research-logger

What This Skill Does

The Research Logger is an advanced AI-driven research pipeline designed to bridge the gap between volatile search sessions and persistent knowledge management. It integrates Perplexity search capabilities with automated SQLite database logging, ensuring that every research query, finding, and decision is permanently captured. By incorporating Langfuse tracing, it provides developers and agents with visibility into the reasoning process, making it an essential tool for complex investigative tasks. It transforms the ephemeral nature of AI chat sessions into a searchable, organized repository that grows alongside your projects.

Installation

To integrate this skill into your environment, ensure you have the OpenClaw environment initialized. Run the following command in your terminal:

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

Ensure that your environment variables for Perplexity API access are configured before executing your first search query.

Use Cases

• Competitive Analysis: Keep a chronological log of market research on competitors, indexed by project name for easy retrieval.
• Knowledge Base Construction: Systematically build a proprietary dataset of technical information by capturing results from repeated research cycles.
• Audit Trails: Track the decision-making history of an AI agent, perfect for compliance-heavy environments or long-term projects where context retention is paramount.
• Rapid Information Retrieval: Use the search functionality to query your internal history instead of re-running costly or time-consuming search operations.

Example Prompts

1. "Research the latest advancements in LLM quantization techniques and save the findings under the project 'Model Optimization'."
2. "Search my research history for everything related to 'vector databases' and summarize the top three takeaways."
3. "Show me the last 5 research queries I conducted to refresh my context for our current development sprint."

Tips & Limitations

• Metadata Management: Always utilize the --topic and --project flags during the logging phase to ensure your SQLite database remains organized and searchable as your data volume grows.
• Storage Oversight: While SQLite is efficient, monitor your storage if conducting high-frequency, massive-scale automated research.
• Privacy: Since this tool performs external API calls, ensure that sensitive proprietary data is scrubbed before being passed to search providers if security protocols require it.
• Data Integrity: Regularly back up the underlying SQLite file located in your local data directory to prevent data loss during system migrations.