Chat Analyzer for Openclaw

Chat Analyzer is a specialized communication assistant that decodes message subtext, emotional tone, and relationship dynamics through advanced sentiment mapping.

imwyvern
v1.0.2
Mar 31, 2026
1
1.3k
0

Install & Download

1. ClawHub CLI

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

npx clawhub@latest install chat-analyzer

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 chat-analyzer 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 Chat Analyzer?

Chat Analyzer is an expert communication tool designed for Openclaw Skills that functions as a digital communication psychologist. It goes beyond surface-level text to identify emotional undertones, hidden motivations, and unspoken dynamics within digital conversations. Whether reviewing work threads, group chats, or personal relationships, this skill provides a structured framework for understanding the "why" behind the words.

By leveraging this skill within the Openclaw Skills ecosystem, users can move from impulsive reactions to informed understanding. It evaluates complex factors such as effort imbalance, reciprocity, and energy shifts, offering users a high-confidence interpretation of digital interactions across various platforms including WeChat and standard SMS.

Chat Analyzer Use Cases

  • Decoding ambiguous professional emails or Slack messages to determine true intent or urgency.
  • Analyzing personal relationship dynamics to identify shifts in engagement or effort imbalance.
  • Understanding cultural-specific texting patterns and platform-specific nuances like WeChat emoji usage.
  • Providing suggested response directions to maintain healthy communication boundaries.
  • Identifying turning points in long conversation histories where the tone shifted significantly.

How Chat Analyzer Works

  1. The user inputs a single message or a full conversation transcript into the Openclaw Skills interface.
  2. The system analyzes the literal surface meaning to establish basic context.
  3. The analyzer maps the emotional tone across specific categories ranging from warm engagement to cold avoidance.
  4. It detects hidden intents, such as boundary testing, reassurance seeking, or power plays.
  5. Pattern detection evaluates response times and initiative balance to determine the overall trajectory of the dynamic.
  6. A structured report is generated, including a confidence rating and actionable advice for the next step.

Chat Analyzer Setup

To integrate Chat Analyzer into your local environment, ensure you have the Openclaw Skills framework installed and follow these steps:

# Navigate to your skills directory
cd ~/openclaw/skills

# Clone the chat-analyzer repository
git clone https://github.com/openclaw/chat-analyzer.git

# Register the skill with your agent
openclaw register ./chat-analyzer

Chat Analyzer Data Schema & Taxonomy

The skill organizes analysis results into specific metadata blocks for clear visualization:

Data Point Description
Literal Meaning The objective text content analyzed.
Subtext (Means) The interpreted hidden meaning or unspoken intent.
Tone Map Emoji-based labels (e.g., Warm, Neutral, Anxious, Cold).
Dynamic Overview Summary of who is leading the conversation and the energy match.
Confidence Score Percentage-based reliability metric for the interpretation.
Platform Rules Context-aware logic for WeChat, WhatsApp, and general texting.

Chat Analyzer Advanced Features

  • Multi-platform pattern recognition (specialized logic for WeChat, SMS, and work chats).
  • Emotional labor distribution analysis to track who is putting in more effort.
  • Confidence rating system (High/Moderate/Low) to prevent over-analysis of ambiguous data.
  • Turning point detection to pinpoint exactly where a conversation flow changed.
  • Integration with pattern memory for long-term conversation tracking.

SKILL.md


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