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Prompt Engineering

Prompt engineering is the practice of designing and optimizing prompts to effectively guide large language models (LLMs) and generative AI systems. It improves AI responses by using clear instructions, relevant context, examples, and constraints to achieve accurate and reliable outputs.

Here are 15,447 public repositories matching this topic...

system_prompts_leaks

Extracted system prompts from Anthropic - Claude Fable 5, Opus 5, Claude Design, Claude Code. OpenAI - ChatGPT GPT-5.6-Sol, Codex. Google - Gemini 3.5 Flash, 3.1 Pro, Antigravity. xAI - Grok, Cursor, Copilot, VS Code, Perplexity, and more. Updated regularly.

  • Updated Aug 7, 2026
  • JavaScript
langfuse

🪢 Open source AI engineering platform: LLM evals, observability, metrics, prompt management, playground, datasets. Integrates with OpenTelemetry, LangChain, OpenAI SDK, LiteLLM, and more. 🍊YC W23

  • Updated Aug 8, 2026
  • TypeScript
mlflow

The open source AI engineering platform for agents, LLMs, and ML models. MLflow enables teams of all sizes to debug, evaluate, monitor, and optimize production-quality AI applications while controlling costs and managing access to models and data.

  • Updated Aug 8, 2026
  • Python

345 Claude Code skills & agent skills & plugins (30+ Agents, 70+ custom commands, 330+ skills, customizable references, scripts)for Claude Code, Codex, Gemini CLI, Cursor, and 8 more coding agents — engineering, marketing, product, compliance, C-level advisory, research, business operations, commercial & finance, and your daily productivity skills.

  • Updated Aug 5, 2026
  • Python

Test your prompts, agents, and RAGs. Red teaming/pentesting/vulnerability scanning for AI. Compare performance of GPT, Claude, Gemini, DeepSeek, and more. Simple declarative configs with command line and CI/CD integration. Used by OpenAI and Anthropic.

  • Updated Aug 8, 2026
  • TypeScript