A local-first analysis tool for summarizing, searching, and extracting key insights from research databases.
The fastest way to install a skill directly from the registry.
npx clawhub@latest install note-processor
Copy the skill folder to one of these locations
~/.openclaw/skills/ <project>/skills/ Priority: Workspace > Local > Bundled
Copy this prompt to OpenClaw to install it automatically.
Help me install note-processor using Clawhub. If Clawhub is not installed, install it first (npm i -g clawhub).
Get the raw skill files in a ZIP archive.
The Note Processor is a specialized utility designed to transform raw research data into actionable insights. It integrates directly with local JSON databases created by research assistants to provide summaries, keyword extraction, and targeted search capabilities. As a vital component of the Openclaw Skills library, it enables developers to review research progress and identify patterns without manually parsing hundreds of individual notes.
This skill is built for efficiency, offering a zero-cost solution that requires no external API keys or cloud dependencies. By processing data locally, it ensures your research remains private while providing professional-grade analysis tools directly in your terminal.
The Note Processor is designed to work out of the box with Python 3 and requires no additional dependencies. It is fully compatible with other Openclaw Skills that use the standard research database format.
# Check available topics and statistics
note_processor.py list
# Generate a summary for a specific topic
note_processor.py summarize <topic-name>
The skill manages research data using a structured JSON schema. It organizes information into the following taxonomy:
| Attribute | Description |
|---|---|
| Topic | The primary identifier for the research category |
| Notes | Array of individual entries with timestamps |
| Tags | User-defined metadata for categorization |
| Metrics | Calculated word counts and note frequency |
| Keywords | Extracted frequency-based terms (filtered) |
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