning-check is a Claude Code skill for ai & agent building. It helps solo builders move faster with AI-assisted development.

  • canvas-morning-check
  • AI & Agent Building
  • AI-coding skill

Canvas Morning Check by the numbers

  • 116 all-time installs (skills.sh)
  • +3 installs in the week ending Jul 27, 2026 (Skillselion tracking)
  • Ranked #3,865 of 16,556 AI & Agent Building skills by installs in the Skillselion catalog
  • Data as of Aug 4, 2026 (Skillselion catalog sync)
npx skills add https://github.com/vishalsachdev/canvas-mcp --skill canvas-morning-check

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Listed on Skillselion
Installs116
repo stars176
Last updatedAugust 4, 2026
Repositoryvishalsachdev/canvas-mcp

What it does

Helps with ai & agent building tasks.

Files

SKILL.mdMarkdownGitHub ↗

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 compliance: Set ENABLE_DATA_ANONYMIZATION=true in the Canvas MCP server environment to anonymize student names in all output. When enabled, names render as Student_xxxxxxxx hashes.

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_peer_review_reminders 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

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.

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