Agent skill

perplexity

Web search and research using Perplexity AI. Use when user says "search", "find", "look up", "ask", "research", or "what's the latest" for generic queries. NOT for library/framework docs (use Context7) or workspace questions.

Stars 23,776
Forks 2,298

Install this agent skill to your Project

npx add-skill https://github.com/davila7/claude-code-templates/tree/main/cli-tool/components/skills/ai-research/perplexity

SKILL.md

Perplexity Tools

Use ONLY when user says "search", "find", "look up", "ask", "research", or "what's the latest" for generic queries. NOT for library/framework docs (use Context7), gt CLI (use Graphite MCP), or workspace questions (use Nx MCP).

Quick Reference

Which Perplexity tool?

  • Need search results/URLs? → Perplexity Search
  • Need conversational answer? → Perplexity Ask
  • Need deep research? → Researcher agent (/research <topic>)

NOT Perplexity - use these instead:

  • Library/framework docs → Context7 MCP
  • Graphite gt CLI → Graphite MCP
  • THIS workspace → Nx MCP
  • Specific URL → URL Crawler

Perplexity Search

When to use:

  • Generic searches, finding resources
  • Current best practices, recent information
  • Tutorial/blog post discovery
  • User says "search for...", "find...", "look up..."

Default parameters (ALWAYS USE):

typescript
mcp__perplexity__perplexity_search({
  query: "your search query",
  max_results: 3,           // Default is 10 - too many!
  max_tokens_per_page: 512  // Reduce per-result content
})

When to increase limits: Only if:

  • User explicitly needs comprehensive results
  • Initial search found nothing useful
  • Complex topic needs multiple sources
typescript
// Increased limits (use sparingly)
mcp__perplexity__perplexity_search({
  query: "complex topic",
  max_results: 5,
  max_tokens_per_page: 1024
})

Perplexity Ask

When to use:

  • Need conversational explanation, not search results
  • Synthesize information from web
  • Explain concepts with current context

Usage:

typescript
mcp__perplexity__perplexity_ask({
  messages: [
    {
      role: "user",
      content: "Explain how postgres advisory locks work"
    }
  ]
})

NOT for:

  • Library documentation (use Context7)
  • Deep multi-source research (use researcher agent)

Prohibited Tool

NEVER use: mcp__perplexity__perplexity_research

Use instead: Researcher agent (/research <topic>)

  • Token cost: 30-50k tokens
  • Provides multi-source synthesis with citations
  • Use sparingly for complex questions only

Tool Selection Chain

Priority order:

  1. Context7 MCP - Library/framework docs
  2. Graphite MCP - Any gt CLI mention
  3. Nx MCP - THIS workspace questions
  4. Perplexity Search - Generic searches
  5. Perplexity Ask - Conversational answers
  6. Researcher agent - Deep multi-source research
  7. WebSearch - Last resort (after Perplexity exhausted)

Examples

✅ CORRECT - Use Perplexity Search:

  • "Find postgres migration best practices"
  • "Search for React testing tutorials"
  • "Look up latest trends in microservices"

✅ CORRECT - Use Perplexity Ask:

  • "Explain how postgres advisory locks work"
  • "What are the trade-offs of microservices?"

❌ WRONG - Use Context7 instead:

  • "Search for React hooks documentation" → Context7 MCP
  • "Find Next.js routing docs" → Context7 MCP
  • "Look up Temporal workflow API" → Context7 MCP

❌ WRONG - Use Graphite MCP instead:

  • "Search for gt stack commands" → Graphite MCP
  • "Find gt branch workflow" → Graphite MCP

❌ WRONG - Use Nx MCP instead:

  • "Search for build config" (in THIS workspace) → Nx MCP
  • "Find project dependencies" (in THIS workspace) → Nx MCP

Key Points

  • Default to limited results - avoid context bloat
  • Library docs = Context7 - ALWAYS try Context7 first
  • "gt" = Graphite MCP - ANY "gt" mention uses Graphite
  • Deep research = /research - NOT perplexity_research tool
  • Fallback chain - Search → Ask → WebSearch (last resort)

Expand your agent's capabilities with these related and highly-rated skills.

davila7/claude-code-templates

verl-rl-training

Provides guidance for training LLMs with reinforcement learning using verl (Volcano Engine RL). Use when implementing RLHF, GRPO, PPO, or other RL algorithms for LLM post-training at scale with flexible infrastructure backends.

23,776 2,298
Explore
davila7/claude-code-templates

openrlhf-training

High-performance RLHF framework with Ray+vLLM acceleration. Use for PPO, GRPO, RLOO, DPO training of large models (7B-70B+). Built on Ray, vLLM, ZeRO-3. 2× faster than DeepSpeedChat with distributed architecture and GPU resource sharing.

23,776 2,298
Explore
davila7/claude-code-templates

gguf-quantization

GGUF format and llama.cpp quantization for efficient CPU/GPU inference. Use when deploying models on consumer hardware, Apple Silicon, or when needing flexible quantization from 2-8 bit without GPU requirements.

23,776 2,298
Explore
davila7/claude-code-templates

Claude Code Guide

Master guide for using Claude Code effectively. Includes configuration templates, prompting strategies "Thinking" keywords, debugging techniques, and best practices for interacting with the agent.

23,776 2,298
Explore
davila7/claude-code-templates

qdrant-vector-search

High-performance vector similarity search engine for RAG and semantic search. Use when building production RAG systems requiring fast nearest neighbor search, hybrid search with filtering, or scalable vector storage with Rust-powered performance.

23,776 2,298
Explore
davila7/claude-code-templates

behavioral-modes

AI operational modes (brainstorm, implement, debug, review, teach, ship, orchestrate). Use to adapt behavior based on task type.

23,776 2,298
Explore

Didn't find tool you were looking for?

Be as detailed as possible for better results