AI-research-SKILLs
🥇GoldThe AI-research-SKILLs library offers a comprehensive collection of open-source AI research and engineering skills, empowering AI models with enhanced capabilities. Developed by Orchestra Research, it serves as a powerful resource for building advanced AI agents.
3,8641320Updated Today
Advanced15 minutes to implementai-agents
Saves ~180 min per use
Quick InstallView Source
claude install zechenzhangAGI/AI-research-SKILLsWorks with:
ClaudeChatGPTGitHub Copilot
Overview
About This Skill
https://www.orchestra-research.com/perspectives/ai-research-skills
Use Cases
Enhance the capabilities of existing AI models by integrating advanced research skills.
Develop custom AI research agents that can autonomously conduct experiments.
Integrate AI skills into applications to provide enhanced functionalities and user experiences.
Facilitate collaboration among AI researchers by sharing and utilizing a common set of skills.
Best For
GrowthRevOps
Tags
Setup & Installation
Quick Install
Terminal
claude install zechenzhangAGI/AI-research-SKILLsAlternative Install (Git Clone)
git clone https://github.com/zechenzhangAGI/AI-research-SKILLsRequirements
- Claude Code or compatible AI agent
- Works with: Claude, ChatGPT, GitHub Copilot
- Advanced skill - requires experience with AI agents
Quick Start Guide
1
Install the Skill
Copy the install command above and run it in your terminal.
2
Open Your AI Agent
Launch Claude Code, Cursor, or your preferred AI coding agent.
3
Try It Out
Use the prompt template or examples below to test the skill.
4
Customize
Adapt the skill to your specific use case and workflow.
Usage Examples
Prompt Template
Please provide a summary of the latest advancements in [INDUSTRY] AI research, focusing on [DATA] and its implications for [COMPANY].
Example Output
### Latest Advancements in AI Research In the field of healthcare, significant advancements have been made in AI algorithms that predict patient outcomes. For example, a recent study by XYZ University demonstrated that machine learning models can accurately forecast hospital readmission rates with an 85% success rate. #### Key Findings: - **Predictive Analytics:** Algorithms utilizing patient history and demographic data are now more effective. - **Real-World Application:** Hospitals implementing these AI systems have reported a 20% decrease in readmission rates, improving patient care and reducing costs. This research indicates that further integration of AI in healthcare could revolutionize patient management and operational efficiency.
