hive

🥇Gold

Hive is an outcome-driven agent development framework that evolves. It benefits operations teams by automating workflows and improving efficiency. It connects to Python-based tools and workflows, enabling self-improving agents that adapt to business needs.

3,9602,4520Updated 1w ago

Intermediate30min to implementautomation

Saves ~90 min per use

Quick InstallView Source

git clone https://github.com/adenhq/hive.git

Works with:

Claude

Overview

About This Skill

https://docs.adenhq.com/

Use Cases

Automate the creation of specialized worker agents for sales, marketing, or operations based on natural language goals.

Implement real-time monitoring and observability for agent performance and decision-making processes.

Facilitate continuous evaluation and adaptation of agents to improve their effectiveness over time.

Deploy agents in a headless environment with CI/CD integration for streamlined operations.

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/adenhq/hive

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 outcome-driven AI agent for [COMPANY] in the [INDUSTRY] sector that can evolve based on [DATA]. Provide a detailed plan outlining the agent's capabilities and expected improvements over time.

Example Output

### AI Agent Overview

**Company:** Tech Innovations Inc.  
**Industry:** Software Development  

**Capabilities:**  
- Automate code reviews and suggest improvements based on previous projects.  
- Analyze user feedback to adapt features in real-time.  
- Integrate with existing CI/CD pipelines to enhance deployment processes.

### Expected Improvements
- **Month 1:** 75% accuracy in identifying code issues.  
- **Month 3:** Improved suggestion accuracy to 85% through user feedback analysis.  
- **Month 6:** Full integration with user workflow, reducing deployment time by 30%.  

This agent will continuously learn from its interactions, ensuring it remains relevant and effective in optimizing software development processes.