tavily-2
AI-optimized web search using Tavily Search API. Use when you need comprehensive web research, current events lookup, domain-specific search, or AI-generated answer summaries. Tavily is optimized for LLM consumption with clean structured results, answer generation, and raw content extraction. Best for research tasks, news queries, fact-checking, and gathering authoritative sources.
What this skill does
# Tavily AI Search
## Overview
Tavily is a search engine specifically optimized for Large Language Models and AI applications. Unlike traditional search APIs, Tavily provides AI-ready results with optional answer generation, clean content extraction, and domain filtering capabilities.
**Key capabilities:**
- AI-generated answer summaries from search results
- Clean, structured results optimized for LLM processing
- Fast (`basic`) and comprehensive (`advanced`) search modes
- Domain filtering (include/exclude specific sources)
- News-focused search for current events
- Image search with relevant visual content
- Raw content extraction for deeper analysis
## Architecture
```mermaid
graph TB
A[User Query] --> B{Search Mode}
B -->|basic| C[Fast Search<br/>1-2s response]
B -->|advanced| D[Comprehensive Search<br/>5-10s response]
C --> E[Tavily API]
D --> E
E --> F{Topic Filter}
F -->|general| G[Broad Web Search]
F -->|news| H[News Sources<br/>Last 7 days]
G --> I[Domain Filtering]
H --> I
I --> J{Include Domains?}
J -->|yes| K[Filter to Specific Domains]
J -->|no| L{Exclude Domains?}
K --> M[Search Results]
L -->|yes| N[Remove Unwanted Domains]
L -->|no| M
N --> M
M --> O{Response Options}
O --> P[AI Answer<br/>Summary]
O --> Q[Structured Results<br/>Title, URL, Content, Score]
O --> R[Images<br/>if requested]
O --> S[Raw HTML Content<br/>if requested]
P --> T[Return to Agent]
Q --> T
R --> T
S --> T
style E fill:#4A90E2
style P fill:#7ED321
style Q fill:#7ED321
style R fill:#F5A623
style S fill:#F5A623
```
## Quick Start
### Basic Search
```bash
# Simple query with AI answer
scripts/tavily_search.py "What is quantum computing?"
# Multiple results
scripts/tavily_search.py "Python best practices" --max-results 10
```
### Advanced Search
```bash
# Comprehensive research mode
scripts/tavily_search.py "Climate change solutions" --depth advanced
# News-focused search
scripts/tavily_search.py "AI developments 2026" --topic news
```
### Domain Filtering
```bash
# Search only trusted domains
scripts/tavily_search.py "Python tutorials" \
--include-domains python.org docs.python.org realpython.com
# Exclude low-quality sources
scripts/tavily_search.py "How to code" \
--exclude-domains w3schools.com geeksforgeeks.org
```
### With Images
```bash
# Include relevant images
scripts/tavily_search.py "Eiffel Tower architecture" --images
```
## Search Modes
### Basic vs Advanced
| Mode | Speed | Coverage | Use Case |
|------|-------|----------|----------|
| **basic** | 1-2s | Good | Quick facts, simple queries |
| **advanced** | 5-10s | Excellent | Research, complex topics, comprehensive analysis |
**Decision tree:**
1. Need a quick fact or definition? → Use `basic`
2. Researching a complex topic? → Use `advanced`
3. Need multiple perspectives? → Use `advanced`
4. Time-sensitive query? → Use `basic`
### General vs News
| Topic | Time Range | Sources | Use Case |
|-------|------------|---------|----------|
| **general** | All time | Broad web | Evergreen content, tutorials, documentation |
| **news** | Last 7 days | News sites | Current events, recent developments, breaking news |
**Decision tree:**
1. Query contains "latest", "recent", "current", "today"? → Use `news`
2. Looking for historical or evergreen content? → Use `general`
3. Need up-to-date information? → Use `news`
## API Key Setup
### Option 1: Clawdbot Config (Recommended)
Add to your Clawdbot config:
```json
{
"skills": {
"entries": {
"tavily": {
"enabled": true,
"apiKey": "tvly-YOUR_API_KEY_HERE"
}
}
}
}
```
Access in scripts via Clawdbot's config system.
### Option 2: Environment Variable
```bash
export TAVILY_API_KEY="tvly-YOUR_API_KEY_HERE"
```
Add to `~/.clawdbot/.env` or your shell profile.
### Getting an API Key
1. Visit https://tavily.com
2. Sign up for an account
3. Navigate to your dashboard
4. Generate an API key (starts with `tvly-`)
5. Note your plan's rate limits and credit allocation
## Common Use Cases
### 1. Research & Fact-Finding
```bash
# Comprehensive research with answer
scripts/tavily_search.py "Explain quantum entanglement" --depth advanced
# Multiple authoritative sources
scripts/tavily_search.py "Best practices for REST API design" \
--max-results 10 \
--include-domains github.com microsoft.com google.com
```
### 2. Current Events
```bash
# Latest news
scripts/tavily_search.py "AI policy updates" --topic news
# Recent developments in a field
scripts/tavily_search.py "quantum computing breakthroughs" \
--topic news \
--depth advanced
```
### 3. Domain-Specific Research
```bash
# Academic sources only
scripts/tavily_search.py "machine learning algorithms" \
--include-domains arxiv.org scholar.google.com ieee.org
# Technical documentation
scripts/tavily_search.py "React hooks guide" \
--include-domains react.dev
```
### 4. Visual Research
```bash
# Gather visual references
scripts/tavily_search.py "modern web design trends" \
--images \
--max-results 10
```
### 5. Content Extraction
```bash
# Get raw HTML content for deeper analysis
scripts/tavily_search.py "Python async/await" \
--raw-content \
--max-results 5
```
## Response Handling
### AI Answer
The AI-generated answer provides a concise summary synthesized from search results:
```python
{
"answer": "Quantum computing is a type of computing that uses quantum-mechanical phenomena..."
}
```
**Use when:**
- Need a quick summary
- Want synthesized information from multiple sources
- Looking for a direct answer to a question
**Skip when** (`--no-answer`):
- Only need source URLs
- Want to form your own synthesis
- Conserving API credits
### Structured Results
Each result includes:
- `title`: Page title
- `url`: Source URL
- `content`: Extracted text snippet
- `score`: Relevance score (0-1)
- `raw_content`: Full HTML (if `--raw-content` enabled)
### Images
When `--images` is enabled, returns URLs of relevant images found during search.
## Best Practices
### 1. Choose the Right Search Depth
- Start with `basic` for most queries (faster, cheaper)
- Escalate to `advanced` only when:
- Initial results are insufficient
- Topic is complex or nuanced
- Need comprehensive coverage
### 2. Use Domain Filtering Strategically
**Include domains for:**
- Academic research (`.edu` domains)
- Official documentation (official project sites)
- Trusted news sources
- Known authoritative sources
**Exclude domains for:**
- Known low-quality content farms
- Irrelevant content types (Pinterest for non-visual queries)
- Sites with paywalls or access restrictions
### 3. Optimize for Cost
- Use `basic` depth as default
- Limit `max_results` to what you'll actually use
- Disable `include_raw_content` unless needed
- Cache results locally for repeated queries
### 4. Handle Errors Gracefully
The script provides helpful error messages:
```bash
# Missing API key
Error: Tavily API key required
Setup: Set TAVILY_API_KEY environment variable or pass --api-key
# Package not installed
Error: tavily-python package not installed
To install: pip install tavily-python
```
## Integration Patterns
### Programmatic Usage
```python
from tavily_search import search
result = search(
query="What is machine learning?",
api_key="tvly-...",
search_depth="advanced",
max_results=10
)
if result.get("success"):
print(result["answer"])
for item in result["results"]:
print(f"{item['title']}: {item['url']}")
```
### JSON Output for Parsing
```bash
scripts/tavily_search.py "Python tutorials" --json > results.json
```
### Chaining with Other Tools
```bash
# Search and extract content
scripts/tavily_search.py "React documentation" --json | \
jq -r '.results[].url' | \
xargs -I {} curl -s {}
```
## Comparison with Other Search APIs
**vs Brave Search:**
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