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Openai Prompt Engineer

Checked
jamesrochabrun·vlatest·ai-ml·MIT

Crafts optimized OpenAI prompts to maximize model output quality, accuracy, and desired creative styles.

Repository

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Showing Claude Code. One command installs this skill into any of the agents below.

  1. 1

    Run this in your project

    terminal
    $ npx skills add jamesrochabrun/skills --skill openai-prompt-engineer -a claude-code

  2. Uses the open-source skills CLI and needs Node.js. Add -g to install it for your user instead of this project.

What we know about this skill

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jamesrochabrun

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Live repository

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Automated safety checks

scanned

This skill passed all 6 checks. We read its files at one commit and looked for the things that make a skill dangerous to run — not for whether it works.

  • Declares what it does: passed

    SKILL.md parses and declares a name and a description.

    SKILL.md exists, its frontmatter parses, and it declares a name and a description.

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    Makes no network calls.

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    Scanned jamesrochabrun/skills at 2482c17637.

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Commit
2482c17637
Manifest
skills/openai-prompt-engineer/SKILL.md
Scanned
5 files, 3,575 lines
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About this skill

The openai-prompt-engineer skill provides a specialized interface for crafting, testing, and optimizing prompts specifically tailored for OpenAI models. It streamlines the workflow of refining instructions to achieve higher accuracy, creativity, and adherence to specific constraints in AI responses.

When to use it

  • Iterating on complex reasoning tasks where standard prompts yield inconsistent results.
  • Generating code snippets or technical documentation that requires strict formatting rules.
  • Creating role-play scenarios or creative writing pieces with defined stylistic guidelines.
  • Debugging ambiguous instructions by systematically testing variations of the same core request.

Key capabilities

  • Advanced prompt structuring for OpenAI architecture.
  • Automated refinement loops to improve output quality.
  • Constraint enforcement mechanisms for specific data formats.
  • Context-aware instruction tuning based on model behavior.

Example prompts

  • "Refine this prompt to ensure the AI outputs only JSON without any markdown formatting: [insert prompt]"
  • "Generate three variations of a system instruction designed to make the model act as a senior Python developer."
  • "Optimize the following prompt for better hallucination reduction while maintaining a conversational tone: [insert prompt]"

Tips & gotchas

Ensure your base prompts are clear before applying engineering techniques, as the skill enhances existing logic rather than inventing it from scratch. Limitations may apply to non-OpenAI models; verify compatibility if integrating with other LLM providers.