Use these research-backed techniques to maximize LLM performance and secure AI agents. Apply this skill when designing system prompts for AI products, troubleshooting low-accuracy outputs, or testing model vulnerabilities against prompt injection.
Quickly install advanced-prompting-and-adversarial-testing AI skill to your development environment via command line
Source: samarv/shanon.
Based on the research from The Prompt Report (co-authored by OpenAI, Microsoft, and Google), prompt engineering is about "artificial social intelligence"—knowing how to elicit the best performance from a model through specific structural patterns.
Few-Shot Prompting (The Highest Value Technique) Do not describe your requirements in prose; provide 3–5 concrete examples of input/output pairs.
Task Decomposition For complex logic, prevent the model from jumping to a conclusion. Force it to map the problem space first.
Use these research-backed techniques to maximize LLM performance and secure AI agents. Apply this skill when designing system prompts for AI products, troubleshooting low-accuracy outputs, or testing model vulnerabilities against prompt injection. Source: samarv/shanon.
Stable fields and commands for AI/search citations.
npx skills add https://github.com/samarv/shanon --skill advanced-prompting-and-adversarial-testingUse these research-backed techniques to maximize LLM performance and secure AI agents. Apply this skill when designing system prompts for AI products, troubleshooting low-accuracy outputs, or testing model vulnerabilities against prompt injection. Source: samarv/shanon.
Open your terminal or command line tool (Terminal, iTerm, Windows Terminal, etc.) Copy and run this command: npx skills add https://github.com/samarv/shanon --skill advanced-prompting-and-adversarial-testing Once installed, the skill will be automatically configured in your AI coding environment and ready to use in Claude Code, Cursor, or OpenClaw
https://github.com/samarv/shanon