Frodex

Frodex

Beta
EnglishPortuguês (BR)
Foundations
1Introduction2Tokens3Controlling the Model
Communicating with LLMs
4Anatomy of a Good Prompt5System Prompts and Personas6Few-Shot Learning
Structured Outputs
7JSON Mode and Structured Output8Function Calling
Advanced Techniques
9Chain of Thought Reasoning10Managing the Context Window11Embeddings and Semantic Search
Production Systems
12Retrieval-Augmented Generation (RAG)13Streaming Responses14Evaluation and Cost Optimization
Frodex

Frodex

Beta
EnglishPortuguês (BR)
Foundations
1Introduction2Tokens3Controlling the Model
Communicating with LLMs
4Anatomy of a Good Prompt5System Prompts and Personas6Few-Shot Learning
Structured Outputs
7JSON Mode and Structured Output8Function Calling
Advanced Techniques
9Chain of Thought Reasoning10Managing the Context Window11Embeddings and Semantic Search
Production Systems
12Retrieval-Augmented Generation (RAG)13Streaming Responses14Evaluation and Cost Optimization
Communicating with LLMs
18 minLesson 4 of 14

Anatomy of a Good Prompt

Learn the components of effective prompts for real LLM-powered products

Learning goals

  • •Understand the CRISPE framework for structuring prompts
  • •Learn best practices for clarity and specificity
  • •Know how to use delimiters and formatting effectively

The CRISPE Framework

A strong prompt often includes these elements:

C - Context Background information the model needs to understand the task.

R - Role Who the model should act as (expert, assistant, character).

I - Instructions Clear, specific directions for what to do.

S - Specifics Details about format, length, style, or constraints.

P - Persona Tone and voice characteristics for the response.

E - Examples Sample inputs and outputs to demonstrate expectations.

Prompt Structure Best Practices

Be Specific, Not Vague ❌ "Write something about dogs" ✅ "Write a 100-word informative paragraph about Golden Retrievers' temperament for first-time dog owners"

Use Clear Delimiters Separate different parts of your prompt with clear markers:

Context: [Your context here]
---
Task: [Your task here]
---
Format: [Expected output format]

Order Matters Put the most important information at the beginning and end of prompts. Information in the middle may receive less attention (the "lost in the middle" problem).

Be Explicit About Format If you want a list, say "as a numbered list." If you want JSON, specify the schema.

Common mistakes

×Being too vague—'write something good' gives the model no direction
×Overloading with instructions—too many competing requirements confuse the model
×Assuming context—the model doesn't know your previous thoughts or projects
×Forgetting format requirements—if you need structured output, specify it explicitly

Key takeaways

+Structure prompts with context, role, instructions, specifics, and examples
+Be specific about format, length, tone, and audience
+Use delimiters to clearly separate different parts of complex prompts
+Put critical information at the beginning and end, not the middle

Playground

Try These Experiments

Prompt

Why This Experiment?

Glance at these tiny prompts to feel the difference between vague and well-structured instructions.

Response
No response yet
Choose an experiment above or type your own prompt, then click Run to see the model's response here.

So short that the model has no idea what you care about—design, errors, performance, security—so the answer will be generic.