Research Logger for Openclaw

A streamlined automation skill that performs web research, fetches relevant media, and logs structured findings directly into Bear notes.

terrycarter1985
v1.0.0
May 12, 2026
0
652
0

Install & Download

1. ClawHub CLI

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

npx clawhub@latest install research-logger-tool

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 research-logger-tool 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 Research Logger?

Research Logger is a powerful addition to the Openclaw Skills ecosystem designed to eliminate the friction of manual data collection. By combining web search capabilities with automated note generation, it allows developers and researchers to transform a simple CLI command into a rich, formatted Bear note.

The skill bridges the gap between raw information gathering and personal knowledge management. It doesn't just pull text; it contextualizes findings by matching them with visual media and organizing them into a professional template that includes summaries, key findings, and actionable next steps.

Research Logger Use Cases

  • Rapidly documenting new technical concepts or library documentation during a development sprint.
  • Automating the creation of visual-rich daily research logs for academic or professional projects.
  • Creating a centralized knowledge base in Bear with consistent tagging and formatting across all entries.
  • Streamlining competitive analysis or market research by gathering top web results and source links automatically.

How Research Logger Works

  1. The user initiates the process via a CLI command providing a topic and optional tags.
  2. The skill executes a web search and fetch routine to gather the most relevant content and source URLs.
  3. A specific search is sent to gifgrep to find a relevant GIF that provides visual context for the topic.
  4. An LLM processes the gathered text to extract a summary, the top three key findings, and suggested action items.
  5. The skill populates the research_template.md file with the dynamic data, including placeholders for the date, media, and links.
  6. The final rendered content is pushed to the Bear app on macOS using the grizzly CLI tool.

Research Logger Setup

To get started with this skill from the Openclaw Skills collection, ensure you have the following requirements met:

  1. Install Grizzly: Ensure the Bear CLI is available on your macOS system.
go install github.com/tylerwince/grizzly/cmd/grizzly@latest
  1. Template Placement: Verify that notes/research_template.md exists in your workspace root.
  2. Execute: Run the logger script with your desired topic.
bash scripts/research_logger.sh "your topic" "tag1,tag2"

Research Logger Data Schema & Taxonomy

The Research Logger uses a structured template system to maintain data integrity across your notes.

Component Description Format
Metadata Title, Date, and Tags YAML/Bear Tags
Findings Top 3 extracted key points Bulleted List
Media GIF URL and Alt-text from gifgrep Markdown Image Syntax
Sources List of URLs from search results Markdown Links
Actions 3 generated action items Task List

Research Logger Advanced Features

  • Custom template support: Modify notes/research_template.md to change how Openclaw Skills format your data.
  • Automated media matching: Uses gifgrep to ensure every note has a relevant visual hook without manual searching.
  • Multi-tool orchestration: Seamlessly integrates web fetching, LLM summarization, and local app interaction in a single workflow.
  • Flexible tagging: Pass custom comma-separated tags directly through the CLI to maintain a clean Bear organizational structure.

SKILL.md


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