A specialized signal extraction skill designed to transform noisy WeChat group chat logs into actionable intelligence and executive summaries.
Install & Download
1. ClawHub CLI
The fastest way to install a skill directly from the registry.
npx clawhub@latest install qclaw
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 qclaw 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 QClaw?
QClaw is a powerful utility within the Openclaw Skills ecosystem specifically engineered for WeChat group chat signal extraction. It addresses the common challenge of information overload in high-volume group environments by compressing long, disorganized conversations into structured, useful summaries. By focusing on intent and outcomes, QClaw allows developers and project managers to maintain high situational awareness without manually parsing hundreds of messages.
This skill is particularly effective at separating signal from noise, ensuring that critical project updates, client requests, and deadlines are never buried. It utilizes advanced processing to identify direct or implicit mentions, providing a streamlined view of the discussion that highlights risks, blockers, and next steps while maintaining a high level of technical accuracy and context preservation.
QClaw Use Cases
- Summarizing massive WeChat group chat histories into brief executive reports.
- Extracting definitive decisions and assigned action items from chaotic threads.
- Tracking specific keywords such as project codenames, client names, or urgent deadlines.
- Identifying mentions of the user or relevant team members that require immediate attention.
- Detecting potential conflicts, project risks, or expressions of urgency within group discussions.
How QClaw Works
- The user provides the raw chat data via plain text, copied transcripts, or structured JSON exports.
- QClaw parses the input to identify timestamps, senders, and message content to establish a chronological flow.
- The engine applies extraction logic to filter out noise (casual chatter) and isolate high-value information blocks.
- Decisions, tasks, and mentions are cross-referenced against user-supplied keywords or project context.
- The skill generates a structured report categorized by summary, action items, and risk assessment for immediate review.
QClaw Setup
To utilize QClaw, ensure you have the core environment ready. This skill is compatible with standard Openclaw Skills installation patterns.
# Install the OpenClaw CLI if you haven't already
npm install -g @openclaw/cli
# Add the QClaw skill to your current agent environment
openclaw skill add qclaw
Once installed, prepare your WeChat chat logs as a .txt or .json file for processing.
QClaw Data Schema & Taxonomy
QClaw expects a flexible input format but delivers a highly structured output to ensure consistency across Openclaw Skills workflows.
| Feature | Description |
|---|---|
| Accepted Input | Plain text logs, JSON arrays (timestamp, sender, content), or copied transcripts. |
| Primary Output | Executive Summary, Decisions, Action Items, Keyword Hits, Risks/Urgency, and Suggested Follow-ups. |
| Metadata | Includes emoji identifiers and versioning for compatibility with the Openclaw manifest. |
| Privacy | Logic favors anonymized or redacted logs and avoids long-term data retention. |
QClaw Advanced Features
- Multi-format support allowing seamless transition between raw text and structured JSON data sources.
- Intelligent keyword tracking that flags implicit mentions and semantic hits related to project milestones.
- Conflict and risk detection heuristics that identify urgency and blockers even when not explicitly stated.
- Seamless integration into broader OpenClaw workflows for automated task creation based on extracted action items.
SKILL.md
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