gh-greyhaven-ai-claude-code-config-grey-haven-plugins-core/skills/prompt-engineering/checklists/prompt-quality-checklist.md

Prompt Quality Checklist

Comprehensive checklist for verifying prompt quality before submission.

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Pre-Submission Checklist

Use this checklist to evaluate any prompt before sending to an LLM.

Section 1: Content Clarity (Principles 1, 2, 9, 21, 25)

Essential Elements:

• Task is specific (not "help me" or "tell me about X")

  • Clear action verb (explain, create, debug, compare, etc.)
  • Specific topic or deliverable
  • Example: ✅ "Debug this login function" vs ❌ "Help with code"

• Audience specified (who is this for?)

  • Experience level stated
  • Background/context provided
  • Example: ✅ "For junior developer" vs ❌ No audience mentioned

• Requirements explicitly stated

  • What must be included
  • What constraints apply
  • Success criteria defined
  • Example: ✅ "Must support TypeScript, < 100 lines" vs ❌ Vague requirements

• Relevant context provided

  • Technology versions
  • Environment details
  • Constraints or limitations
  • Why you need this
  • Example: ✅ "React 18 + TypeScript for production SaaS" vs ❌ "React app"

• Detail level appropriate

  • Specific enough to avoid ambiguity
  • Not so detailed it's overwhelming
  • Includes examples where helpful
  • Example: ✅ "Validate emails per RFC 5322" vs ❌ "Validate emails"

Score: ___/5

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Section 2: Structure & Organization (Principles 3, 8, 17)

Structural Elements:

• Complex tasks broken down

  • Multi-step tasks split into phases
  • Clear sequence defined
  • One focus per step
  • Example: ✅ "Step 1: Design schema, Step 2: Create API" vs ❌ "Build everything"

• Delimiters used for sections

  • ###Headers### for major sections
  • Code blocks properly fenced
  • Lists for related items
  • Clear visual separation
  • Example: ✅ Uses ###Task###, ###Requirements### vs ❌ Wall of text

• Output format specified

  • Exact structure desired (table, list, code, etc.)
  • Format template provided if applicable
  • Length/detail level indicated
  • Example: ✅ "Return as JSON with fields: name, age" vs ❌ "Give me the data"

Score: ___/3

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Section 3: Reasoning & Examples (Principles 12, 19, 20)

Thinking Guidance:

• Step-by-step requested (if applicable)

  • Uses "step-by-step" or "think through"
  • Numbered sequence for complex tasks
  • Reasoning process requested
  • Example: ✅ "Debug step-by-step: 1) Identify bug..." vs ❌ "Fix this"

• Chain-of-thought prompted (for complex problems)

  • Asks for reasoning
  • Requests explanation of approach
  • "Walk through your thinking"
  • Example: ✅ "Explain your reasoning at each step" vs ❌ Direct answer only

• Examples provided (when pattern matters)

  • 2-3 examples of desired format
  • Shows edge cases
  • Demonstrates expected style
  • Example: ✅ Shows input/output examples vs ❌ No examples

Score: ___/3

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Section 4: Style & Tone (Principles 5, 10, 11, 22, 24, 26)

Expression Quality:

• Language complexity appropriate

  • Matches audience level
  • Technical terms explained if needed
  • Simple when possible
  • Example: ✅ Adjusts vocabulary to audience vs ❌ Assumes expertise

• Affirmative directives used

  • Says what TO do, not what NOT to do
  • Positive framing
  • Clear direction
  • Example: ✅ "Use simple language" vs ❌ "Don't use complex words"

• Role assignment (if beneficial)

  • Specific expertise requested
  • Perspective defined
  • Helpful for domain tasks
  • Example: ✅ "As a security expert, review..." vs ❌ Generic request

• Natural language

  • Conversational tone
  • Not overly formal or robotic
  • Human-like phrasing
  • Example: ✅ "Explain how this works" vs ❌ "Elucidate the operational mechanics"

• Format preference stated

  • Bullets, paragraphs, tables, etc.
  • Desired length indicated
  • Style guidance provided
  • Example: ✅ "Answer in bullet points, < 200 words" vs ❌ No format specified

• Leading words used

  • Directs response style
  • Sets expectations
  • Guides detail level
  • Example: ✅ "Write a detailed analysis..." vs ❌ "Analysis"

Score: ___/6

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Section 5: Advanced Techniques (Principles 4, 6, 7, 13-15, 18, 23)

Specialized Approaches:

• Explanation requested (complex topics)

  • Asks "why" or "explain reasoning"
  • Seeks understanding, not just answer
  • Example: ✅ "Explain your technology choice" vs ❌ Just picks technology

• Unbiased approach (sensitive topics)

  • Explicitly requests objectivity
  • Asks for multiple perspectives
  • Example: ✅ "Present both sides objectively" vs ❌ Potentially biased framing

• Clarifying questions (unclear requirements)

  • Allows model to ask questions
  • Admits uncertainty
  • Example: ✅ "Ask me questions to clarify" vs ❌ Forces model to guess

• Comprehension testing (learning)

  • Includes quiz or practice
  • Tests understanding
  • Example: ✅ "Include 3 quiz questions" vs ❌ Explanation only

• Learning objectives (educational content)

  • Specific skills to gain
  • Measurable outcomes
  • Example: ✅ "Learner should be able to..." vs ❌ No objectives

• Multi-turn awareness (complex projects)

  • Acknowledges iterative process
  • Plans for refinement
  • Example: ✅ "Start with X, we'll refine later" vs ❌ Expects perfection first try

Score: ___/6

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Scoring Guide

Total Score: ___/23

Quality Levels:

20-23: Excellent Prompt ✅

• Highly likely to get quality response on first try
• All essential elements present
• Well-structured and clear
• Action: Submit confidently

15-19: Good Prompt ✅

• Likely to get useful response
• Minor improvements possible
• Core elements covered
• Action: Submit, but note areas for future improvement

10-14: Weak Prompt ⚠️

• May get partial or unclear response
• Missing important elements
• Needs significant improvement
• Action: Revise before submitting

0-9: Ineffective Prompt ❌

• Unlikely to get useful response
• Critical elements missing
• Will require multiple clarifications
• Action: Restart with template from examples/

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Quick Improvement Checklist

If your score is < 15, apply these quick fixes:

Priority 1 (Essential - Fix These First)

• Add specific task description (Principle 9)
• Include relevant context (Principle 21)
• State requirements clearly (Principle 25)

Priority 2 (Important - Significant Impact)

• Use delimiters to structure (Principle 8)
• Break down complex tasks (Principle 3)
• Specify output format (Principle 17)

Priority 3 (Helpful - Polish)

• Add examples if pattern matters (Principle 7, 20)
• Specify audience (Principle 2)
• Request step-by-step for complex tasks (Principle 12)

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Category-Specific Checklists

For Technical Prompts (Code/Debug/Architecture)

Must Have:

• Language/framework with version
• Specific functionality or problem
• Expected behavior clearly defined
• Code examples or error messages
• Test cases or success criteria

Should Have:

• Environment details (OS, dependencies)
• Coding standards to follow
• Performance requirements
• Example input/output

Impact: 85% → 95% first-response quality

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For Learning Prompts (Tutorials/Explanations)

Must Have:

• Target audience with experience level
• Learning objectives defined
• Concept to explain specified
• Desired explanation structure

Should Have:

• Examples requested
• Comprehension check included
• Progressive complexity (basic → advanced)
• Practice exercise

Impact: 70% → 90% learner success

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For Creative Prompts (Writing/Ideation)

Must Have:

• Target audience specified
• Tone/style guidelines
• Length requirements
• Purpose or use case

Should Have:

• Format preference (blog, email, etc.)
• Key points to cover
• Brand voice or examples
• Constraints or avoid-list

Impact: 60% → 85% satisfaction with output

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For Research Prompts (Analysis/Comparison)

Must Have:

• Research question specific
• Scope defined (what to include/exclude)
• Objectivity requested
• Output format (report, table, bullets)

Should Have:

• Evaluation criteria
• Use case context
• Sources or data to consider
• Decision framework

Impact: 65% → 90% actionable insights

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Common Issues Checklist

If you're not getting good responses, check:

Issue: Responses are too general

• Add more specific details (Principle 21)
• Provide context and use case (Principle 2)
• Include examples of what you want (Principle 7, 20)

Issue: Wrong format or structure

• Explicitly specify desired format (Principle 17)
• Show an example of format (Principle 7)
• Use delimiters to organize request (Principle 8)

Issue: Missing important aspects

• Break down into steps (Principle 3)
• List all requirements explicitly (Principle 25)
• Provide comprehensive context (Principle 21)

Issue: Too basic or too complex

• Specify audience level (Principle 2)
• Adjust language complexity (Principle 5)
• Provide background on current knowledge

Issue: Need multiple clarifying exchanges

• Be more direct about needs (Principle 9)
• Provide all relevant details upfront (Principle 21)
• Use structured format with sections (Principle 8)

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Final Validation

Before hitting send, ask yourself:

1. Can someone else understand what I need?

   • If you showed this prompt to a colleague, would they know what you want?
   • If NO → Add more context and specifics

2. Is this the minimum information needed?

   • Is every detail relevant?
   • Is anything missing that would change the answer?
   • If NO → Trim irrelevant info, add missing pieces

3. Is the desired output clear?

   • Would you recognize a good response if you saw it?
   • Do you know what "done" looks like?
   • If NO → Specify success criteria and format

4. Is this appropriately scoped?

   • Can this be answered in one response?
   • Or should it be broken into multiple steps?
   • If too large → Use Principle 3 to break down

5. Have I made assumptions?

   • Am I assuming the model knows my context?
   • Am I assuming technical knowledge level?
   • If YES → Make assumptions explicit

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Total Validation Checks: ___/5

If all 5 are "YES" → Ready to submit! ✅

If any are "NO" → Revise using the relevant section above

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Quick Reference:

• Excellent prompt (20+ score): Clear task, structured, specific, examples provided
• Most common fixes: Add delimiters (8), break down tasks (3), add details (21)
• Biggest impact principles: 3, 7, 8, 17, 19, 21, 25

Template Library: See ../templates/ for ready-to-use formats