deep-search

What This Skill Does

The deep-search skill provides a high-powered, multi-tier research interface for OpenClaw agents, leveraging the Perplexity API to deliver synthesized, accurate, and cited information. It serves as an intelligent research assistant capable of filtering through vast quantities of web data to provide precise answers. By integrating Langfuse for observability, every query is tracked, allowing for performance monitoring and transparency in agent reasoning. The tool offers three distinct tiers of processing power—quick, pro, and deep—ensuring that users can balance response latency with the depth of analysis required. Whether you are performing a simple fact-check or a complex, multi-faceted market analysis, deep-search delivers context-aware results across specific domains like academic literature, news, or community discussions.

Installation

To integrate this capability into your agent workflow, use the OpenClaw management utility. Run the following command in your terminal: clawhub install openclaw/skills/skills/aiwithabidi/deep-search-pro Ensure you have configured your environment variables, specifically PERPLEXITY_API_KEY, to grant the agent search permissions. Optionally, include OPENROUTER_API_KEY for detailed Langfuse cost tracking.

Use Cases

This skill is ideal for tasks requiring external context beyond the agent's pre-trained weights. Use it for:

• Market Analysis: Evaluating competitor strategies or technical architecture trends.
• Fact-Checking: Verifying claims against real-time web sources.
• Academic Research: Summarizing findings from scholarly papers via the academic focus mode.
• Trend Monitoring: Aggregating recent news or community sentiment from Reddit and YouTube.
• Comparative Research: Comparing software frameworks, hardware, or consumer products.

Example Prompts

1. "Look up the current status of the OpenAI O1 release and provide a summary of its key breakthroughs."
2. "Compare the performance of React vs. Vue.js for enterprise-level applications, cite your sources."
3. "Deep search for the latest trends in autonomous agent frameworks and analyze how they impact business automation."

Tips & Limitations

• Tier Selection: Use the 'quick' tier for simple queries to keep costs low and speed high. Reserve 'deep' for complex synthesis to maximize accuracy.
• Focus Modes: Always utilize the --focus flag (e.g., academic, news) to significantly improve the relevance of your search results.
• Cost Awareness: The 'deep' mode consumes more tokens and costs more per request; ensure you monitor usage via Langfuse.
• Latency: Be mindful that 'deep' mode may take up to 20 seconds; design your UI or agent flow to handle this wait time gracefully.