Project Aura: The Emo-Agent-Toolkit for Openclaw

A lightweight emotional presentation layer for AI companions using RLHF and dynamic weighted algorithms.

bryanchen3777
v1.8.0
Mar 30, 2026
0
665
0

Install & Download

1. ClawHub CLI

The fastest way to install a skill directly from the registry.

npx clawhub@latest install project-aura

2. Manual Installation

Copy the skill folder to one of these locations

Global
~/.openclaw/skills/
Workspace
<project>/skills/

Priority: Workspace > Local > Bundled

3. Prompt Installation

Copy this prompt to OpenClaw to install it automatically.

Help me install project-aura using Clawhub. If Clawhub is not installed, install it first (npm i -g clawhub).

Prefer to download?

Get the raw skill files in a ZIP archive.

What is Project Aura: The Emo-Agent-Toolkit?

Project Aura is a specialized framework designed to provide AI agents with a sophisticated Emotional Presentation Layer. As part of the Openclaw Skills ecosystem, it allows developers to move beyond static responses by implementing seven distinct personality modules that range from lighthearted flirting to deep emotional transcendence. The toolkit focuses on adding depth and personality to AI interactions, making companions feel more human and responsive to user needs.

By integrating this skill, developers can leverage a privacy-first, local-only storage system that ensures user data remains secure while the AI learns through a Reinforcement Learning from Human Feedback (RLHF) mechanism. Project Aura is the ideal solution for those looking to build more engaging and emotionally resonant AI agents using Openclaw Skills.

Project Aura: The Emo-Agent-Toolkit Use Cases

  • Creating more empathetic and human-like AI companions within Openclaw Skills.
  • Implementing a dynamic personality system that evolves based on user feedback.
  • Generating multi-stage emotional combos for complex conversational storytelling.
  • Building lightweight AI projects that require personality without heavy cloud dependencies.

How Project Aura: The Emo-Agent-Toolkit Works

  1. The developer initializes the GreenTeaSkill class from the toolkit.
  2. The agent selects a phrase from one of the 7 specific emotional modules based on the conversation context.
  3. A dynamic weighted random algorithm chooses the most appropriate response, factoring in past performance ratings.
  4. The user provides feedback via the increase_rating or decrease_rating methods, triggering the RLHF self-evolution process.
  5. The system persists all learning outcomes in local JSON files for long-term memory and continuity within Openclaw Skills.

Project Aura: The Emo-Agent-Toolkit Setup

To integrate this emotional toolkit into your Openclaw Skills project, follow these steps:

git clone https://github.com/bryanchen3777/Project-Aura.git

Ensure you have Python 3.8 or higher installed. There are no external dependencies required. Initialize the skill in your code as follows:

import sys
sys.path.append('scripts')
from scripts.green_tea_skill.selector import GreenTeaSkill

# Initialize the emotional engine
yua_skill = GreenTeaSkill()

Project Aura: The Emo-Agent-Toolkit Data Schema & Taxonomy

Project Aura manages its personality data through a structured local JSON storage system. This ensures that every instance of the agent can maintain its unique personality profile in Openclaw Skills.

File Component Purpose Metadata Included
Emotional Modules Stores available phrases Phrase text, UID
Weight Registry Tracks phrase performance Rating score, usage count
Local JSON Persistent memory User preferences, evolution state

Project Aura: The Emo-Agent-Toolkit Advanced Features

  • Combo System: Sequence multiple emotional responses, such as deep confession followed by playful resolution, for realistic interaction flows.
  • RLHF Self-Evolution: Autonomous learning where the agent improves its phrase selection based on direct user feedback within Openclaw Skills.
  • Dynamic Weighting: Automatically adjusts the frequency of phrases based on historical engagement data.
  • Privacy-First Architecture: Completely local execution with no cloud API requirements, perfect for secure and private AI implementations.

SKILL.md


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