Delegation Validator

Delegation Validator

Validates lesson plans to ensure complete coverage of Delegation competency from the AI Fluency Framework.

When to Use This Skill

Use this skill when:

• Educator created a lesson plan about AI planning/​Delegation
• Need objective validation of 3 subcategories coverage
• Want specific, actionable feedback on gaps
• Preparing for pilot test with students
• Want to self-assess before using delegation-coach agent

How It Works

Input

Lesson plan text (markdown, PDF, or plain text)

Output

1. Score (0-10) for each subcategory:
   • Problem Awareness (0-10)
   • Platform Awareness (0-10)
   • Task Delegation (0-10)
2. Overall Delegation Score (average)
3. Gap Analysis (what's missing)
4. Actionable Recommendations (specific improvements)

Process

1. Read lesson plan file or text
2. Execute validation script: python scripts/​validate_plan.py --input <file>
3. Script analyzes against criteria from references/​delegation_criteria.md
4. Return structured report with scores and recommendations

Validation Criteria

Problem Awareness (0-10)

• 0-3: No mention of defining objectives before using AI
• 4-6: Mentions objectives but doesn't teach students to question IF they should use AI
• 7-9: Teaches when to use AI vs when not to
• 10: Includes exercises for identifying appropriate AI interaction modes (Automation/​Augmentation/​Agency)

Platform Awareness (0-10)

• 0-3: Assumes one AI tool (usually ChatGPT)
• 4-6: Mentions multiple tools but doesn't compare
• 7-9: Teaches comparison of capabilities AND limitations
• 10: Includes ethical/​privacy considerations in tool selection

Task Delegation (0-10)

• 0-3: No guidance on dividing work
• 4-6: Generic advice on "use AI for X"
• 7-9: Specific strategies for human-AI collaboration
• 10: Includes examples of good vs bad delegation + justifications

Example Usage

Via Script (Claude Code)

# Validate lesson plan
python scripts/​validate_plan.py --input lesson_plan.md --format json

# Output:
{
  "scores": {
    "problem_awareness": 8,
    "platform_awareness": 6,
    "task_delegation": 9,
    "overall": 7.7
  },
  "gaps": [
    "Platform Awareness: Lesson doesn't teach students to compare tool limitations"
  ],
  "recommendations": [
    "Add exercise: Students compare ChatGPT vs Claude vs Copilot for same task",
    "Include discussion on privacy considerations when choosing AI tools"
  ]
}

Via Skill (Claude.ai or Code)

"Use delegation-validator to analyze this lesson plan: [paste plan text]"

Integration with delegation-coach Agent

The delegation-coach agent invokes this skill when:

• Educator shares a written lesson plan
• Coach wants objective validation to supplement Socratic questioning
• Coach needs concrete data to guide deeper questions

Workflow:

1. Coach asks: "Can you share your written lesson plan?"
2. Educator provides file/​text
3. Coach runs: python scripts/​validate_plan.py --input plan.md
4. Coach uses score to guide Socratic questions:
   • "Your Platform Awareness scored 6/​10. What do you think might be missing?"
   • "You scored 9/​10 on Task Delegation - excellent! What made that part strong?"
   • "The validator suggests adding X. Does that align with your teaching goals?"

Analogies

This Skill = Recipe for Quality Control

• Clear rubric (ingredients)
• Objective scoring steps
• Same input = same output (deterministic)
• Anyone can use to validate

delegation-coach Agent = Master Teacher Using Recipe

• Uses validation scores to guide teaching
• Adapts questions based on results
• Combines objective data with subjective coaching

Together = Restaurant with Quality Standards

• Recipe ensures consistency (skill validation)
• Chef uses standards to improve dishes (coach uses scores to guide)

References

For detailed criteria and examples:

• references/​delegation_criteria.md - Complete rubric with examples
• references/​example_plans.md - Annotated lesson plans (good vs weak)

Both files available on-demand when you need more detail.

Portability

✅ Works in Claude.ai (browser - paste lesson text) ✅ Works in Claude Code (CLI - file or text) ✅ Works via Claude API (integrations) ✅ Can be shared with other educators via plugin

Token Efficiency

• Skill body: ~1.5k tokens
• References loaded only when needed
• Script executes without loading into context
• Optimal for repeated use