unifuncs-deep-search

What This Skill Does

The unifuncs-deep-search skill provides OpenClaw agents with high-performance, comprehensive deep-searching capabilities powered by the UniFuncs API. Unlike standard search tools that may only scrape top-level results, this skill is designed for intensive information gathering, research, and analysis. It processes complex queries by navigating multiple sources and synthesizing high-quality, relevant data, making it an essential utility for tasks requiring accuracy, breadth, and depth. Whether you are conducting market research, looking for technical documentation, or performing background checks, this tool ensures your agent has access to the most pertinent and up-to-date information available.

Installation

To integrate this skill into your OpenClaw environment, execute the following command in your terminal: clawhub install openclaw/skills/skills/vinlic/unifuncs-deep-search. Before use, ensure you have an active account at https://unifuncs.com/account to obtain your API Key. Once obtained, set the key as an environment variable by adding export UNIFUNCS_API_KEY="sk-your-api-key" to your shell profile. This configuration is necessary for the agent to authenticate with the UniFuncs servers.

Use Cases

This skill is ideal for research-intensive workloads. It is perfect for market analysts identifying trends across disparate sources, developers searching for specific, niche library configurations or architectural best practices, and writers gathering exhaustive facts for detailed reports. It excels when the answer is not contained in a single webpage but requires an iterative, multi-step search process across the broader internet.

Example Prompts

1. "Perform a deep search on the current limitations and long-term scalability of decentralized identity protocols in 2024."
2. "Research the historical performance and risk factors of semiconductor stocks during the last three economic cycles."
3. "Find comprehensive documentation and community consensus on the best practices for migrating a large-scale React codebase to Next.js."

Tips & Limitations

To maximize effectiveness, provide specific, context-rich queries rather than short, vague keywords. While the s2 model is recommended for its superior depth, note that deeper searches consume more tokens and have higher latency than standard web search. Ensure your API key has sufficient credit balance, as intensive deep searches perform multiple recursive requests. Avoid using this for simple, factual lookups (like current time or weather) where a standard lightweight query is more efficient and faster.