buildforce-cli

🥈Silver

Buildforce CLI is a framework for AI-assisted engineering. It enables developers to build, test, and deploy code with AI agents. The tool integrates with Claude for coding tasks, improving efficiency and consistency in software development workflows.

3120Updated 1mo ago

Intermediate30min to implementautomation

Saves ~240 min per use

Quick InstallView Source

git clone https://github.com/berserkdisruptors/buildforce-cli.git

Works with:

Claude

Overview

About This Skill

Buildforce-cli is an innovative automation skill designed to streamline AI-assisted engineering processes. This framework provides a consistent and reliable approach to developing engineering solutions, enabling teams to leverage AI for increased efficiency. By integrating Buildforce into your workflow, you can enhance your engineering capabilities and ensure that your projects are completed with precision and speed. One of the key benefits of using Buildforce-cli is its ability to save time during the engineering process, although specific time savings are currently unknown. The skill's intermediate complexity means that while it may require some technical knowledge to implement, it is manageable within a 30-minute timeframe. This makes it an attractive option for developers and product managers looking to optimize their workflows without extensive setup. Buildforce-cli is particularly suited for developers and AI practitioners who are involved in engineering tasks. Its framework can be integrated into various projects, making it a versatile tool for teams aiming to adopt AI automation. For example, a software development team might use Buildforce-cli to automate repetitive coding tasks, allowing engineers to focus on more complex problem-solving and innovation. To implement Buildforce-cli, users should have a basic understanding of automation frameworks and AI principles. The skill fits seamlessly into AI-first workflows, providing a foundation for building more advanced AI agent skills. As the demand for automation continues to grow, integrating Buildforce-cli can position teams to stay ahead in the rapidly evolving landscape of AI automation.

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/berserkdisruptors/buildforce-cli

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

I need to create a new Python script for [SPECIFIC TASK]. Use the buildforce-cli to generate the initial code structure. Ensure it includes [KEY FUNCTIONALITIES] and follows [CODING STANDARDS]. Also, provide a brief explanation of the code's logic.

Example Output

Based on your request, I've generated a Python script for data processing using buildforce-cli. The script includes the following functionalities: data ingestion from CSV files, data cleaning, and basic statistical analysis. Here's the code structure:

```python
import pandas as pd

# Data Ingestion
def load_data(file_path):
    data = pd.read_csv(file_path)
    return data

# Data Cleaning
def clean_data(data):
    data = data.dropna()
    data = data.drop_duplicates()
    return data

# Statistical Analysis
def analyze_data(data):
    stats = data.describe()
    return stats

# Main Function
def main():
    file_path = 'data.csv'
    data = load_data(file_path)
    cleaned_data = clean_data(data)
    stats = analyze_data(cleaned_data)
    print(stats)

if __name__ == '__main__':
    main()
```

The script starts by importing the necessary library, pandas, which is widely used for data manipulation and analysis. The `load_data` function reads the CSV file and returns the data as a pandas DataFrame. The `clean_data` function handles data cleaning by removing missing values and duplicates. Finally, the `analyze_data` function generates basic statistics for the cleaned data. The `main` function orchestrates the entire process.