Engineer AI prompts using a 5-phase process with adversarial testing.
npx skills add https://github.com/m16khb/agent-harness --skill karpathy-m16khb
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
Karpathy Skill solves the challenge of crafting effective prompts for AI systems, ensuring precise, accurate, and optimized outputs through systematic prompt design and testing.
Optimize a prompt for the 'code-review' task by running Karpathy Skill with the input 'Here is the code, please review and suggest improvements'.
High-intent search queries and answers about installing and using this skill.
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.
Testing prompts against adversarial inputs involves structured adversarial testing procedures to ensure your prompts withstand malicious manipulation and remain secure for AI systems.
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.
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.
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.
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marinvchAnalyze MiniMax M2.1 interleaved thinking traces to diagnose agent failures and generate prompt improvements.
