karpathy

Name: karpathy
Availability: InStock
Author: m16khb

Engineer AI prompts using a 5-phase process with adversarial testing.

1|Updated Jun 4, 2026

Search Tags:#prompt engineering #prompt design #AI optimization #AI debugging #prompt testing

Ready to run

npx skills add https://github.com/m16khb/agent-harness --skill karpathy-m16khb

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: karpathy
Source: https://github.com/m16khb/agent-harness/tree/main/skills/karpathy
Command: npx skills add https://github.com/m16khb/agent-harness --skill karpathy-m16khb

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes scripts (resource) and references (resource) components.

What problem does it solve?

Karpathy Skill solves the challenge of crafting effective prompts for AI systems, ensuring precise, accurate, and optimized outputs through systematic prompt design and testing.

Core Features & Use Cases

Prompt Engineering: Design, test, and refine prompts for AI systems to produce desired outputs.
Systematic Approach: Utilizes a 5-phase method for prompt development: Specify, Draft, Test, Diagnose, Refine.
Adversarial Testing: Ensures prompts withstand adversarial inputs and are secure against malicious manipulation.
Integration with IssueOps: Seamless integration with IssueOps to optimize prompts for IssueOps skills and workflows.

Quick Start

Optimize a prompt for the 'code-review' task by running Karpathy Skill with the input 'Here is the code, please review and suggest improvements'.

Frequently Asked Questions about karpathy

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

FAQPage Schema

What is the best way to optimize prompt design for AI systems?▼

Optimizing prompt design for AI systems requires a structured 5-phase method: Specify, Draft, Test, Diagnose, and Refine to ensure accurate and reliable AI responses.

How do I test prompts against adversarial inputs?▼

Testing prompts against adversarial inputs involves structured adversarial testing procedures to ensure your prompts withstand malicious manipulation and remain secure for AI systems.

Why does my prompt engineering process fail to produce accurate AI responses?▼

Prompt engineering fails to produce accurate AI responses when it lacks a systematic diagnosis phase to identify flaws and a refinement phase to iteratively improve prompt reliability.

Can I integrate prompt testing with IssueOps workflows?▼

Yes, you can integrate prompt testing with IssueOps workflows to optimize prompts specifically for IssueOps skills and ensure seamless AI system operations within those environments.

Do I need to follow a specific methodology for AI debugging and prompt testing?▼

Yes, effective AI debugging and prompt testing requires following a structured 5-phase process to systematically diagnose prompt issues and refine AI outputs for robustness.