Research Logger
AI research pipeline with automatic logging. Search via Perplexity, auto-save results to SQLite with topic and project metadata, full Langfuse tracing. Never lose a research session again. Use when conducting research, competitive analysis, or building a knowledge base.
Best use case
Research Logger is best used when you need a repeatable AI agent workflow instead of a one-off prompt.
AI research pipeline with automatic logging. Search via Perplexity, auto-save results to SQLite with topic and project metadata, full Langfuse tracing. Never lose a research session again. Use when conducting research, competitive analysis, or building a knowledge base.
Teams using Research Logger should expect a more consistent output, faster repeated execution, less prompt rewriting.
When to use this skill
- You want a reusable workflow that can be run more than once with consistent structure.
When not to use this skill
- You only need a quick one-off answer and do not need a reusable workflow.
- You cannot install or maintain the underlying files, dependencies, or repository context.
Installation
Claude Code / Cursor / Codex
Manual Installation
- Download SKILL.md from GitHub
- Place it in
.claude/skills/research-logger/SKILL.mdinside your project - Restart your AI agent — it will auto-discover the skill
How Research Logger Compares
| Feature / Agent | Research Logger | Standard Approach |
|---|---|---|
| Platform Support | Not specified | Limited / Varies |
| Context Awareness | High | Baseline |
| Installation Complexity | Unknown | N/A |
Frequently Asked Questions
What does this skill do?
AI research pipeline with automatic logging. Search via Perplexity, auto-save results to SQLite with topic and project metadata, full Langfuse tracing. Never lose a research session again. Use when conducting research, competitive analysis, or building a knowledge base.
Where can I find the source code?
You can find the source code on GitHub using the link provided at the top of the page.
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SKILL.md Source
# 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](https://www.linkedin.com/in/mohammad-ali-abidi) | [agxntsix.ai](https://www.agxntsix.ai)
[YouTube](https://youtube.com/@aiwithabidi) | [GitHub](https://github.com/aiwithabidi)
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## Profile