Awesome-Prompt-Engineering

<h2 align="center">Awesome Prompt Engineering 🧙‍♂️</h2>

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  <img width="650" src="https://raw.githubusercontent.com/promptslab/Awesome-Prompt-Engineering/main/_source/prompt.png">
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<p align="center">
  A hand-curated collection of resources for Prompt Engineering and Context Engineering — covering papers, tools, models, APIs, benchmarks, courses, and communities for working with Large Language Models.
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https://promptslab.github.io
  </p>
 <h4 align="center">
  
  ```
     Master Prompt Engineering. Join the Course at https://promptslab.github.io
  ```
  <a href="https://awesome.re"><img src="https://awesome.re/badge.svg" alt="Awesome" /></a>
  <a href="https://github.com/promptslab/Awesome-Prompt-Engineering/blob/main/LICENSE"><img src="https://img.shields.io/badge/License-Apache_2.0-blue.svg" alt="License" /></a>
  <a href="http://makeapullrequest.com"><img src="https://img.shields.io/badge/PRs-welcome-brightgreen.svg?style=flat-square" alt="PRs Welcome" /></a>
  <a href="https://discord.gg/m88xfYMbK6"><img src="https://img.shields.io/badge/Discord-Community-orange" alt="Community" /></a>
  <img src="https://img.shields.io/badge/Last%20Updated-February%202026-brightgreen" alt="Last Updated" />
</p>

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## 🚀 Start Here

New to prompt engineering? Follow this path:

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  <img width="1000" src="https://raw.githubusercontent.com/promptslab/Awesome-Prompt-Engineering/refs/heads/main/_source/main.jpg">
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1. **Learn the basics** → [ChatGPT Prompt Engineering for Developers](https://www.deeplearning.ai/short-courses/chatgpt-prompt-engineering-for-developers/) (free, ~90 min)
2. **Read the guide** → [Prompt Engineering Guide by DAIR.AI](https://www.promptingguide.ai/) (open-source, comprehensive)
3. **Study provider docs** → [OpenAI Prompt Engineering Guide](https://platform.openai.com/docs/guides/prompt-engineering) · [Anthropic Prompt Engineering Guide](https://docs.anthropic.com/en/docs/build-with-claude/prompt-engineering/overview)
4. **Understand where the field is heading** → [Anthropic: Effective Context Engineering for AI Agents](https://www.anthropic.com/engineering/effective-context-engineering-for-ai-agents)
5. **Read the research** → [The Prompt Report](https://arxiv.org/abs/2406.06608) — taxonomy of 58+ prompting techniques from 1,500+ papers

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## Table of Contents

- [Papers](#papers)
  - [Major Surveys](#major-surveys)
  - [Prompt Optimization and Automatic Prompting](#prompt-optimization-and-automatic-prompting)
  - [Prompt Compression](#prompt-compression)
  - [Reasoning Advances](#reasoning-advances)
  - [In-Context Learning](#in-context-learning)
  - [Agentic Prompting and Multi-Agent Systems](#agentic-prompting-and-multi-agent-systems)
  - [Multimodal Prompting](#multimodal-prompting)
  - [Structured Output and Format Control](#structured-output-and-format-control)
  - [Prompt Injection and Security](#prompt-injection-and-security)
  - [Applications of Prompt Engineering](#applications-of-prompt-engineering)
  - [Text-to-Image Generation](#text-to-image-generation)
  - [Text-to-Music/Audio Generation](#text-to-musicaudio-generation)
  - [Foundational Papers (Pre-2024)](#foundational-papers-pre-2024)
- [Tools and Code](#tools-and-code)
  - [Prompt Management and Testing](#prompt-management-and-testing)
  - [LLM Evaluation Tools](#llm-evaluation-tools)
  - [Agent Frameworks](#agent-frameworks)
  - [Prompt Optimization Tools](#prompt-optimization-tools)
  - [Red Teaming and Prompt Security](#red-teaming-and-prompt-security)
  - [MCP (Model Context Protocol)](#mcp-model-context-protocol)
  - [Vibe Coding and AI Coding Assistants](#vibe-coding-and-ai-coding-assistants)
    - [CLI-Based Coding Agents](#cli-based-coding-agents)
    - [AI Code Editors / IDEs](#ai-code-editors--ides)
    - [IDE Extensions / Plugins](#ide-extensions--plugins)
    - [AI Coding Platforms / Cloud Agents](#ai-coding-platforms--cloud-agents)
    - [Open-Source Coding Agent Frameworks](#open-source-coding-agent-frameworks)
  - [Other Notable Repositories](#other-notable-repositories)
- [APIs](#apis)
- [Datasets and Benchmarks](#datasets-and-benchmarks)
- [Models](#models)
- [AI Content Detectors](#ai-content-detectors)
- [Books](#books)
- [Courses](#courses)
- [Tutorials and Guides](#tutorials-and-guides)
- [Videos](#videos)
- [Communities](#communities)
- [Autonomous Research & Self-Improving Agents](#autonomous-research--self-improving-agents)
- [How to Contribute](#how-to-contribute)

---

## Papers
📄

### Major Surveys

- [The Prompt Report: A Systematic Survey of Prompting Techniques](https://arxiv.org/abs/2406.06608) [2024] — Most comprehensive survey: taxonomy of 58 text and 40 multimodal prompting techniques from 1,500+ papers. Co-authored with OpenAI, Microsoft, Google, Stanford.
- [A Systematic Survey of Prompt Engineering in Large Language Models: Techniques and Applications](https://arxiv.org/abs/2402.07927) [2024] — 44 techniques across app

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