A high-performance utility designed to convert unstructured WhatsApp TXT and JSON exports into structured, machine-readable message objects.
Install & Download
1. ClawHub CLI
The fastest way to install a skill directly from the registry.
npx clawhub@latest install message-parser
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 message-parser 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 Message Parser?
The Message Parser is a foundational component within the Openclaw Skills ecosystem, specifically engineered to handle the nuances of chat export formatting. It transforms raw, often messy text files into a strict array of objects containing timestamps, sender information, and message content. By serving as the entry point for chat data processing, it ensures that subsequent AI agents receive clean, validated data for analysis.
This skill is built for developers and automation specialists who need to bridge the gap between human-readable chat logs and programmatic data pipelines. It meticulously handles edge cases such as multiline message continuations and varies date formats, making it a reliable first step in any complex Openclaw Skills workflow.
Message Parser Use Cases
- Normalizing raw WhatsApp TXT exports for downstream lead extraction.
- Converting unstructured group chat dumps into structured JSON for archival or analysis.
- Cleaning chat logs by removing system boilerplate like encryption notices and member alerts.
- Preparing chat data for sentiment analysis or priority scoring within a multi-agent chain.
How Message Parser Works
- The skill accepts raw input as plain text, JSON, or direct file contents provided by a supervisor agent.
- It identifies the source format and applies regex patterns to detect timestamp markers and sender delimiters.
- Raw lines are normalized into a schema-compliant object featuring timestamp (RFC 3339), sender, and content.
- Multiline messages are intelligently merged to prevent data fragmentation.
- System-generated messages and boilerplate are filtered out while preserving the chronological order of the conversation.
- The resulting array is validated against a strict JSON schema to ensure data integrity for the next Openclaw Skills in the chain.
Message Parser Setup
To integrate the Message Parser into your workflow, ensure the skill is registered in your agent's directory. You can trigger the parsing logic via natural language commands or CLI interactions.
# Example: Triggering the parser via a CLI-based agent
openclaw run message-parser --input ./whatsapp_chat_export.txt
Message Parser Data Schema & Taxonomy
The output is a validated array of message objects adhering to the following structure:
| Property | Type | Description |
|---|---|---|
timestamp |
string | RFC 3339 formatted date and time |
sender |
string | The name or identifier of the message author |
content |
string | The text body of the message |
All output is strictly validated against references/parsed-message-array.schema.json to guarantee compatibility with other Openclaw Skills.
Message Parser Advanced Features
- Context-aware multiline merging for long conversational messages.
- Automated boilerplate suppression to focus strictly on human interaction data.
- Schema-locked output ensures zero-fail handoffs to extraction or storage agents.
- High-fidelity ordering that maintains original source sequence even during timestamp collisions.
SKILL.md
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