(Office) CO-STAR Framework in Prompt Engineering

In a training session last Friday, I introduced the CO-STAR framework to our KTP team as a method to enhance prompt creation for LLMs and to capitalize on AI technology.

I began by asking the team to write prompts as they normally would—typically just a sentence or two.

Then,

I explained the CO-STAR framework and its significance in crafting prompts that produce focused, specific, and customized outputs.

The CO-STAR framework is a powerful tool for creating effective prompts for language models (LLMs). It enhances focus, specificity, and customization, ensuring that outputs align with the user’s goals.

CO-STAR stands for:

✅ Context: Provides background and relevant details.

✅ Output/Objective: Defines the desired result, such as text or a list.

✅ Specificity/Style: Clarifies the nature and tone of the output, avoiding ambiguity.

✅ Task/Tone: Outlines the action required and the mood of the response.

✅ Assumptions/Audience: Addresses unstated expectations and tailors the response to the intended audience.

✅ Requirements/Response: Specifies non-negotiable elements like length or keywords.

Applying the CO-STAR framework, the team learned to set the scene, define clear objectives, specify style and tone, consider the audience, and outline specific requirements.

A practical example from Friday’s training:

✅ C (Context): You’re auditing a construction company for the first time.

✅ O (Objective): Provide clear, step-by-step guidance.

✅ S (Style): Simple, professional language with actionable advice.

✅ T (Tone/Task): Professional, supportive, and encouraging.

✅ A (Audience/Assumption): Fresh graduates and new auditors at KTP.

✅ R (Response/Result): Confidence in executing a thorough audit.

Watch our 20-minute CO-STAR framework training on KTP's YouTube channel here: https://youtu.be/MMYEGDY-L1Q

PS : Authored by Mr Koh Teck Peng in his personal LinkedIn post https://bit.ly/46PpRSf

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