ms-agent

🥇Gold

MS-Agent is a lightweight framework that enables autonomous exploration for agents in complex task scenarios. It benefits operations teams by automating research, code generation, and chatbot interactions. The framework connects to Python-based workflows and supports agents like Claude.

4,0024470Updated Today

Intermediate30min to implementautomation

Saves ~180 min per use

Quick InstallView Source

git clone https://github.com/modelscope/ms-agent.git

Works with:

Claude

Overview

About This Skill

https://ms-agent-en.readthedocs.io

Use Cases

Automate code generation tasks for software development projects.

Facilitate data analysis by enabling agents to autonomously gather and process information.

Implement multi-agent systems for collaborative problem-solving in complex scenarios.

Utilize memory features to build agents that can retain context and improve decision-making over time.

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/modelscope/ms-agent

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

Using MS-Agent, create a plan for [COMPANY] in the [INDUSTRY] to automate [DATA]. Include specific steps and expected outcomes.

Example Output

### Automation Plan for XYZ Corp in the Manufacturing Industry

**Objective:** Automate the inventory management process.

**Steps to Implement:**
- **Assess Current Workflow:** Review the existing inventory management system to identify bottlenecks.
- **Integrate MS-Agent:** Deploy MS-Agent to monitor stock levels and predict reordering needs based on historical data.
- **Set Up Alerts:** Configure the system to send alerts when stock levels fall below a certain threshold.
- **Evaluate Performance:** After one month, analyze the efficiency improvements in inventory turnover rates.

**Expected Outcomes:**
- Reduced manual intervention by 70%.
- Improved stock accuracy by 90%.
- Increased overall operational efficiency.