agentic-workflows

🥈Silver

Agentic workflows streamline AI-assisted coding by integrating Claude Code features. Developers benefit from rapid, context-aware coding with guardrails. Connects to Claude Code, Cursor, and Windsurf for efficient workflows.

5580Updated 1w ago

Intermediate30min to implementautomation

Saves ~100 min per use

Quick InstallView Source

git clone https://github.com/pwnk77/agentic-workflows.git

Works with:

Claude

Overview

About This Skill

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/pwnk77/agentic-workflows

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

Create an agentic workflow for [COMPANY] in the [INDUSTRY] sector. The workflow should automate [TASK] using [TOOLS]. Ensure the workflow includes error handling, progress tracking, and integration with [DATA] sources. Provide a step-by-step guide and any necessary code snippets.

Example Output

# Agentic Workflow for Data Processing at TechCorp

## Overview
This workflow automates data processing for TechCorp, a tech company in the software industry. The workflow uses Python, Claude Code, and Cursor to streamline the data cleaning and analysis process.

## Workflow Steps
1. **Data Ingestion**: Automatically fetch data from [DATA SOURCE] using a Python script.
2. **Data Cleaning**: Use Claude Code to identify and clean data inconsistencies.
3. **Data Analysis**: Perform initial analysis using predefined Python scripts.
4. **Error Handling**: Implement error handling to manage data inconsistencies.
5. **Progress Tracking**: Use Cursor to track the progress of each step.

## Code Snippets
```python
# Example code snippet for data ingestion
import pandas as pd
data = pd.read_csv('[DATA SOURCE]')
```

## Expected Output
- Cleaned and analyzed data ready for further processing.
- Detailed logs of each step for troubleshooting.
- Automated alerts for any errors or inconsistencies.