Perplexity Search Skill

Perplexity Search Skill

Search the web using Perplexity's Sonar AI models. Unlike traditional search engines that return links, Perplexity provides synthesized AI-generated answers with inline citations and source URLs.

How It Works

This skill provides instructions and context. To execute searches, connect the Perplexity Search node to the agent's input-tools handle.

perplexity_search Tool

Ask a question and get an AI-synthesized answer with citations.

Schema Fields

Node Parameters

Additional options configured on the node:

Response Format

{
  "query": "What are the latest developments in quantum computing?",
  "answer": "Recent developments in quantum computing include several significant breakthroughs. **Google's Willow chip** demonstrated error correction below the threshold needed for reliable quantum computation [1]. **IBM** released its 1,121-qubit Condor processor [2], while **Microsoft** announced a new topological qubit approach [3].\n\nKey areas of progress:\n- Error correction advances\n- Increased qubit counts\n- New materials and architectures\n- Growing commercial applications",
  "citations": [
    "https://blog.google/technology/research/quantum-computing-willow/",
    "https://research.ibm.com/blog/condor-processor",
    "https://azure.microsoft.com/en-us/blog/quantum/"
  ],
  "results": [
    {"url": "https://blog.google/technology/research/quantum-computing-willow/"},
    {"url": "https://research.ibm.com/blog/condor-processor"},
    {"url": "https://azure.microsoft.com/en-us/blog/quantum/"}
  ],
  "model": "sonar",
  "provider": "perplexity",
  "images": [],
  "related_questions": [
    "What is quantum error correction?",
    "How many qubits does a useful quantum computer need?"
  ]
}

Examples

Research question:

{
  "query": "What are the latest developments in quantum computing?"
}

Technical question:

{
  "query": "How does React Server Components work in Next.js 15?"
}

Current events:

{
  "query": "What happened at the latest AI safety summit?"
}

Comparison:

{
  "query": "Compare PostgreSQL vs MySQL for large-scale applications"
}

When to Use Perplexity Search

• Research questions - Get synthesized, well-structured answers with citations
• Technical explanations - Detailed answers about how things work
• Current events analysis - AI-summarized coverage of recent events
• Comparison queries - Side-by-side analysis of options
• Complex topics - Multi-faceted questions that benefit from AI synthesis
• When you need citations - Every claim backed by source URLs

When NOT to Use Perplexity Search

• Simple factual lookups - Use Brave or Serper for quick facts
• Image search - Use Serper with searchType "images"
• Local business search - Use Serper with searchType "places"
• High-volume queries - Perplexity costs more per query ($0.005)
• Simple calculations - Use the calculator tool

Key Differences from Traditional Search

Answer Format

The answer field contains rich markdown:

• Bold text for emphasis
• Numbered citations [1][2] referencing the citations array
• Bullet points and lists for structured information
• Headers for organized sections
• Code blocks for technical content

API Details

• API: POST https://api.perplexity.ai/chat/completions
• Auth: Authorization: Bearer header
• Models: sonar (fast, default), sonar-pro (deeper research)
• Timeout: 60 seconds (AI generation takes longer than traditional search)
• Pricing: ~$0.005 per request

Setup Requirements

1. Connect this skill to the agent's input-skill handle
2. Connect the Perplexity Search node to the agent's input-tools handle
3. Add your Perplexity API key in Credentials > Search