Canvas Morning Check

Start the teaching day with a prioritised briefing: what needs grading, who hasn't submitted, which deadlines are coming, and which students may need a nudge — all from a single agent session.

Prerequisites

• Canvas MCP server must be running and connected.
• You must have instructor, TA, or admin role in the target courses.
• Privacy notice: student names and submission data are visible in this output. Run this skill only in a private or educator-only session — never in a shared screen or student-facing context. Your institution's Canvas admin token policy governs what data is accessible; you are responsible for handling student information in accordance with FERPA or your local equivalent.

Steps

1. Load Active Courses

Call list_courses to retrieve your currently active courses (use enrollment_type=teacher if needed to filter to courses where you are the instructor). Alternatively, call get_dashboard_cards for a quick overview of courses with pending items.

Note each course ID, name, and enrollment count.

2. Check the Grading Queue (per course)

For each active course:

1. Call list_assignments to find assignments whose due date has passed and that accept online submissions.
2. For each such assignment, call list_submissions filtered to workflow_state=submitted (or graded=false if available) to count ungraded submissions.

Build a grading backlog table: course → assignment → ungraded count → due date.

3. Check Participation and Missing Submissions

For each course, call list_course_enrollments with type=StudentEnrollment and state=active to get the enrolled student list.

For the most recent assignment with a past due date per course, cross-reference submitted student IDs against the enrollment list to identify students with no submission. Flag those with zero submissions in the past 2 assignments as participation gaps.

4. Scan Engagement Trends

For courses flagged with participation issues or declining grades, call get_course_analytics (with the course ID) to see aggregated participation and on-time submission rates.

For individual students flagged in Step 3, call get_student_analytics (with course ID and student user ID) to confirm declining trends before including them in the action list.

5. Check Upcoming Deadlines

From the list_assignments data gathered in Step 2, surface any assignments due within the next 48 hours that have not yet been published or that have zero submissions (possibly a reminder is needed for students).

6. Present the Morning Briefing

Organise output in this order:

1. Grading queue (highest count first)
2. Upcoming deadlines needing attention
3. Students with participation gaps
4. Any urgent analytics flags

Ask the instructor if they want to drill into any item or take action (messaging students, opening a submission for review).

Output Format

Morning Check — [Instructor Name]
[Date]  |  Active courses: [n]

GRADING QUEUE
• [Course A] — [Assignment]  [n] ungraded  (due [date])
• [Course B] — [Assignment]  [n] ungraded  (due [date])

UPCOMING DEADLINES (next 48 h)
• [Course] — [Assignment]  due [datetime]  submissions so far: [n]/[total]

PARTICIPATION GAPS
• [Course] — [Student Name]  — no submission in last 2 assignments
• [Course] — [Student Name]  — grade trending down (was 82% → now 67%)

ANALYTICS FLAGS
• [Course] — on-time submission rate dropped to [n]% this week

All clear on remaining courses.

Notes

• This skill is read-only — it surfaces information but does not grade or message anyone. Use canvas-at-risk-students for the outreach step.
• For courses with large enrolments (100+ students), list_submissions may return many pages. Focus on the most recently due assignment per course to keep the briefing concise.
• get_student_analytics may be slow on large courses; call it only for students already flagged in Step 3, not for every student.
• Gradebook data reflects posted grades only. Unposted grades will not appear in analytics trends.