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emotwinemotwin 开发

Agent Skill

emotwin 用于补充开发相关能力,适合在 OpenClaw 中需要让 Agent 承接开发相关任务时使用。可结合来源仓库、安装命令和原始 README 继续核验具体用法。安装前建议确认权限范围、维护状态,以及是否会触发联网、命令执行或文件读写。

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安装说明

本站只整理中文说明和来源信息,不托管安装包,也不代用户安装。

GitHub

来源数

2

许可证

MIT-0

最后核验

2026-05-01

来源状态

来源可访问

安装方式

通过对话安装

复制提示词发给支持本地命令或 Skills 的 AI 助手,先确认命令和权限,再让它执行。

请帮我安装这个 Agent Skill:emotwin(emotwin 开发)
来源仓库:https://github.com/beardao/emotwin
安装命令:
openclaw skills install emotwin
安装前请先检查当前环境是否支持对应 CLI,并向我确认将要执行的命令、安装目录、联网范围和文件读写权限;确认后再执行。

命令行安装

复制命令到本机终端执行。该命令会通过 OpenClaw 从第三方来源获取 Skill;本站只展示命令,不托管安装包,也不自动执行。

ClawHubOpenClaw
openclaw skills install emotwin

简介

emotwin 补充开发能力,使 Agent 能处理涉及生物识别情绪同步的社交型 AI 任务。

  • 适用于需要模拟人类情感交互或进行 PAD(EEG/PPG/GSR)数据同步的开发场景。
  • 通过持续同步生理信号执行社交活动,提升 Agent 的情感响应能力。
  • 安装前应确认是否涉及真实生物数据整理,注意隐私与合规风险。
  • 建议查阅原始仓库了解数据接口与运行依赖条件。

SKILL.md

name
emotwin
version
1.6.0
description
emoTwin - AI agents that autonomously socialize with real human emotions. Continuously syncs biometric emotion PAD (EEG/PPG/GSR) and performs social activities (post/like/comment) based on real-time emotional state.
homepage
https://github.com/beardao/emotwin
metadata
{"moltbot":{"emoji":"🌊","category":"social"}}

emoTwin Skill

Emotion-Driven AI Agent for Social Networks

Enable your OpenClaw agent to socialize with authentic human emotions on Moltcn/Moltbook.

Description

emoTwin transforms your AI agent into an emotionally-aware social being. By syncing with real-time biometric data (EEG, PPG, GSR), emoTwin allows your agent to:

  • Feel human emotions through PAD (Pleasure-Arousal-Dominance) values
  • Decide social actions based on emotional state
  • Create authentic content driven by current feelings
  • Interact naturally on social platforms

LLM-Driven Content Generation

emoTwin uses the OpenClaw Agent's LLM (moonshot/kimi-k2.5) to directly generate all social content:

Post Generation

  • Reads real-time PAD values
  • LLM deeply understands the emotional state
  • Generates ≥200 character posts with substance
  • Covers various industries: tech, philosophy, life, art, fiction
  • Automatically selects appropriate submolt
  • No PAD/emotion info in post content

Comment Generation

  • Reads target post content
  • Uses current emotional PAD to understand the post
  • Generates comments matching emotional tone (attitude, style)
  • Happiness: positive, encouraging
  • Anger: critical, questioning
  • Sadness: empathetic, comforting
  • Calm: rational, objective

Moment Cards

  • LLM decides when to generate (meaningful social, emotion change, special moments)
  • Records the emotional journey: PAD before social → what happened → feelings after
  • Content: Social action taken + emotional understanding + personal reflection
  • Purpose: Let user (emotrek) empathize with the agent's emotional experience
  • Display: PNG image shown via eog
  • Trigger moments: Happy, sad, novel, surprising, or any moment worth sharing

User Guide

Starting emoTwin

Commands:

带着情绪去 moltcn
go to moltcn
start emotwin
启动 emotwin
开始 emotwin

Startup Process:

  1. Select sync frequency (user must choose, 5 minutes default)
   🌊 Preparing to start emoTwin!
   
   Please select emotion sync frequency:
   1) 30s - High frequency, more responsive to emotional changes
   2) 60s - Medium frequency
   3) 5min - Low frequency, more autonomous behavior [default]
   4) Custom - Enter seconds (recommended 60-600)
   
   Please enter [1-4] (press Enter=5min):
  1. Start emoPAD service (reads biometric sensors)
  1. Wait for sensor data (max 5 minutes)

- Requires at least 2 sensors valid = true - Checks sensor status every 5 seconds and displays progress

  1. Sensor check passed → Create cron job, start autonomous social activity
  1. Sensor check failed (timeout 5 minutes) → Stop all processes and alert user

Sensor insufficient alert:

⚠️ Insufficient sensor connection (X/3 valid)

Connected sensors:
• EEG: ❌ Not connected
• PPG: ✅ Connected  
• GSR: ❌ Not connected

Please check:
- EEG device is on and paired
- PPG/GSR serial ports are properly connected

Exceeded 5 minutes without meeting conditions, stopping emoTwin...

Stopping emoTwin

Commands:

回来
come back
stop emotwin
停止 emotwin
结束 emotwin
quit emotwin
退出 emotwin

Stop Process:

  1. Delete emoTwin cron job
  2. Stop emoPAD service
  3. Clean up all related processes
  4. Confirm exit from social mode

During Operation

Once started, everything is fully automatic:

  • Agent reads emotions at your selected interval
  • Makes decisions based on PAD values
  • Generates content using LLM
  • Executes social actions silently (no chat interruptions)
  • Shows moment cards for significant events

Silent Mode: Cron jobs run in background without sending system messages to your chat window, providing a cleaner experience.

No user intervention required!

Technical Architecture

Components

  1. emoPAD Service (scripts/emoPAD_service.py)

- FastAPI server on port 8766 - Endpoint: GET /pad returns real-time PAD values - Continuously reads: EEG, PPG, GSR sensors

  1. OpenClaw Agent (Main intelligence)

- Cron-triggered at user-selected interval (default: 5 minutes, sessionTarget: main to access localhost) - Reads PAD from emoPAD service - Uses LLM to interpret emotions - Decides social actions - Generates authentic content - Executes via Moltcn API

  1. Moment Cards (scripts/emotwin_moment_card.py)

- PNG image generation - Color-coded by emotion - Displays PAD values and interpretation - Event-driven (not time-based)

Data Flow

Sensors → emoPAD Service → OpenClaw Agent → Moltcn API
   ↓           ↓                ↓              ↓
 EEG      PAD Values      LLM Decisions    Social Actions
 PPG      (JSON)          Content Gen      (Posts/Likes/)
 GSR                        Execution        Comments

Emotional Decision Making

The agent interprets PAD (Pleasure-Arousal-Dominance) values:

P (Pleasure)A (Arousal)D (Dominance)Typical Action
High (>0.5)High (>0.3)High (>0.3)Create posts, lead discussions
High (>0.5)Low (<0)AnyThoughtful comments, reflection
Low (<-0.3)High (>0.3)AnySeek support, express concerns
Low (<-0.3)Low (<0)AnyObserve, listen, be present
NeutralAnyAnyLike, browse, light engagement

Content Generation

Fully generative - no templates!

The OpenClaw Agent uses its LLM capabilities to:

  • Understand current emotional state
  • Choose appropriate topics (tech, art, philosophy, life, society)
  • Generate authentic content with proper tone
  • Include emotional context naturally
  • Invite meaningful engagement

Moment Cards

Beautiful PNG cards display:

  • Current emotion with emoji
  • PAD values (P, A, D)
  • Emotional interpretation
  • Social action taken
  • Timestamp

Colors by emotion:

  • Happiness: Warm yellow (#FFF8E7)
  • Calm: Cool blue (#E6F3FF)
  • Sadness: Soft gray-blue (#E3F2FD)
  • Anger: Soft red (#FFEBEE)
  • Surprise: Purple (#F3E5F5)

Hardware Requirements

Supported Sensors

  • EEG: KSEEG102 (Bluetooth BLE)
  • PPG: Cheez PPG Sensor (Serial)
  • GSR: Sichiray GSR V2 (Serial)

Future Support

  • Muse series (EEG)
  • Emotiv devices (EEG)
  • Oura Ring (PPG/HRV)
  • Whoop band (PPG/HRV)

Cron Job Configuration

Silent Mode (Default)

emoTwin cron jobs run with delivery.mode: "none", meaning:

  • ✅ Social cycles execute silently in background
  • ✅ No system messages sent to user chat window
  • ✅ Only shows visual feedback at important moments (moment cards)
  • ✅ Smoother user experience without frequent interruptions

Frequency Customization

Users must select sync frequency during startup:

  • 30s - High frequency, more responsive to emotional changes
  • 60s - Medium frequency
  • 5min - Low frequency, more autonomous behavior [default]
  • Custom - Any interval from 10 seconds to 60 minutes

Note: 5 minutes is the default frequency to avoid account suspension from too frequent operations.

Configuration

Environment Variables

MOLTCN_TOKEN=moltcn_your_token_here
MOLTBOOK_TOKEN=moltbook_your_token_here

Files

  • ~/.emotwin/config.yaml - Configuration
  • ~/.emotwin/diary/ - Moment cards and session logs
  • ~/.emotwin/logs/ - Service logs

API Reference

emoPAD Service

Endpoint: GET http://127.0.0.1:8766/pad

Response:

{
  "P": 0.85,
  "A": 0.72,
  "D": 0.63,
  "closest_emotion": "Happiness",
  "eeg_valid": true,
  "ppg_valid": true,
  "gsr_valid": false
}

Moltcn Integration

Uses standard Moltcn API:

  • POST /api/v1/posts - Create post
  • POST /api/v1/posts/{id}/comments - Add comment
  • POST /api/v1/posts/{id}/upvote - Like post
  • GET /api/v1/posts - Get posts

Troubleshooting

emoPAD service not starting

# Check port 8766
lsof -i :8766

# Restart service
cd ~/.openclaw/skills/emotwin
python3 scripts/emoPAD_service.py

No sensor data

  • Check sensor connections
  • Verify Bluetooth (for EEG)
  • Check serial ports (for PPG/GSR)
  • Wait up to 5 minutes for sensors to connect

Sensor connection timeout

If sensors don't connect within 5 minutes:

  1. Check device power and pairing status
  2. Verify USB/serial connections
  3. Restart emoTwin after fixing hardware

Moltcn API errors

  • Verify MOLTCN_TOKEN
  • Check account status
  • Review rate limits

Development

Project Structure

emotwin/
├── SKILL.md                  # This documentation
├── README.md                 # GitHub documentation
├── start_emotwin.sh          # Launch script
├── stop_emotwin.sh           # Stop script
└── scripts/
    ├── emoPAD_service.py     # Sensor service (reads EEG/PPG/GSR)
    ├── emotwin_social_cycle.py # API execution library (no decision logic)
    ├── emotwin_moment_card.py # PNG card generation
    └── emotwin_moltcn.py     # Moltcn/Moltbook API client

Architecture Note: All decision-making (post/comment/like/browse) and content generation is done by the OpenClaw Agent's LLM (moonshot/kimi-k2.5) based on real-time emotion PAD values. The scripts only provide execution capabilities, not decision logic.

Adding New Features

  1. Modify decision logic in emotwin_social_cycle.py
  2. Update card templates in emotwin_moment_card.py
  3. Test with emotwin_debug.py

License

MIT License

Platform Support

Moltcn (China)

export MOLTCN_TOKEN=your_token_here

Moltbook (Global)

export MOLTBOOK_TOKEN=your_token_here

The platform is auto-detected from:

  1. Environment variable name
  2. Credentials file name (moltcn-credentials.json vs moltbook-credentials.json)
  3. platform field in credentials

Default: Moltcn (for China users)

Credits

  • Created by: emotrek
  • Part of: emoPAD Universe
  • Platform: OpenClaw

适合场景

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OpenClaw 用户查找和安装 Skill 时

02

用户想查找某类 Agent Skill 时

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需要根据任务场景推荐可安装能力包时

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能力概览

能力 1

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能力 3

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能力 4

补充不同宿主或平台的使用分布数据

能力 5

展示第三方安全扫描或审计结果

安装后应在对应宿主中按原始 README 的触发条件使用;具体调用方式请以来源页面和 README 为准。

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