A safe and encouraging AI agent that helps users decode text messages and navigate crush situations with playful, grounded advice.
Install & Download
1. ClawHub CLI
The fastest way to install a skill directly from the registry.
npx clawhub@latest install ai-crush-simulator
2. Manual Installation
Copy the skill folder to one of these locations
~/.openclaw/skills/ <project>/skills/ Priority: Workspace > Local > Bundled
3. Prompt Installation
Copy this prompt to OpenClaw to install it automatically.
Help me install ai-crush-simulator 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 AI Crush Simulator?
AI Crush Simulator is an innovative social intelligence tool designed to help users interpret the often-confusing world of modern dating and friendships. By integrating this capability into your library of Openclaw Skills, you gain access to a sophisticated heuristics engine that evaluates social signals, calculates vibe scores, and offers actionable communication tips. It is built to be a supportive companion that turns vague interactions into clear, manageable insights while maintaining a respectful and fun tone.
This skill prioritizes safety and authenticity, ensuring that all advice is free from manipulative tactics or harassment. Whether you are looking to understand a single text or evaluate a months-long connection, AI Crush Simulator provides a structured way to process social data. As part of the wider ecosystem of Openclaw Skills, it demonstrates how AI can be applied to soft skills and personal development in a youth-friendly and private manner.
AI Crush Simulator Use Cases
- Decoding ambiguous text messages to understand potential warmth and intent.
- Analyzing social situations to identify green, yellow, or red flags in a relationship.
- Generating multiple reply options ranging from bold to chill for any conversation.
- Deciding on an empowering next move based on a grounded analysis of recent interactions.
How AI Crush Simulator Works
- The user inputs a message or a description of a social situation into the agent.
- The scoring engine evaluates the input against a dictionary of over 30 positive, negative, and ambiguous signal patterns.
- The textDecoder module analyzes specific markers like emoji usage, message length, and question frequency to determine a warmth score.
- The replyGenerator creates three distinct response templates tailored to the user's specific goals, such as showing interest or keeping it cool.
- The nextMove advisor combines all heuristic data to recommend a strategic action, such as giving space or asking the person to hang out.
AI Crush Simulator Setup
To add this agent to your collection of Openclaw Skills, follow these installation steps to set up the local environment:
# Clone the repository
git clone https://github.com/example/ai-crush-simulator.git
# Navigate to the directory
cd ai-crush-simulator
# Install dependencies
npm install
# Run the local CLI for testing
npm run start:cli
AI Crush Simulator Data Schema & Taxonomy
The skill utilizes a structured data model to process social interactions and generate consistent results.
| Object | Purpose | Key Attributes |
|---|---|---|
CrushSituation |
Input for high-level analysis | howTheyMet, interactionFrequency, yourFeelingConfidence |
AnalysisResult |
Output of the vibe check | vibeScore, connectionDepth, signals, flags |
DecodedText |
Text interpretation data | readings, overallVibe, warmthScore |
ReplyOptions |
Communication suggestions | replies (Bold/Chill/Safe), coachingTip |
NextMoveResult |
Strategic recommendation | action, reasoning, empoweringTips |
AI Crush Simulator Advanced Features
- Local Heuristics Engine: Runs entirely on-device without external API dependencies, ensuring high privacy for sensitive social data within Openclaw Skills.
- Extensible Signal Dictionary: Power users can modify
heuristics.tsto add custom signal patterns and weightings. - Multi-Module Composition: Modules can be called individually for quick tasks or chained together for a comprehensive crush check.
- Safety-First Logic: Hardcoded templates ensure G-rated, non-manipulative, and respectful output at all times.
SKILL.md
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