perplexity-research
Conduct deep research using Perplexity Agent API with web search, reasoning, and multi-model analysis. Use when the user needs current information, market research, trend analysis, investment insights, or comprehensive research on any topic requiring web search and reasoning capabilities.
Why use this skill?
Integrate powerful web search and deep reasoning into your OpenClaw agent. Get real-time data, cost-tracked research, and multi-model analysis for complex tasks.
Install via CLI (Recommended)
clawhub install openclaw/skills/skills/hushenglang/perplexity-researchWhat This Skill Does
The Perplexity Research skill provides OpenClaw agents with advanced web-searching and analytical capabilities. By leveraging the Perplexity Agent API, this skill empowers agents to go beyond basic LLM knowledge by performing real-time web lookups, synthesizing complex data, and applying high-reasoning effort to answer queries. It is designed to handle tasks that require current information, market analysis, or deep technical investigation while providing built-in cost and token tracking for every operation.
Installation
To integrate this skill into your environment, use the OpenClaw command-line interface. First, ensure you have your environment variable PERPLEXITY_API_KEY configured with your valid API credentials. Then, run the following command in your terminal:
clawhub install openclaw/skills/skills/hushenglang/perplexity-research
This will pull the necessary scripts, including perplexity_client.py, into your skill folder, allowing you to import the PerplexityClient directly into your custom agents.
Use Cases
This skill is ideal for tasks requiring high-fidelity information retrieval:
- Market Research: Analyzing current trends in stock performance or industry shifts.
- Technical Documentation: Investigating the latest updates to software libraries or frameworks.
- Comparative Analysis: Evaluating multiple viewpoints or model responses to complex ethical or scientific questions.
- Fact Checking: Verifying claims against current web sources to minimize hallucinations.
- Deep Reasoning: Performing multi-step research that requires synthesizing findings from diverse online sources.
Example Prompts
- "Perform a deep research analysis on the current state of AI-driven cybersecurity tools and summarize the top three trends for 2025."
- "Compare the performance and reasoning capabilities of GPT-5.2 and Claude 3.5 Sonnet regarding their ability to solve complex legal logic puzzles."
- "Search for the latest public announcements regarding renewable energy policy changes in the European Union and explain their potential impact on manufacturing costs."
Tips & Limitations
- Model Selection: Use the default
openai/gpt-5.2for maximum quality. Switch togoogle/gemini-2.0-flashfor high-volume, low-latency needs to save on costs. - Reasoning Effort: Always set
reasoning_efforttohighfor research tasks to ensure the agent takes the time to synthesize information rather than just returning search snippets. - Cost Awareness: Always check the
costfield returned in your response object to avoid unexpected API bills. - Limitations: The skill is dependent on live internet access and the availability of the Perplexity API. Ensure your network allows calls to the Perplexity endpoint.
Metadata
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Find the right skillPaste this into your clawhub.json to enable this plugin.
{
"plugins": {
"official-hushenglang-perplexity-research": {
"enabled": true,
"auto_update": true
}
}
}Tags(AI)
Flags: network-access, external-api