Find tools for prompt design, testing, optimization, and management for LLM applications.
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🤖 Everything you need to create an LLM Agent—tools, prompts, frameworks, and models—all in one place.
The ultimate all-in-one guide to mastering Claude Code. From setup, prompt engineering, commands, hooks, workflows, automation, and integrations, to MCP servers, tools, and the BMAD method—packed with step-by-step tutorials, real-world examples, and expert strategies to make this the global go-to repo for Claude mastery.
A curated list of awesome resources, tools, and other shiny things for LLM prompt engineering.
Langtrace 🔍 is an open-source, Open Telemetry based end-to-end observability tool for LLM applications, providing real-time tracing, evaluations and metrics for popular LLMs, LLM frameworks, vectorDBs and more.. Integrate using Typescript, Python. 🚀💻📊
A robust enterprise application sample (deployed on ACA) that leverages MCP and multiple AI agents orchestrated by Langchain.js, Llamaindex.TS and Microsoft Agent Framework.
♊ 50+ selected Gemini prompts with images, multilingual support, and instant gallery preview. Open-source prompt engineering library
| Tool | Stars | Language | License | Score |
|---|---|---|---|---|
| ai-guide | ★ 10.6k | JavaScript | — | 54 |
| yu-ai-agent | ★ 1.8k | Java | — | 44 |
| DemoGPT | ★ 1.9k | Python | MIT | 40 |
| Claude-Code-Everything-You-Need-to-Know | ★ 1.3k | Python | MIT | 51 |
| awesome-gpt-prompt-engineering | ★ 1.5k | Python | — | 39 |
| langtrace | ★ 1.2k | TypeScript | AGPL-3.0 | 38 |
| openinference | ★ 898 | Python | Apache-2.0 | 39 |
| mcp-client-cli | ★ 669 | Python | MIT | 37 |
| azure-ai-travel-agents | ★ 422 | TypeScript | MIT | 48 |
| awesome-gemini-3-prompts | ★ 440 | TypeScript | — | 38 |
The top prompt engineering tools include ai-guide, yu-ai-agent, DemoGPT. These are ranked by our composite score based on GitHub stars, community activity, and code quality.
Most tools listed here are open-source. 6 out of 10 have explicit open-source licenses, making them free to use and modify.
Consider your tech stack (language compatibility), project scale (stars indicate community trust), and specific features you need. Use the comparison table above to evaluate side by side.
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