Setup & Installation
Or with the ClawHub CLI, for registry-managed skill folders outside a full OpenClaw workspace:
What This Skill Does
A command-line tool that analyzes and summarizes research notes stored in research_db.json. Provides summaries, keyword extraction, keyword search, and topic listing. Works alongside research-assistant, which handles note creation.
Avoids manually scanning all accumulated notes by providing frequency-based keyword extraction and pattern-matched key point detection in a single CLI call.
When to use it
- Summarizing a research topic before writing a report
- Finding which notes mention a specific tool or concept
- Reviewing all active research topics and their sizes
- Extracting recurring themes from accumulated notes
- Locating conclusions or key findings without re-reading notes
Example Workflow
Here's how your AI assistant might use this skill in practice.
User asks: summarize what I learned about income-experiments and find notes mentioning monetization
- 1Run note_processor.py summarize income-experiments to get note count, top tags, key points, and recent notes
- 2Run note_processor.py keywords income-experiments to extract top 20 recurring terms
- 3Run note_processor.py extract income-experiments monetization to find all notes containing that keyword
- 4Review matched notes with highlighted keyword and timestamps
A summary showing 4 notes, top tags like content and automation, key points surfaced by pattern detection, and a list of notes where monetization appears with context