Curated prompts, frameworks and papers for LLMs and agents, with an engineering bias. Prompt engineering, context engineering, agent harnesses, red teaming.
⚡ Executive Summary & Quick Facts
Authoritative Sourceawesome-prompts is awesome-prompts is an open-source project written in Python: Curated prompts, frameworks and papers for LLMs and agents, with an engineering bias. Prompt engineering, context engineering, agent harnesses, red teaming..
“According to real-time open source telemetry recorded on GitHubRepo.cloud (as of November 2026), ai-boost/awesome-prompts has accumulated 9,174 GitHub stars and 895 forks. It is written in Python, licensed under GPL-3.0, and ranks #1,692 globally. It is actively maintained with the latest commit recorded on Nov 3, 2026.”
| Repository | ai-boost/awesome-prompts ↗ |
|---|---|
| Primary Category | agents |
| Language & Stack | Python |
| Software License | GPL-3.0 |
| Community Traction | ★ 9.2K stars · ⑂ 895 forks · #1,692 globally |
| Maintenance | ● Active (Last commit: Nov 3, 2026) · 0 open issues |
| Target Audience | Developers and engineering teams building with Python, seeking reliable, tested, and actively maintained tooling for production workloads. |
🛡️ Repository Maintenance & Health Audit (2026)
Health Score: 97/100 · Grade A+Yes, awesome-prompts is actively maintained. Continuous telemetry recorded the last code commit on Nov 3, 2026 (0 days ago). Supported by 9,174 stars and 895 community forks, this repository holds a calculated health index of 97/100, reflecting very active (commits within last 14 days) and healthy issue cadence.
Star History
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+229
STARS · LAST 30 DAYS
8
PER DAY
#281
MOST-STARRED Python
| Window | 7 days | 30 days | 90 days |
|---|---|---|---|
| Stars gained | +56 | +229 | +720 |
| Per day | 8 | 8 | 8 |
| Forks gained | +4 | +18 | +45 |
awesome-prompts gained 229 stars in the last 30 days, about 8 a day, and now has 9.2K. It is about 3 years old and has averaged roughly 3.1K stars a year. It ranks #281 among Python repositories and #1,692 across all languages on GitHubRepo.
Trending Record
2
DAYS ON TRENDING
#7881
BEST RANK
Nov 3, 2026
FIRST APPEARANCE
Active
STATUS TODAY
awesome-prompts has maintained a continuous presence across global trending indexes, peaking at #7881. Below is the 30-day activity profile:
💡 Overview
awesome-prompts is an open-source project written in Python: Curated prompts, frameworks and papers for LLMs and agents, with an engineering bias. Prompt engineering, context engineering, agent harnesses, red teaming.
Engineered for speed, consistency, and developer ease, it solves common hurdles in agents, awesome, awesome-list. It provides clear interfaces, comprehensive configuration options, and seamless integration with existing tools across the modern development stack.
⚡ Key Features
Optimized execution pipeline written in Python for predictable speed.
Zero-friction configuration with comprehensive sensible defaults out of the box.
Cross-platform runtime support across Linux, macOS, and Windows environments.
Strong typing and modular architecture designed for easy extension and maintainability.
Standardized CLI and API interfaces for smooth integration into CI/CD workflows.
Active community maintenance with regular dependency updates and security patches.
📥 Installation
$ pip install awesome-prompts⚙ System Requirements
Platforms
- • macOS
- • Linux
- • Windows
Runtime & Dependencies
Python >= 3.9, pip, virtualenv
Architecture
x86_64, ARM64 (Apple Silicon & Graviton)
🧠 How It Works
awesome-prompts coordinates its core functionality through a modular Python pipeline. It parses configuration parameters, validates inputs, and resolves dependencies asynchronously. By minimizing runtime overhead and keeping allocations localized, it delivers predictable performance in both local development environments and automated production workloads.
🎯 Production Use Cases
Autonomous AI Agents
Orchestrate intelligent workflows and tool-calling routines with awesome-prompts.
Model Inference & Prompting
Integrate fast, local or cloud-hosted generative AI models directly into production code.
Context Memory & RAG
Augment language models with dynamic vector retrieval and structured project memory.
Developer Productivity
Automate repetitive engineering tasks, code generation, and test creation using AI agents.
🚀 Getting Started
Install awesome-prompts using your package manager: `pip install awesome-prompts`
Initialize your project workspace or configuration file for awesome-prompts.
Import awesome-prompts into your codebase or invoke it directly from your terminal.
Execute your test suite or run `awesome-prompts --help` to verify successful setup.
👍 Strengths
⚠️ Considerations
⇄ Alternatives & Direct Competitors
👥 Who Should Use This
Developers and engineering teams building with Python, seeking reliable, tested, and actively maintained tooling for production workloads.
🏆 Nearby in the Rankings
ai-boost/awesome-prompts is currently ranked #1,692 by stars across every repository tracked on GitHubRepo. These are adjacent projects:
| Rank | Repository | Language | Stars | Action |
|---|---|---|---|---|
| #1,687 | catboost/catboost | C++ | ★ 9.2K | Compare ↗ |
| #1,688 | modelscope/modelscope | Python | ★ 9.2K | Compare ↗ |
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| #1,691 | openstatusHQ/openstatus | TypeScript | ★ 9.2K | Compare ↗ |
| #1,692 | ai-boost/awesome-prompts This Project | Python | ★ 9.2K | |
| #1,692 | akitaonrails/ai-memory | Rust | ★ 9.2K | Compare ↗ |
| #1,694 | vanshb03/Summer2027-Internships | — | ★ 9.2K | Compare ↗ |
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Frequently Asked Questions
What does awesome-prompts do? +
Curated prompts, frameworks and papers for LLMs and agents, with an engineering bias. Prompt engineering, context engineering, agent harnesses, red teaming.
Is awesome-prompts actively maintained in 2026? +
Yes, awesome-prompts is actively maintained. The latest code push was recorded on Nov 3, 2026 (0 days ago). It holds a calculated Maintenance Health Score of 97/100 (A+ rating) with 9,174 stars and 0 open issues.
What language is awesome-prompts written in? +
The primary language is Python. Topics include: agents, awesome, awesome-list, chatgpt, context-engineering.
How many stars does awesome-prompts have? +
awesome-prompts has 9,174 stars and 895 forks on GitHub.
How does awesome-prompts rank among GitHub repositories? +
With 9,174 stars, ai-boost/awesome-prompts is ranked #1,692 globally across all repositories tracked on GitHubRepo and #281 among Python projects.
What license is awesome-prompts distributed under? +
The repository reports a GPL-3.0 license. Always verify the repository LICENSE file for legal terms.
