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Perplexity AI Search

AI software team for Claude Code - 138 agents, 295 skills, 73 hooks. Self-learning, multi-agent swarm, autonomous skill evolution.

Installable skillMITBy vibeevalUpdated Oct 30, 2026
INTENDED FOROpenClawInstall in a listed agent.

instructions.md

---
name: perplexity-search-939e7aca7609
description: AI-powered web search, research, and reasoning via Perplexity
allowed-tools: [Bash, Read]
---

# Perplexity AI Search

Web search with AI-powered answers, deep research, and chain-of-thought reasoning.

## When to Use

- Direct web search for ranked results (no AI synthesis)
- AI-synthesized research with citations
- Chain-of-thought reasoning for complex decisions
- Deep comprehensive research on topics

## Models (2025)

| Model | Purpose |
|-------|---------|
| `sonar` | Lightweight search with grounding |
| `sonar-pro` | Advanced search for complex queries |
| `sonar-reasoning-pro` | Chain of thought reasoning |
| `sonar-deep-research` | Expert-level exhaustive research |

## Usage

### Quick question (AI answer)
```bash
uv run python scripts/mcp/perplexity_search.py \
    --ask "What is the latest version of Python?"
```

### Direct web search (ranked results, no AI)
```bash
uv run python scripts/mcp/perplexity_search.py \
    --search "SQLite graph database patterns" \
    --max-results 5 \
    --recency week
```

### AI-synthesized research
```bash
uv run python scripts/mcp/perplexity_search.py \
    --research "compare FastAPI vs Django for microservices"
```

### Chain-of-thought reasoning
```bash
uv run python scripts/mcp/perplexity_search.py \
    --reason "should I use Neo4j or SQLite for small graph under 10k nodes?"
```

### Deep comprehensive research
```bash
uv run python scripts/mcp/perplexity_search.py \
    --deep "state of AI agent observability 2025"
```

## Parameters

| Parameter | Description |
|-----------|-------------|
| `--ask` | Quick question with AI answer (sonar) |
| `--search` | Direct web search - ranked results without AI synthesis |
| `--research` | AI-synthesized research (sonar-pro) |
| `--reason` | Chain-of-thought reasoning (sonar-reasoning-pro) |
| `--deep` | Deep comprehensive research (sonar-deep-research) |

### Search-specific options
| Parameter | Description |
|-----------|-------------|
| `--max-results N` | Number of results (1-20, default: 10) |
| `--recency` | Filter: `day`, `week`, `month`, `year` |
| `--domains` | Limit to specific domains |

## Mode Selection Guide

| Need | Use | Why |
|------|-----|-----|
| Quick fact | `--ask` | Fast, lightweight |
| Find sources | `--search` | Raw results, no AI overhead |
| Synthesized answer | `--research` | AI combines multiple sources |
| Complex decision | `--reason` | Chain-of-thought analysis |
| Comprehensive report | `--deep` | Exhaustive multi-source research |

## Examples

```bash
# Find recent sources on a topic
uv run python scripts/mcp/perplexity_search.py \
    --search "OpenTelemetry AI agent tracing" \
    --recency month --max-results 5

# Get AI synthesis
uv run python scripts/mcp/perplexity_search.py \
    --research "best practices for AI agent logging 2025"

# Make a decision
uv run python scripts/mcp/perplexity_search.py \
    --reason "microservices vs monolith for startup MVP"

# Deep dive
uv run python scripts/mcp/perplexity_search.py \
    --deep "comprehensive guide to building feedback loops for autonomous agents"
```

## API Key Required

Requires `PERPLEXITY_API_KEY` in environment or `~/.claude/.env`.

Platform guidance

Imported from the listed AgentSkill.sh category. Complete supplied package files and notices are retained. Required external tools and credentials are not installed. No bundled code was executed during import. Individual agent task behavior has not been tested.