Note Processor for Openclaw

A local-first analysis tool for summarizing, searching, and extracting key insights from research databases.

johstracke
v1.0.0
Feb 8, 2026
2
2.2k
0

Install & Download

1. ClawHub CLI

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

npx clawhub@latest install note-processor

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 note-processor 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 Note Processor?

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.

Note Processor Use Cases

  • Summarizing complex research topics into key points and statistics.
  • Extracting frequently used keywords to identify hidden themes or trends.
  • Searching for specific data points or references within large research datasets.
  • Reviewing overall project progress and topic distribution across a workspace.
  • Generating structured overviews before drafting formal reports or documentation.

How Note Processor Works

  1. The skill accesses the research_db.json file located within the local environment.
  2. It parses the JSON structure to isolate specific research topics and their associated metadata.
  3. The processor applies frequency-based logic to identify top keywords while filtering out common stop words.
  4. It scans note content for priority indicators like 'critical' or 'essential' to automatically detect key points.
  5. Results are rendered in a clean, technical format for immediate review or redirection to external files.

Note Processor Setup

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>

Note Processor Data Schema & Taxonomy

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)

Note Processor Advanced Features

  • Pattern-based key point detection using priority markers for automated insight generation.
  • Built-in stop-word filtering optimized for technical and research-oriented English.
  • Seamless integration with research-assistant for a unified research-to-analysis pipeline.
  • Lightweight keyword extraction that operates without the need for expensive LLM tokens.
  • Support for CLI redirection to export summaries directly into markdown or text files.

SKILL.md


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