Research Logger Pro
VerifiedAuto-saves deep search results to SQLite and Langfuse. Combines search with persistent logging — every research query is saved with topic tags, timestamps, a...
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# Research Logger 📝🔬
Search + auto-save pipeline. Every research query is logged to SQLite with Langfuse tracing.
When to Use
- Research that you want to save and recall later
- Building a knowledge base from repeated searches
- Reviewing past research on a topic
- Creating an audit trail of research decisions
Usage
```bash # Search and auto-log python3 {baseDir}/scripts/research_logger.py log quick "what is RAG" python3 {baseDir}/scripts/research_logger.py log pro "compare vector databases" --topic "databases"
# Search past research python3 {baseDir}/scripts/research_logger.py search "vector databases"
# View recent entries python3 {baseDir}/scripts/research_logger.py recent --limit 5 ```
Credits
Built by M. Abidi | agxntsix.ai YouTube | GitHub Part of the AgxntSix Skill Suite for OpenClaw agents.
📅 Need help setting up OpenClaw for your business? Book a free consultation
Use Cases
- Conduct structured research with systematic literature review workflows
- Log research progress and findings for reproducibility and tracking
- Analyze and synthesize research findings from multiple sources
- Generate research summaries and reports for team collaboration
Pros & Cons
Pros
- +Handles database operations with proper safety patterns
- +Supports multiple database backends for flexibility
- +Clear documentation makes it easy to get started and integrate
Cons
- -Database-specific features limit portability across different database engines
- -Requires proper database credentials and network access
FAQ
What does Research Logger Pro do?
What platforms support Research Logger Pro?
What are the use cases for Research Logger Pro?
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