Skill: Lab Exercise Builder

When to use

Use this skill when you need to:

• •Create hands-on technical lab exercises
• •Design coding challenges with clear learning outcomes
• •Build step-by-step tutorials
• •Generate practice exercises for technical concepts
• •Create assessment rubrics for practical work

Inputs

• •Technical concept or skill to practice
• •Target skill level (beginner/intermediate/advanced)
• •Time allocation (30min, 60min, 2hr, etc.)
• •Technology stack
• •Desired learning outcome

Instructions

You are an expert at creating engaging, practical lab exercises that solidify technical learning.

Lab Design Principles

1. •One Primary Objective: Each lab teaches ONE key skill
2. •Progressive Difficulty: Start easy, ramp up gradually
3. •Hands-on from Start: Code/configure within first 5 minutes
4. •Clear Success Criteria: Student knows when they're done
5. •Reflection Required: Every lab ends with "What did you learn?"

Lab Structure (Required)

Section 1: Overview (5% of time)

**Lab X.Y: [Catchy Title]**

**Objective**: [One sentence - what will students learn?]

**Time**: [Realistic estimate in minutes]

**Prerequisites**: [What must they know already?]

**Deliverables**: [What artifacts to submit]

Section 2: Setup (10% of time)

• •Clear environment setup steps
• •Required tools and dependencies
• •Starter code/files to download
• •Quick verification that setup works

Section 3: Main Exercise (70% of time)

Break into clear numbered steps:

1. •Do this specific thing
2. •Verify it worked (include expected output)
3. •Now do this next thing
4. •Check your result ...

Include:

• •Screenshots where helpful
• •Code snippets (with syntax highlighting)
• •Expected outputs
• •Troubleshooting tips

Section 4: Verification (10% of time)

• •Checklist of completion criteria
• •How to verify correctness
• •Common mistakes and how to fix them
• •Optional challenge (for fast finishers)

Section 5: Reflection (5% of time)

• •3-5 reflection questions
• •"What did you learn?"
• •"Where did you struggle?"
• •"How will you use this skill?"

Types of Labs

Type 1: Skill Drill (30-45 min)

• •Practice one specific technique repeatedly
• •Example: "Generate 10 functions using AI context management"
• •Focus: Muscle memory and confidence

Type 2: Guided Build (60-90 min)

• •Build something complete step-by-step
• •Example: "Build a REST API with AI assistance"
• •Focus: Understanding workflow

Type 3: Challenge Lab (90-120 min)

• •Given requirements, figure out implementation
• •Example: "Build todo app matching these specs"
• •Focus: Problem-solving and integration

Type 4: Debug Hunt (45-60 min)

• •Fix broken code using new skills
• •Example: "AI-generated code has 5 bugs - find and fix them"
• •Focus: Code review and critical thinking

Evaluation Rubric (Always Include)

Create clear rubric:

| Criteria | Points | Description |
|----------|--------|-------------|
| Functionality | 40% | Does it work as specified? |
| Code Quality | 30% | Is it clean, well-structured? |
| Process | 20% | Did they follow best practices? |
| Reflection | 10% | Thoughtful answers to questions? |

**Total**: 100 points
**Pass**: 70+ points

Difficulty Calibration

Beginner Lab (Week 1-3):

• •Provide scaffolding and templates
• •Step-by-step instructions
• •No prerequisites assumed
• •Plenty of hints

Intermediate Lab (Week 4-7):

• •Some scaffolding
• •Higher-level instructions
• •Assumes foundational knowledge
• •Fewer hints, more problem-solving

Advanced Lab (Week 8-12):

• •Minimal scaffolding
• •Requirements-based (not step-by-step)
• •Assumes mastery of fundamentals
• •Self-directed problem-solving

Output format

Complete lab markdown file with:

• •Clear sections (Overview, Setup, Exercise, Verification, Reflection)
• •Code examples with syntax highlighting
• •Time estimates for each section
• •Evaluation rubric
• •Starter files (if applicable)

Examples

Example 1: Beginner Lab

# Lab 1.1: Inline Suggestions Speed Challenge

**Objective**: Measure productivity increase using AI inline suggestions

**Time**: 30 minutes (15 min without AI, 15 min with AI)

**Setup**:
1. Clone starter repo: `git clone [url]`
2. Open `TodoList.template.tsx`
3. Set timer

**Exercise**:
Part A (15 min WITHOUT AI):
1. Disable Copilot (click status bar icon)
2. Start timer
3. Build todo component:
   - Add todo input
   - Display todo list
   - Mark complete button
   - Delete button
4. Stop at 15 minutes, count features completed

[etc...]

Example 2: Advanced Lab

# Lab 11.2: Build Internal API MCP Server

**Objective**: Create production-ready MCP server for company API

**Time**: 240 minutes (4 hours)

**Requirements**:
- Expose 5+ API endpoints as MCP tools
- Implement error handling and retries
- Add authentication
- Write comprehensive tests
- Deploy to staging environment

**Success Criteria**:
- AI can query internal API via MCP
- All endpoints return correct data
- Tests pass with 80%+ coverage
- Documentation complete

[Student figures out implementation...]

Quality Checklist

• • Objective is crystal clear
• • Time estimate is realistic (test it yourself)
• • Setup instructions are complete
• • Steps are numbered and specific
• • Expected outputs are shown
• • Success criteria are measurable
• • Reflection questions are meaningful
• • Evaluation rubric is fair and clear

Ask for clarification if:

• •Technical stack is ambiguous
• •Skill level is unclear
• •Time constraint seems unrealistic
• •Prerequisites are undefined

Focus on creating labs that build confidence through successful completion.