Requirements
- Target platform
- OpenClaw
- Install method
- Manual import
- Extraction
- Extract archive
- Prerequisites
- OpenClaw
- Primary doc
- SKILL.md
Tencent SkillHub Β· AI Featured
Tavily Web Search
Provides concise, highly relevant search results tuned for AI agents via the Tavily API.
skill openclawclawhub Free
Provides concise, highly relevant search results tuned for AI agents via the Tavily API.
β¬ 72,000 downloads β
320 stars Featured by editorial review
Install for OpenClaw
Quick setup
- Download the package from Yavira.
- Extract the archive and review SKILL.md first.
- Import or place the package into your OpenClaw setup.
Package facts
- Download mode
- Yavira redirect
- Package format
- ZIP package
- Source platform
- Tencent SkillHub
- What's included
- SKILL.md, references/api-reference.md, scripts/tavily_search.py
Validation
- Use the Yavira download entry.
- Review SKILL.md after the package is downloaded.
- Confirm the extracted package contains the expected setup assets.
Install with your agent
Agent handoff
Hand the extracted package to your coding agent with a concrete install brief instead of figuring it out manually.
- Download the package from Yavira.
- Extract it into a folder your agent can access.
- Paste one of the prompts below and point your agent at the extracted folder.
New install
I downloaded a skill package from Yavira. Read SKILL.md from the extracted folder and install it by following the included instructions. Tell me what you changed and call out any manual steps you could not complete.
Upgrade existing
I downloaded an updated skill package from Yavira. Read SKILL.md from the extracted folder, compare it with my current installation, and upgrade it while preserving any custom configuration unless the package docs explicitly say otherwise. Summarize what changed and any follow-up checks I should run.
Trust & source
Release facts
- Source
- Tencent SkillHub
- Verification
- Indexed source record
- Version
- 1.0.0
Provenance
- Publisher
- bert-builder
- Source page
- View original listing
- Canonical URL
- Open canonical page
Documentation
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
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
Basic Search
# 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
# 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
# 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
# Include relevant images scripts/tavily_search.py "Eiffel Tower architecture" --images
Basic vs Advanced
ModeSpeedCoverageUse Casebasic1-2sGoodQuick facts, simple queriesadvanced5-10sExcellentResearch, complex topics, comprehensive analysis Decision tree: Need a quick fact or definition? β Use basic Researching a complex topic? β Use advanced Need multiple perspectives? β Use advanced Time-sensitive query? β Use basic
General vs News
TopicTime RangeSourcesUse CasegeneralAll timeBroad webEvergreen content, tutorials, documentationnewsLast 7 daysNews sitesCurrent events, recent developments, breaking news Decision tree: Query contains "latest", "recent", "current", "today"? β Use news Looking for historical or evergreen content? β Use general Need up-to-date information? β Use news
Option 1: Clawdbot Config (Recommended)
Add to your Clawdbot config: { "skills": { "entries": { "tavily": { "enabled": true, "apiKey": "tvly-YOUR_API_KEY_HERE" } } } } Access in scripts via Clawdbot's config system.
Option 2: Environment Variable
export TAVILY_API_KEY="tvly-YOUR_API_KEY_HERE" Add to ~/.clawdbot/.env or your shell profile.
Getting an API Key
Visit https://tavily.com Sign up for an account Navigate to your dashboard Generate an API key (starts with tvly-) Note your plan's rate limits and credit allocation
1. Research & Fact-Finding
# 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
# 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
# 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
# Gather visual references scripts/tavily_search.py "modern web design trends" \ --images \ --max-results 10
5. Content Extraction
# Get raw HTML content for deeper analysis scripts/tavily_search.py "Python async/await" \ --raw-content \ --max-results 5
AI Answer
The AI-generated answer provides a concise summary synthesized from search results: { "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.
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: # 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
Programmatic Usage
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
scripts/tavily_search.py "Python tutorials" --json > results.json
Chaining with Other Tools
# 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: β AI answer generation β Raw content extraction β Better domain filtering β Slower than Brave β Costs credits vs Perplexity: β More control over sources β Raw content available β Dedicated news mode β Similar answer quality β Similar speed vs Google Custom Search: β LLM-optimized results β Answer generation β Simpler API β Smaller index β Similar cost structure
Script Won't Run
# Make executable chmod +x scripts/tavily_search.py # Check Python version (requires 3.6+) python3 --version # Install dependencies pip install tavily-python
API Key Issues
# Verify API key format (should start with tvly-) echo $TAVILY_API_KEY # Test with explicit key scripts/tavily_search.py "test" --api-key "tvly-..."
Rate Limit Errors
Check your plan's credit allocation at https://tavily.com Reduce max_results to conserve credits Use basic depth instead of advanced Implement local caching for repeated queries
Resources
See api-reference.md for: Complete API parameter documentation Response format specifications Error handling details Cost and rate limit information Advanced usage examples
Dependencies
Python 3.6+ tavily-python package (install: pip install tavily-python) Valid Tavily API key
Credits & Attribution
Tavily API: https://tavily.com Python SDK: https://github.com/tavily-ai/tavily-python Documentation: https://docs.tavily.com
Category context
Agent frameworks, memory systems, reasoning layers, and model-native orchestration.
Source: Tencent SkillHub
Largest current source with strong distribution and engagement signals.
Package contents
Included in package
2 Docs1 Scripts
- SKILL.md
- references/api-reference.md
- scripts/tavily_search.py