Autonomous-Agents

🥈Silver

Autonomous Agents skill provides access to the latest research papers on LLM-based agents. It benefits operations teams looking to implement AI-driven automation. The skill connects to workflows requiring agentic AI for task automation and decision-making.

1,155830Updated Today

Intermediate30min to implementautomation

Saves ~100 min per use

Quick InstallView Source

git clone https://github.com/tmgthb/Autonomous-Agents.git

Works with:

Claude

Overview

About This Skill

http://github.com/tmgthb/Autonomous-Agents

Use Cases

Stay updated with the latest research papers on autonomous agents and LLMs to inform your projects.

Utilize the aggregated research to enhance your understanding of AI methodologies and frameworks.

Explore innovative approaches to developing AI agents based on the latest findings in the field.

Incorporate insights from research papers into your own AI projects to improve performance and efficiency.

Setup & Installation

Quick Install

No install command available. Check the GitHub repository for manual installation instructions.

Alternative Install (Git Clone)

git clone https://github.com/tmgthb/Autonomous-Agents

Requirements

Claude Code or compatible AI agent
Works with: Claude

Quick Start Guide

Install the Skill

Copy the install command above and run it in your terminal.

Open Your AI Agent

Launch Claude Code, Cursor, or your preferred AI coding agent.

Try It Out

Use the prompt template or examples below to test the skill.

Customize

Adapt the skill to your specific use case and workflow.

Usage Examples

Prompt Template

Can you summarize the latest research papers on autonomous agents in [INDUSTRY]? Please provide insights on [DATA] and key findings that could impact [COMPANY].

Example Output

### Latest Research on Autonomous Agents

#### Key Findings:
- **Paper Title:** Advances in Autonomous Decision-Making
  - **Authors:** Smith et al. (2023)
  - **Summary:** This paper discusses novel algorithms that enhance decision-making capabilities in autonomous agents, showing a 30% improvement in efficiency compared to previous models.

- **Paper Title:** Ethical Considerations in LLM Deployment
  - **Authors:** Johnson & Lee (2023)
  - **Summary:** The authors explore the ethical implications of deploying LLMs in sensitive environments, emphasizing the need for robust oversight mechanisms.

### Implications for [COMPANY]:
- The advancements in decision-making algorithms could significantly reduce operational costs and improve service delivery in [INDUSTRY].
- Addressing ethical concerns proactively can enhance [COMPANY]'s reputation and compliance with industry regulations.