canvas-morning-check
Educator morning course health check for Canvas LMS. Shows submission rates, struggling students, grade distribution, and upcoming deadlines. Trigger phrases include "morning check", "course status", "how are my students", or any start-of-day teaching review.
What this skill does
# 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: | 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_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 | 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.
Related in Code Review
gstack
IncludedFast headless browser for QA testing and site dogfooding. Navigate pages, interact with elements, verify state, diff before/after, take annotated screenshots, test responsive layouts, forms, uploads, dialogs, and capture bug evidence. Use when asked to open or test a site, verify a deployment, dogfood a user flow, or file a bug with screenshots. (gstack)
startup-due-diligence
IncludedLegal due diligence review for seed-stage and Series A startups (US, Delaware C-Corp focus). Supports both investor and founder perspectives. Capabilities include: (1) Interactive document review and issue spotting; (2) Document request list generation; (3) Cap table and SAFE/convertible note analysis; (4) Red flag identification with severity ratings; (5) Diligence report generation. TRIGGERS: due diligence, DD, startup investment, cap table review, Series A, seed round, investor diligence, legal review startup, SAFE analysis, convertible note, 409A, founder vesting.
interview-master
IncludedThis skill should be used when the user asks to "generate interview questions", "prepare for interview", "optimize resume", "conduct mock interview", "analyze git commits for resume", "generate resume from code", "review my resume", or mentions interview preparation, career assistance, or extracting project experience from git history. Provides comprehensive interview and career development guidance for both job seekers and interviewers.
fix-issue
IncludedFixes GitHub issues using parallel analysis agents for root cause investigation, code exploration, and regression detection. Reads issue context from gh CLI, searches codebase and memory for related patterns, generates a fix with tests, and links the resolution back to the issue via PR. Includes prevention analysis to avoid recurrence. Use when debugging errors, resolving regressions, fixing bugs, or triaging issues.
sf-apex
IncludedGenerates and reviews Salesforce Apex code with 150-point scoring. TRIGGER when: user writes, reviews, or fixes Apex classes, triggers, test classes, batch/queueable/schedulable jobs, or touches .cls/.trigger files. DO NOT TRIGGER when: LWC JavaScript (use sf-lwc), Flow XML (use sf-flow), SOQL-only queries (use sf-soql), or non-Salesforce code.
swift-development
IncludedComprehensive Swift development for building, testing, and deploying iOS/macOS applications. Use when Claude needs to: (1) Build Swift packages or Xcode projects from command line, (2) Run tests with XCTest or Swift Testing framework, (3) Manage iOS simulators with simctl, (4) Handle code signing, provisioning profiles, and app distribution, (5) Format or lint Swift code with SwiftFormat/SwiftLint, (6) Work with Swift Package Manager (SPM), (7) Implement Swift 6 concurrency patterns (async/await, actors, Sendable), (8) Create SwiftUI views with MVVM architecture, (9) Set up Core Data or SwiftData persistence, or any other Swift/iOS/macOS development tasks.