research-logger

What This Skill Does

The Research Logger is an advanced productivity suite designed for OpenClaw agents to bridge the gap between volatile web searches and persistent knowledge management. At its core, the tool functions as an automated research assistant that performs deep web queries and instantly serializes the results into both a local SQLite database and the Langfuse observability platform. By capturing the query, full result sets, custom topic tags, and high-precision timestamps, this skill ensures that every piece of information harvested during a research session is available for future retrieval. It effectively transforms your AI agent into a self-documenting research engine, ensuring that you never have to repeat a search or lose track of critical insights uncovered during your investigative workflows.

Installation

To integrate the Research Logger into your existing OpenClaw environment, ensure you have the necessary system permissions to manage local SQLite databases and network access. Run the following command in your terminal:

clawhub install openclaw/skills/skills/aiwithabidi/research-logger-pro

Ensure your baseDir variable is correctly configured in your environment to allow the Python script to execute from the correct path. Once installed, the skill exposes several CLI triggers and intent hooks that your agent will automatically detect and execute based on your natural language commands.

Use Cases

• Knowledge Management: Build a personal wiki by saving deep-dive research into specific technical or academic topics.
• Audit Trails: Keep a comprehensive log of the research conducted to reach specific conclusions, useful for corporate decision-making or technical project management.
• Rapid Recall: Instead of relying on search engine history, search your own database of curated research entries to find specific data points you gathered months ago.
• Workflow Optimization: Use the tool as a persistent context provider, where the agent references your past findings to inform current task execution.

Example Prompts

1. "Log a deep research query about the latest advancements in quantum computing and save it under the tag 'science'."
2. "Search my past research logs for anything related to vector databases or embedding models."
3. "Show me the 5 most recent research entries I've saved this week to help me catch up on my project."

Tips & Limitations

To get the most out of this tool, always provide descriptive tags during your requests; this makes the search feature significantly more effective. Be aware that because this tool writes to a local SQLite database, frequent, extremely large-scale logging may eventually impact local disk space if not managed with occasional cleanup. Ensure that your Langfuse credentials are correctly set up if you require cloud-based observability, otherwise, the agent will gracefully rely on the local SQLite store. Note that the accuracy of the logged content depends on the underlying search providers configured within your OpenClaw instance.