# Awesome Prompt Engineering — Papers, Tools & Courses

> Hand-curated collection of 60+ papers, 50+ tools, benchmarks, and courses for prompt engineering and context engineering. Covers CoT, RAG, agents, security, and multimodal. Apache 2.0.

## Install

Paste the prompt below into your AI tool:

## Quick Use

1. Browse the collection: [github.com/promptslab/Awesome-Prompt-Engineering](https://github.com/promptslab/Awesome-Prompt-Engineering)
2. Start with survey papers for a broad overview
3. Explore specific topics: reasoning, RAG, agents, security
4. Try the listed tools for your prompt workflow

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## Intro

Awesome Prompt Engineering is a hand-curated collection of 60+ research papers, 50+ tools, benchmarks, courses, and community resources for prompt engineering and context engineering, with 5,700+ GitHub stars and Apache 2.0 license. It covers the full spectrum from chain-of-thought reasoning and automatic prompt optimization to adversarial prompting, multimodal generation, and AI agent architectures. Unlike tutorial-style guides, this is a research-oriented resource that tracks the cutting edge of how we interact with and control LLMs.

Best for: researchers and advanced practitioners who want to stay current with prompt engineering research and tools.
Covers: papers, tools, APIs, benchmarks, courses, communities.
License: Apache 2.0.

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## Awesome Prompt Engineering — Resource Categories

### Research Papers (60+)

| Category | Topics |
|----------|--------|
| **Surveys** | Comprehensive reviews of prompt engineering |
| **Optimization** | Automatic prompt tuning, DSPy, soft prompts |
| **Reasoning** | Chain-of-thought, tree-of-thoughts, self-consistency |
| **Compression** | Reducing prompt length while preserving quality |
| **Agents** | ReAct, tool use, multi-agent orchestration |
| **Multimodal** | Text-to-image, text-to-audio, vision prompting |
| **Security** | Prompt injection, jailbreaks, defense techniques |

### Tools (50+)

| Category | Examples |
|----------|---------|
| **Prompt Management** | Promptfoo, Braintrust, Helicone |
| **Evaluation** | DeepEval, Ragas, Phoenix |
| **Agent Frameworks** | LangChain, CrewAI, AutoGen |
| **Optimization** | DSPy, TextGrad, OPRO |
| **Testing** | Garak, Promptfoo red-team |

### Benchmarks & Datasets
- Standard evaluation benchmarks for LLM capabilities
- Prompt robustness datasets
- Domain-specific test suites

### Courses & Tutorials
- University courses on prompt engineering
- Industry training programs
- Hands-on workshops and notebooks

### FAQ

**Q: What is Awesome Prompt Engineering?**
A: A research-oriented collection of 60+ papers, 50+ tools, benchmarks, and courses covering prompt engineering from fundamentals to cutting-edge research.

**Q: Is it free?**
A: Yes, Apache 2.0 license. Individual papers and tools have their own licenses.

**Q: How is this different from the Prompt Engineering Guide?**
A: The Guide is tutorial-focused (learn prompt engineering). This collection is research-focused (track cutting-edge papers, tools, and benchmarks).

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## Source & Thanks

> Maintained by [PromtsLab](https://github.com/promptslab). Licensed under Apache 2.0.
>
> [Awesome-Prompt-Engineering](https://github.com/promptslab/Awesome-Prompt-Engineering) — ⭐ 5,700+

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## 快速使用

浏览：[github.com/promptslab/Awesome-Prompt-Engineering](https://github.com/promptslab/Awesome-Prompt-Engineering)

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## 简介

手工策划的提示工程研究资源集合，60+ 论文、50+ 工具、基准测试和课程。涵盖思维链、RAG、Agent、安全、多模态。5,700+ Star，Apache 2.0。

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## 来源与感谢

> Maintained by [PromtsLab](https://github.com/promptslab). Licensed under Apache 2.0.
>
> [Awesome-Prompt-Engineering](https://github.com/promptslab/Awesome-Prompt-Engineering) — ⭐ 5,700+

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Source: https://tokrepo.com/en/workflows/1b3fa22b-1246-42e5-a6d4-f5211029f6ef
Author: Prompt Lab