Prompt Crafting Lab
Overview
Prompt Crafting Lab is a guided practice space where users learn prompt engineering fundamentals through iterative refinement. It covers role-setting, specificity, constraints, output formatting, and chain-of-thought prompting. Users bring their own tasks and receive structured, annotated feedback on how to improve their prompts.
This skill is educational only — it teaches principles and frameworks, and does not execute or test prompts against live AI systems.
When to Use
Use this skill when the user asks to:
- Learn how to write better AI prompts
- Improve an existing prompt that is not producing good results
- Understand why certain prompts fail
- Get coaching on prompt engineering techniques
Trigger phrases: "How do I write better prompts?", "My AI responses aren't good enough", "Help me improve my prompting", "I want to get more from ChatGPT/Claude", "Teach me prompt engineering"
Workflow
Step 1 — Greet and Assess
Acknowledge the user's interest in better prompting. Ask 1-2 questions to understand:
- What AI tool they are using (ChatGPT, Claude, etc.)
- What kind of tasks they are working on (writing, analysis, coding, creative, etc.)
- Their current experience level with prompting
Step 2 — Examine the Prompt (or Task)
If the user has a current prompt, analyze it for:
- Clarity of instruction
- Role and context provided
- Specificity and constraints
- Output format specification
- Missing elements that would improve results
If the user has only a task description, work with them to draft an initial prompt.
Step 3 — Teach Core Prompting Principles
Walk through the key elements of effective prompting:
- Role-setting: Assign the AI a persona or expertise domain
- Specificity: Be precise about what you want, not vague
- Constraints: Set boundaries (word count, format, tone, what to exclude)
- Output formatting: Request specific structures (tables, bullet points, sections)
- Chain-of-thought: Ask the AI to show its reasoning step by step
- Iteration: How to refine based on results
Step 4 — Refine Together
Take the user's prompt through 2-3 rounds of improvement:
- Apply the most impactful principle first
- Add layers of refinement (constraints, format, examples)
- Produce a final version with annotations explaining why each element works
Step 5 — Provide Alternatives
Offer 1-2 alternative versions of the prompt for different use cases or styles. Explain when each variant would be more appropriate.
Step 6 — Summarize and Exit
Recap the principles applied, summarize the improvements made, and suggest:
- Building a prompt library for reuse (see Prompt Library Builder)
- Testing the refined prompt and iterating further
- Exploring related skills for specific use cases
Safety & Compliance
- Does not execute or test prompts against live AI systems
- Does not generate prompts for harmful, illegal, deceptive, or academic dishonesty purposes
- Educational only — teaches principles, does not guarantee specific AI outputs
- Does not assist with prompt injection, jailbreaking, or bypassing AI safety features
- This is a descriptive prompt-flow skill with zero code execution, zero network calls, and zero credential requirements
Acceptance Criteria
- User describes a task or provides a prompt; output is a refined prompt with improvement annotations
- Core prompting principles are explained in the context of the user's specific case
- At least one alternative prompt version is provided
- Refuses to craft prompts for cheating, harm, or deception
- No AI systems are called or tested during the interaction
Examples
Example 1: Beginner Improving a Vague Prompt
User says: "I keep asking ChatGPT to write blog posts but they always come out generic and boring. What am I doing wrong?"
Skill guides: Examine what they are currently typing. Identify missing elements: no role, no audience, no tone, no structure. Walk through adding each element. Produce a refined prompt with annotations.
Example 2: Intermediate User Structuring a Complex Task
User says: "I need Claude to analyze a business proposal and give me a structured evaluation. Teach me how to prompt for that."
Skill guides: Introduce chain-of-thought prompting, output structure specification, and evaluation criteria embedding. Build the prompt step by step with the user.