openai-gpt5-prompting

Design, refine, and debug prompts for OpenAI GPT-5 series models.

Updated Jul 5, 2026

Search Tags:#prompt engineering #llm #openai #gpt-5 #structured output #ai prompting

Ready to run

npx skills add https://github.com/ijindal1/jaunt --skill openai-gpt5-prompting

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: openai-gpt5-prompting
Source: https://github.com/ijindal1/jaunt/tree/main/.codex/skills/openai-gpt5-prompting
Command: npx skills add https://github.com/ijindal1/jaunt --skill openai-gpt5-prompting

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes references (resource) components.

What problem does it solve?

This Skill helps users write, critique, and iterate on prompts for OpenAI's GPT-5 series models, ensuring clear instructions and desired model behaviors.

Core Features & Use Cases

Prompt Design: Develop unambiguous, testable, and robust prompts.
Behavior Tuning: Select between quick vs. deep reasoning.
Structured Outputs: Create prompts for JSON schemas and tool calls.
Debugging: Identify and fix prompt failures like hallucinations or format drift.
Use Case: You need to generate a JSON output from GPT-5 that strictly adheres to a provided schema. This skill will help you craft the system and developer messages to ensure the model outputs valid JSON without extra prose.

Quick Start

Use the openai-gpt5-prompting skill to draft a system message for a GPT-5 model that needs to act as a code reviewer.

Frequently Asked Questions about openai-gpt5-prompting

High-intent search queries and answers about installing and using this skill.

FAQPage Schema

How do I write GPT-5 prompts that strictly output valid JSON?▼

To get valid JSON from GPT-5, you need to craft precise system and developer messages that define strict schema constraints. This Skill helps design structured output prompts, ensuring the model generates JSON without extra prose or format drift.

What is the best way to debug GPT-5 prompt failures like hallucinations?▼

Debugging GPT-5 prompt failures involves identifying ambiguous instructions and refining message templates. This Skill helps analyze prompt failures like hallucinations or format drift, allowing you to iterate on requirements and fix unexpected model behaviors.

How do I control reasoning depth in GPT-5 prompt engineering?▼

Controlling reasoning depth in GPT-5 prompt engineering requires tuning behavior settings within your prompts. This Skill assists in selecting between quick and deep reasoning modes by refining your system and user messages for optimal performance.

Do I need developer messages to format tool calls in GPT-5?▼

Yes, developer messages are essential for formatting tool calls in GPT-5. This Skill leverages system, developer, and user message templates to address structured output generation, ensuring your prompts correctly instruct the model on tool usage.

Can I use this to clarify ambiguous requirements before generating OpenAI prompts?▼

Yes, you can use this Skill to clarify ambiguous requirements before generating OpenAI prompts. It addresses requirement clarification as a core task, helping you develop unambiguous, testable, and robust prompts for GPT-5 models.

What are the limitations of using system messages for GPT-5 behavior tuning?▼

System messages alone may not prevent format drift or hallucinations in GPT-5 without proper evaluation design. This Skill helps identify these limitations by debugging prompt failures and designing comprehensive evaluations to test model behaviors.