Using GPT

Prompt Checklist

Checklist for reviewing Stubber AI prompts before use. Covers tone, structure, guardrails, background context, output format, and standard actions for reliable LLM workflows. To allow for easier system prompt crafting, here is a checklist of items to consider when creating prompts for LLMs.

# Tone and Style

[ ] Give instructions on the tone and style of the output (e.g., formal, casual, technical, simple)

[ ] Specify the target audience for the response (e.g., public, internal staff, experts)

[ ] Include examples of the desired tone and style if possible

# Structure and Format

[ ] Define the desired structure of the response (e.g., bullet points, numbered list, paragraphs)

[ ] Specify any formatting requirements (e.g., headings, bold text, code blocks)

[ ] Indicate the length of the response (e.g., brief summary, detailed explanation)

# Guardrails and Constraints

[ ] Set clear boundaries for the response (e.g., avoid certain topics, maintain confidentiality)

[ ] Include any legal or ethical considerations (e.g., compliance with regulations)

[ ] Specify the level of creativity allowed in the response (e.g., strictly factual, imaginative)

[ ] Tell the model to say "I don't know" if unsure about the answer

[ ] Instruct the model not to engage in any other discussion outside the scope of the job

# Context and Background

[ ] Provide relevant context or background information for the prompt

[ ] Include any necessary definitions or explanations of terms

[ ] Specify the perspective or role the model should take (e.g., customer support agent, technical expert)

# Standard Actions to add

[ ] Allow the model to escalate to a manager if unsure or if the request is beyond its capabilities, providing the escalate_to_manager action

[ ] Give the model the calculator action if numerical calculations are needed

[ ] Give the model the make_a_note action to keep track of important information during the conversation

[ ] Give the model the search_knowledge_base action to look up information in a knowledge base

[ ] Give the model the set_reminder action set to allow it to set reminders for follow-up actions