SkillsAdd

vishalsachdev/claude-skills

canvas-feedback-template

Generate learning science-backed feedback templates for Canvas assignments.

First seen Jan 28, 2026

Installation

$ npx skills add vishalsachdev/claude-skills --skill canvas-feedback-template
View on skills.sh ↗ GitHub repository ↗

Summary

  • Generate learning science-backed feedback templates for Canvas assignments.
  • Use when educators need feedback templates for grading, want to create rubric comments, need encouraging feedback language aligned with Pillar 3 principles (targeted, encouraging, immediate), or want to set up SpeedGrader comment libraries.
  • Works with canvas-mcp for bulk grading.

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More details

Agent compatibility

Declared targets from SKILL.md / docs. Unmarked agents are not listed — the skill may still install via the CLI.

Claude Code Not declared
Cursor Not declared
Codex Not declared
GitHub Copilot Not declared
Windsurf Not declared
Gemini CLI Not declared
Cline Not declared
OpenCode Not declared

Repository health

Stars 2
License LICENSE
Default branch main
Open issues 0
Status Active

Package contents

Files included with this skill beyond the listing page.

  • skill md SKILL.md 3,469 B
  • docs SUMMARY.md 388 B

History

  1. First seen on skills.sh
  2. First recorded snapshot · 12 installs

SKILL.md

Canvas Feedback Template Generator

Generate feedback templates applying Pillar 3: Continuous Practice & Feedback.

Workflow

Step 1: Gather Context

Ask the user for:

  1. Assignment type (essay, project, quiz, discussion, peer review)
  2. Learning objectives being assessed
  3. Common issues seen in submissions (optional)
  4. Rubric criteria if available

Step 2: Generate Templates

Organize by performance level. Each template must include these components (per Principle 3.2.1):

  1. Strength acknowledgment (3.2.2 - Encouraging)
  2. Specific observation with evidence from submission
  3. Actionable improvement with concrete next step
  4. Forward-looking connection to future learning

Exceeds Expectations

Celebrate mastery, suggest stretch goals.

Meets Expectations

Acknowledge success, highlight one improvement area.

Approaching Expectations

Specific improvements with encouragement.

Needs Improvement

Clear next steps with support resources.

Step 3: Apply Principles

Principle Application in Feedback
3.2.1 Targeted Focus on specific, goal-oriented actions
3.2.2 Encouraging Start with positives, maintain supportive tone
3.2.3 Immediate Design for quick delivery via SpeedGrader
3.3.2 Generating explanations Ask questions that prompt reflection
3.3.3 Reflection Include prompts for self-assessment

Step 4: Canvas Integration

If canvas-mcp is available:

  • Rubric Comments: Generate comment options for each rubric criterion at each level
  • Comment Library: Format for Canvas SpeedGrader comment library
  • Bulk Feedback: Create templates for bulkgradesubmissions

Template Examples

Essay — Meets Expectations

**What's Working Well:**
Your thesis in paragraph 1 clearly establishes your argument about [topic].

**One Area to Strengthen:**
Your conclusion summarizes but could be more impactful. Try connecting
back to your opening hook or suggesting implications.

**Next Step:**
For your next essay, experiment with a "so what?" statement in your
conclusion that explains why your argument matters.

Peer Review — Approaching Expectations

**Strengths in Your Review:**
You identified key strengths and provided specific examples.

**Area for Growth:**
Your suggestions are general ("make it clearer"). Effective peer feedback
includes specific, actionable recommendations.

**How to Improve:**
Instead of "the introduction needs work," try: "Consider opening with a
specific example of [topic] to immediately engage readers."

**Reflection Question:**
What specific change would have the biggest impact on your peer's draft?

Feedback Quality Checklist

Before finalizing:

  • Specific: References actual work, not generic statements
  • Actionable: Includes concrete next step
  • Encouraging: Leads with strengths
  • Forward-looking: Connects to future assignments
  • Proportionate: Length matches assignment weight