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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.\n\nTags: ai:1.0.0, latest:1.0.0, search:1.0.0, web:1.0.0\n\nVersion history:\n\nv1.0.0 | 2026-01-24T20:53:10.264Z | user\n\nInitial release: AI-optimized web search with basic/advanced modes, domain filtering, news search, image search, and AI answer generation.\n\nArchive index:\n\nArchive v1.0.0: 4 files, 9094 bytes\n\nFiles: references/api-reference.md (5218b), scripts/tavily_search.py (7328b), SKILL.md (9986b), _meta.json (125b)\n\nFile v1.0.0:SKILL.md\n\n---\nname: tavily\ndescription: 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.\n---\n\n# Tavily AI Search\n\n## Overview\n\nTavily 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.\n\n**Key capabilities:**\n- AI-generated answer summaries from search results\n- Clean, structured results optimized for LLM processing\n- Fast (`basic`) and comprehensive (`advanced`) search modes\n- Domain filtering (include/exclude specific sources)\n- News-focused search for current events\n- Image search with relevant visual content\n- Raw content extraction for deeper analysis\n\n## Architecture\n\n```mermaid\ngraph TB\n A[User Query] --> B{Search Mode}\n B -->|basic| C[Fast Search
1-2s response]\n B -->|advanced| D[Comprehensive Search
5-10s response]\n \n C --> E[Tavily API]\n D --> E\n \n E --> F{Topic Filter}\n F -->|general| G[Broad Web Search]\n F -->|news| H[News Sources
Last 7 days]\n \n G --> I[Domain Filtering]\n H --> I\n \n I --> J{Include Domains?}\n J -->|yes| K[Filter to Specific Domains]\n J -->|no| L{Exclude Domains?}\n K --> M[Search Results]\n L -->|yes| N[Remove Unwanted Domains]\n L -->|no| M\n N --> M\n \n M --> O{Response Options}\n O --> P[AI Answer
Summary]\n O --> Q[Structured Results
Title, URL, Content, Score]\n O --> R[Images
if requested]\n O --> S[Raw HTML Content
if requested]\n \n P --> T[Return to Agent]\n Q --> T\n R --> T\n S --> T\n \n style E fill:#4A90E2\n style P fill:#7ED321\n style Q fill:#7ED321\n style R fill:#F5A623\n style S fill:#F5A623\n```\n\n## Quick Start\n\n### Basic Search\n\n```bash\n# Simple query with AI answer\nscripts/tavily_search.py \"What is quantum computing?\"\n\n# Multiple results\nscripts/tavily_search.py \"Python best practices\" --max-results 10\n```\n\n### Advanced Search\n\n```bash\n# Comprehensive research mode\nscripts/tavily_search.py \"Climate change solutions\" --depth advanced\n\n# News-focused search\nscripts/tavily_search.py \"AI developments 2026\" --topic news\n```\n\n### Domain Filtering\n\n```bash\n# Search only trusted domains\nscripts/tavily_search.py \"Python tutorials\" \\\n --include-domains python.org docs.python.org realpython.com\n\n# Exclude low-quality sources\nscripts/tavily_search.py \"How to code\" \\\n --exclude-domains w3schools.com geeksforgeeks.org\n```\n\n### With Images\n\n```bash\n# Include relevant images\nscripts/tavily_search.py \"Eiffel Tower architecture\" --images\n```\n\n## Search Modes\n\n### Basic vs Advanced\n\n| Mode | Speed | Coverage | Use Case |\n|------|-------|----------|----------|\n| **basic** | 1-2s | Good | Quick facts, simple queries |\n| **advanced** | 5-10s | Excellent | Research, complex topics, comprehensive analysis |\n\n**Decision tree:**\n1. Need a quick fact or definition? → Use `basic`\n2. Researching a complex topic? → Use `advanced`\n3. Need multiple perspectives? → Use `advanced`\n4. Time-sensitive query? → Use `basic`\n\n### General vs News\n\n| Topic | Time Range | Sources | Use Case |\n|-------|------------|---------|----------|\n| **general** | All time | Broad web | Evergreen content, tutorials, documentation |\n| **news** | Last 7 days | News sites | Current events, recent developments, breaking news |\n\n**Decision tree:**\n1. Query contains \"latest\", \"recent\", \"current\", \"today\"? → Use `news`\n2. Looking for historical or evergreen content? → Use `general`\n3. Need up-to-date information? → Use `news`\n\n## API Key Setup\n\n### Option 1: Clawdbot Config (Recommended)\n\nAdd to your Clawdbot config:\n\n```json\n{\n \"skills\": {\n \"entries\": {\n \"tavily\": {\n \"enabled\": true,\n \"apiKey\": \"tvly-YOUR_API_KEY_HERE\"\n }\n }\n }\n}\n```\n\nAccess in scripts via Clawdbot's config system.\n\n### Option 2: Environment Variable\n\n```bash\nexport TAVILY_API_KEY=\"tvly-YOUR_API_KEY_HERE\"\n```\n\nAdd to `~/.clawdbot/.env` or your shell profile.\n\n### Getting an API Key\n\n1. Visit https://tavily.com\n2. Sign up for an account\n3. Navigate to your dashboard\n4. Generate an API key (starts with `tvly-`)\n5. Note your plan's rate limits and credit allocation\n\n## Common Use Cases\n\n### 1. Research & Fact-Finding\n\n```bash\n# Comprehensive research with answer\nscripts/tavily_search.py \"Explain quantum entanglement\" --depth advanced\n\n# Multiple authoritative sources\nscripts/tavily_search.py \"Best practices for REST API design\" \\\n --max-results 10 \\\n --include-domains github.com microsoft.com google.com\n```\n\n### 2. Current Events\n\n```bash\n# Latest news\nscripts/tavily_search.py \"AI policy updates\" --topic news\n\n# Recent developments in a field\nscripts/tavily_search.py \"quantum computing breakthroughs\" \\\n --topic news \\\n --depth advanced\n```\n\n### 3. Domain-Specific Research\n\n```bash\n# Academic sources only\nscripts/tavily_search.py \"machine learning algorithms\" \\\n --include-domains arxiv.org scholar.google.com ieee.org\n\n# Technical documentation\nscripts/tavily_search.py \"React hooks guide\" \\\n --include-domains react.dev\n```\n\n### 4. Visual Research\n\n```bash\n# Gather visual references\nscripts/tavily_search.py \"modern web design trends\" \\\n --images \\\n --max-results 10\n```\n\n### 5. Content Extraction\n\n```bash\n# Get raw HTML content for deeper analysis\nscripts/tavily_search.py \"Python async/await\" \\\n --raw-content \\\n --max-results 5\n```\n\n## Response Handling\n\n### AI Answer\n\nThe AI-generated answer provides a concise summary synthesized from search results:\n\n```python\n{\n \"answer\": \"Quantum computing is a type of computing that uses quantum-mechanical phenomena...\"\n}\n```\n\n**Use when:**\n- Need a quick summary\n- Want synthesized information from multiple sources\n- Looking for a direct answer to a question\n\n**Skip when** (`--no-answer`):\n- Only need source URLs\n- Want to form your own synthesis\n- Conserving API credits\n\n### Structured Results\n\nEach result includes:\n- `title`: Page title\n- `url`: Source URL\n- `content`: Extracted text snippet\n- `score`: Relevance score (0-1)\n- `raw_content`: Full HTML (if `--raw-content` enabled)\n\n### Images\n\nWhen `--images` is enabled, returns URLs of relevant images found during search.\n\n## Best Practices\n\n### 1. Choose the Right Search Depth\n\n- Start with `basic` for most queries (faster, cheaper)\n- Escalate to `advanced` only when:\n - Initial results are insufficient\n - Topic is complex or nuanced\n - Need comprehensive coverage\n\n### 2. Use Domain Filtering Strategically\n\n**Include domains for:**\n- Academic research (`.edu` domains)\n- Official documentation (official project sites)\n- Trusted news sources\n- Known authoritative sources\n\n**Exclude domains for:**\n- Known low-quality content farms\n- Irrelevant content types (Pinterest for non-visual queries)\n- Sites with paywalls or access restrictions\n\n### 3. Optimize for Cost\n\n- Use `basic` depth as default\n- Limit `max_results` to what you'll actually use\n- Disable `include_raw_content` unless needed\n- Cache results locally for repeated queries\n\n### 4. Handle Errors Gracefully\n\nThe script provides helpful error messages:\n\n```bash\n# Missing API key\nError: Tavily API key required\nSetup: Set TAVILY_API_KEY environment variable or pass --api-key\n\n# Package not installed\nError: tavily-python package not installed\nTo install: pip install tavily-python\n```\n\n## Integration Patterns\n\n### Programmatic Usage\n\n```python\nfrom tavily_search import search\n\nresult = search(\n query=\"What is machine learning?\",\n api_key=\"tvly-...\",\n search_depth=\"advanced\",\n max_results=10\n)\n\nif result.get(\"success\"):\n print(result[\"answer\"])\n for item in result[\"results\"]:\n print(f\"{item['title']}: {item['url']}\")\n```\n\n### JSON Output for Parsing\n\n```bash\nscripts/tavily_search.py \"Python tutorials\" --json > results.json\n```\n\n### Chaining with Other Tools\n\n```bash\n# Search and extract content\nscripts/tavily_search.py \"React documentation\" --json | \\\n jq -r '.results[].url' | \\\n xargs -I {} curl -s {}\n```\n\n## Comparison with Other Search APIs\n\n**vs Brave Search:**\n- ✅ AI answer generation\n- ✅ Raw content extraction\n- ✅ Better domain filtering\n- ❌ Slower than Brave\n- ❌ Costs credits\n\n**vs Perplexity:**\n- ✅ More control over sources\n- ✅ Raw content available\n- ✅ Dedicated news mode\n- ≈ Similar answer quality\n- ≈ Similar speed\n\n**vs Google Custom Search:**\n- ✅ LLM-optimized results\n- ✅ Answer generation\n- ✅ Simpler API\n- ❌ Smaller index\n- ≈ Similar cost structure\n\n## Troubleshooting\n\n### Script Won't Run\n\n```bash\n# Make executable\nchmod +x scripts/tavily_search.py\n\n# Check Python version (requires 3.6+)\npython3 --version\n\n# Install dependencies\npip install tavily-python\n```\n\n### API Key Issues\n\n```bash\n# Verify API key format (should start with tvly-)\necho $TAVILY_API_KEY\n\n# Test with explicit key\nscripts/tavily_search.py \"test\" --api-key \"tvly-...\"\n```\n\n### Rate Limit Errors\n\n- Check your plan's credit allocation at https://tavily.com\n- Reduce `max_results` to conserve credits\n- Use `basic` depth instead of `advanced`\n- Implement local caching for repeated queries\n\n## Resources\n\nSee [api-reference.md](references/api-reference.md) for:\n- Complete API parameter documentation\n- Response format specifications\n- Error handling details\n- Cost and rate limit information\n- Advanced usage examples\n\n## Dependencies\n\n- Python 3.6+\n- `tavily-python` package (install: `pip install tavily-python`)\n- Valid Tavily API key\n\n## Credits & Attribution\n\n- Tavily API: https://tavily.com\n- Python SDK: https://github.com/tavily-ai/tavily-python\n- Documentation: https://docs.tavily.com\n\nFile v1.0.0:_meta.json\n\n{\n \"ownerId\": \"kn7dak197zp1gy590j60ct8r7h7zte7t\",\n \"slug\": \"tavily\",\n \"version\": \"1.0.0\",\n \"publishedAt\": 1769287990264\n}\n\nFile v1.0.0:references/api-reference.md\n\n# Tavily API Reference\n\n## Overview\n\nTavily is a search engine optimized for Large Language Models (LLMs) and AI applications. It provides:\n\n- **AI-optimized results**: Results specifically formatted for LLM consumption\n- **Answer generation**: Optional AI-generated summaries from search results\n- **Raw content extraction**: Clean, parsed HTML content from sources\n- **Domain filtering**: Include or exclude specific domains\n- **Image search**: Relevant images for visual context\n- **Topic specialization**: General or news-focused search\n\n## API Key Setup\n\n1. Visit https://tavily.com and sign up\n2. Generate an API key from your dashboard\n3. Store the key securely:\n - **Recommended**: Add to Clawdbot config under `skills.entries.tavily.apiKey`\n - **Alternative**: Set `TAVILY_API_KEY` environment variable\n\n## Search Parameters\n\n### Required\n\n- `query` (string): The search query\n\n### Optional\n\n| Parameter | Type | Default | Description |\n|-----------|------|---------|-------------|\n| `search_depth` | string | `\"basic\"` | `\"basic\"` (fast, ~1-2s) or `\"advanced\"` (comprehensive, ~5-10s) |\n| `topic` | string | `\"general\"` | `\"general\"` or `\"news\"` (current events, last 7 days) |\n| `max_results` | int | 5 | Number of results (1-10) |\n| `include_answer` | bool | true | Include AI-generated answer summary |\n| `include_raw_content` | bool | false | Include cleaned HTML content of sources |\n| `include_images` | bool | false | Include relevant images |\n| `include_domains` | list[str] | null | Only search these domains |\n| `exclude_domains` | list[str] | null | Exclude these domains |\n\n## Response Format\n\n```json\n{\n \"success\": true,\n \"query\": \"What is quantum computing?\",\n \"answer\": \"Quantum computing is a type of computing that uses...\",\n \"results\": [\n {\n \"title\": \"Quantum Computing Explained\",\n \"url\": \"https://example.com/quantum\",\n \"content\": \"Quantum computing leverages...\",\n \"score\": 0.95,\n \"raw_content\": null\n }\n ],\n \"images\": [\"https://example.com/image.jpg\"],\n \"response_time\": \"1.67\",\n \"usage\": {\n \"credits\": 1\n }\n}\n```\n\n## Use Cases & Best Practices\n\n### When to Use Tavily\n\n1. **Research tasks**: Comprehensive information gathering\n2. **Current events**: News-focused queries with `topic=\"news\"`\n3. **Domain-specific search**: Use `include_domains` for trusted sources\n4. **Visual content**: Enable `include_images` for visual context\n5. **LLM consumption**: Results are pre-formatted for AI processing\n\n### Search Depth Comparison\n\n| Depth | Speed | Results Quality | Use Case |\n|-------|-------|-----------------|----------|\n| `basic` | 1-2s | Good | Quick lookups, simple facts |\n| `advanced` | 5-10s | Excellent | Research, complex topics, comprehensive analysis |\n\n**Recommendation**: Start with `basic`, use `advanced` for research tasks.\n\n### Domain Filtering\n\n**Include domains** (allowlist):\n```python\ninclude_domains=[\"python.org\", \"github.com\", \"stackoverflow.com\"]\n```\nOnly search these specific domains - useful for trusted sources.\n\n**Exclude domains** (denylist):\n```python\nexclude_domains=[\"pinterest.com\", \"quora.com\"]\n```\nRemove unwanted or low-quality sources.\n\n### Topic Selection\n\n**General** (`topic=\"general\"`):\n- Default mode\n- Broader web search\n- Historical and evergreen content\n- Best for most queries\n\n**News** (`topic=\"news\"`):\n- Last 7 days only\n- News-focused sources\n- Current events and developments\n- Best for \"latest\", \"recent\", \"current\" queries\n\n## Cost & Rate Limits\n\n- **Credits**: Each search consumes credits (1 credit for basic search)\n- **Free tier**: Check https://tavily.com/pricing for current limits\n- **Rate limits**: Varies by plan tier\n\n## Error Handling\n\nCommon errors:\n\n1. **Missing API key**\n ```json\n {\n \"error\": \"Tavily API key required\",\n \"setup_instructions\": \"Set TAVILY_API_KEY environment variable\"\n }\n ```\n\n2. **Package not installed**\n ```json\n {\n \"error\": \"tavily-python package not installed\",\n \"install_command\": \"pip install tavily-python\"\n }\n ```\n\n3. **Invalid API key**\n ```json\n {\n \"error\": \"Invalid API key\"\n }\n ```\n\n4. **Rate limit exceeded**\n ```json\n {\n \"error\": \"Rate limit exceeded\"\n }\n ```\n\n## Python SDK\n\nThe skill uses the official `tavily-python` package:\n\n```python\nfrom tavily import TavilyClient\n\nclient = TavilyClient(api_key=\"tvly-...\")\nresponse = client.search(\n query=\"What is AI?\",\n search_depth=\"advanced\",\n max_results=10\n)\n```\n\nInstall: `pip install tavily-python`\n\n## Comparison with Other Search APIs\n\n| Feature | Tavily | Brave Search | Perplexity |\n|---------|--------|--------------|------------|\n| AI Answer | ✅ Yes | ❌ No | ✅ Yes |\n| Raw Content | ✅ Yes | ❌ No | ❌ No |\n| Domain Filtering | ✅ Yes | Limited | ❌ No |\n| Image Search | ✅ Yes | ✅ Yes | ❌ No |\n| News Mode | ✅ Yes | ✅ Yes | ✅ Yes |\n| LLM Optimized | ✅ Yes | ❌ No | ✅ Yes |\n| Speed | Medium | Fast | Medium |\n| Free Tier | ✅ Yes | ✅ Yes | Limited |\n\n## Additional Resources\n\n- Official Docs: https://docs.tavily.com\n- Python SDK: https://github.com/tavily-ai/tavily-python\n- API Reference: https://docs.tavily.com/documentation/api-reference\n- Pricing: https://tavily.com/pricing","readmeExcerpt":"Skill: Tavily AI Search Owner: bert-builder Summary: 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 autho","codeSnippets":[],"executableExamples":[{"language":"mermaid","snippet":"graph TB\n A[User Query] --> B{Search Mode}\n B -->|basic| C[Fast Search
1-2s response]\n B -->|advanced| D[Comprehensive Search
5-10s response]\n \n C --> E[Tavily API]\n D --> E\n \n E --> F{Topic Filter}\n F -->|general| G[Broad Web Search]\n F -->|news| H[News Sources
Last 7 days]\n \n G --> I[Domain Filtering]\n H --> I\n \n I --> J{Include Domains?}\n J -->|yes| K[Filter to Specific Domains]\n J -->|no| L{Exclude Domains?}\n K --> M[Search Results]\n L -->|yes| N[Remove Unwanted Domains]\n L -->|no| M\n N --> M\n \n M --> O{Response Options}\n O --> P[AI Answer
Summary]\n O --> Q[Structured Results
Title, URL, Content, Score]\n O --> R[Images
if requested]\n O --> S[Raw HTML Content
if requested]\n \n P --> T[Return to Agent]\n Q --> T\n R --> T\n S --> T\n \n style E fill:#4A90E2\n style P fill:#7ED321\n style Q fill:#7ED321\n style R fill:#F5A623\n style S fill:#F5A623"},{"language":"bash","snippet":"# Simple query with AI answer\nscripts/tavily_search.py \"What is quantum computing?\"\n\n# Multiple results\nscripts/tavily_search.py \"Python best practices\" --max-results 10"},{"language":"bash","snippet":"# Comprehensive research mode\nscripts/tavily_search.py \"Climate change solutions\" --depth advanced\n\n# News-focused search\nscripts/tavily_search.py \"AI developments 2026\" --topic news"},{"language":"bash","snippet":"# Search only trusted domains\nscripts/tavily_search.py \"Python tutorials\" \\\n --include-domains python.org docs.python.org realpython.com\n\n# Exclude low-quality sources\nscripts/tavily_search.py \"How to code\" \\\n --exclude-domains w3schools.com geeksforgeeks.org"},{"language":"bash","snippet":"# Include relevant images\nscripts/tavily_search.py \"Eiffel Tower architecture\" --images"},{"language":"json","snippet":"{\n \"skills\": {\n \"entries\": {\n \"tavily\": {\n \"enabled\": true,\n \"apiKey\": \"tvly-YOUR_API_KEY_HERE\"\n }\n }\n }\n}"}],"parameters":null,"dependencies":[],"permissions":[],"extractedFiles":[{"path":"SKILL.md","content":"---\nname: tavily\ndescription: 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.\n---\n\n# Tavily AI Search\n\n## Overview\n\nTavily 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.\n\n**Key capabilities:**\n- AI-generated answer summaries from search results\n- Clean, structured results optimized for LLM processing\n- Fast (`basic`) and comprehensive (`advanced`) search modes\n- Domain filtering (include/exclude specific sources)\n- News-focused search for current events\n- Image search with relevant visual content\n- Raw content extraction for deeper analysis\n\n## Architecture\n\n```mermaid\ngraph TB\n A[User Query] --> B{Search Mode}\n B -->|basic| C[Fast Search
1-2s response]\n B -->|advanced| D[Comprehensive Search
5-10s response]\n \n C --> E[Tavily API]\n D --> E\n \n E --> F{Topic Filter}\n F -->|general| G[Broad Web Search]\n F -->|news| H[News Sources
Last 7 days]\n \n G --> I[Domain Filtering]\n H --> I\n \n I --> J{Include Domains?}\n J -->|yes| K[Filter to Specific Domains]\n J -->|no| L{Exclude Domains?}\n K --> M[Search Results]\n L -->|yes| N[Remove Unwanted Domains]\n L -->|no| M\n N --> M\n \n M --> O{Response Options}\n O --> P[AI Answer
Summary]\n O --> Q[Structured Results
Title, URL, Content, Score]\n O --> R[Images
if requested]\n O --> S[Raw HTML Content
if requested]\n \n P --> T[Return to Agent]\n Q --> T\n R --> T\n S --> T\n \n style E fill:#4A90E2\n style P fill:#7ED321\n style Q fill:#7ED321\n style R fill:#F5A623\n style S fill:#F5A623\n```\n\n## Quick Start\n\n### Basic Search\n\n```bash\n# Simple query with AI answer\nscripts/tavily_search.py \"What is quantum computing?\"\n\n# Multiple results\nscripts/tavily_search.py \"Python best practices\" --max-results 10\n```\n\n### Advanced Search\n\n```bash\n# Comprehensive research mode\nscripts/tavily_search.py \"Climate change solutions\" --depth advanced\n\n# News-focused search\nscripts/tavily_search.py \"AI developments 2026\" --topic news\n```\n\n### Domain Filtering\n\n```bash\n# Search only trusted domains\nscripts/tavily_search.py \"Python tutorials\" \\\n --include-domains python.org docs.python.org realpython.com\n\n# Exclude low-quality sources\nscripts/tavily_search.py \"How to code\" \\\n --exclude-domains w3schools.com geeksforgeeks.org\n```\n\n### With Images\n\n```bash\n# Include relevant images\nscripts/tavily_search.py \"Eiffel Tower architecture\" --images\n```\n\n## Search Modes\n\n### Basic vs Advanced"},{"path":"_meta.json","content":"{\n \"ownerId\": \"kn7dak197zp1gy590j60ct8r7h7zte7t\",\n \"slug\": \"tavily\",\n \"version\": \"1.0.0\",\n \"publishedAt\": 1769287990264\n}"},{"path":"references/api-reference.md","content":"# Tavily API Reference\n\n## Overview\n\nTavily is a search engine optimized for Large Language Models (LLMs) and AI applications. It provides:\n\n- **AI-optimized results**: Results specifically formatted for LLM consumption\n- **Answer generation**: Optional AI-generated summaries from search results\n- **Raw content extraction**: Clean, parsed HTML content from sources\n- **Domain filtering**: Include or exclude specific domains\n- **Image search**: Relevant images for visual context\n- **Topic specialization**: General or news-focused search\n\n## API Key Setup\n\n1. Visit https://tavily.com and sign up\n2. Generate an API key from your dashboard\n3. Store the key securely:\n - **Recommended**: Add to Clawdbot config under `skills.entries.tavily.apiKey`\n - **Alternative**: Set `TAVILY_API_KEY` environment variable\n\n## Search Parameters\n\n### Required\n\n- `query` (string): The search query\n\n### Optional\n\n| Parameter | Type | Default | Description |\n|-----------|------|---------|-------------|\n| `search_depth` | string | `\"basic\"` | `\"basic\"` (fast, ~1-2s) or `\"advanced\"` (comprehensive, ~5-10s) |\n| `topic` | string | `\"general\"` | `\"general\"` or `\"news\"` (current events, last 7 days) |\n| `max_results` | int | 5 | Number of results (1-10) |\n| `include_answer` | bool | true | Include AI-generated answer summary |\n| `include_raw_content` | bool | false | Include cleaned HTML content of sources |\n| `include_images` | bool | false | Include relevant images |\n| `include_domains` | list[str] | null | Only search these domains |\n| `exclude_domains` | list[str] | null | Exclude these domains |\n\n## Response Format\n\n```json\n{\n \"success\": true,\n \"query\": \"What is quantum computing?\",\n \"answer\": \"Quantum computing is a type of computing that uses...\",\n \"results\": [\n {\n \"title\": \"Quantum Computing Explained\",\n \"url\": \"https://example.com/quantum\",\n \"content\": \"Quantum computing leverages...\",\n \"score\": 0.95,\n \"raw_content\": null\n }\n ],\n \"images\": [\"https://example.com/image.jpg\"],\n \"response_time\": \"1.67\",\n \"usage\": {\n \"credits\": 1\n }\n}\n```\n\n## Use Cases & Best Practices\n\n### When to Use Tavily\n\n1. **Research tasks**: Comprehensive information gathering\n2. **Current events**: News-focused queries with `topic=\"news\"`\n3. **Domain-specific search**: Use `include_domains` for trusted sources\n4. **Visual content**: Enable `include_images` for visual context\n5. **LLM consumption**: Results are pre-formatted for AI processing\n\n### Search Depth Comparison\n\n| Depth | Speed | Results Quality | Use Case |\n|-------|-------|-----------------|----------|\n| `basic` | 1-2s | Good | Quick lookups, simple facts |\n| `advanced` | 5-10s | Excellent | Research, complex topics, comprehensive analysis |\n\n**Recommendation**: Start with `basic`, use `advanced` for research tasks.\n\n### Domain Filtering\n\n**Include domains** (allowlist):\n```python\ninclude_domains=[\"python.org\", \"github.com\", \"stackoverflow.com\"]\n```\nOnly search these specific domains - useful"}],"languages":[],"docsSourceLabel":"CLAWHUB","editorialOverview":null,"editorialQuality":{"score":100,"threshold":65,"status":"thin","wordCount":897,"uniquenessScore":43,"reasons":["uniqueness-below-45"]}},"media":{"evidence":{"source":"no-media","verified":false,"confidence":"low","updatedAt":"2026-05-16T06:12:10.068Z","emptyReason":"No screenshots, media assets, or demo links are available."},"primaryImageUrl":null,"mediaAssetCount":0,"assets":[],"demoUrl":null},"ownerResources":{"evidence":{"source":"unclaimed","verified":false,"confidence":"low","updatedAt":"2026-05-16T06:12:10.068Z","emptyReason":"This page has not been claimed by the agent owner."},"hasCustomPage":false,"customPageUpdatedAt":null,"customLinks":[],"structuredLinks":{"docsUrl":null,"demoUrl":null,"supportUrl":null,"pricingUrl":null,"statusUrl":null},"customPage":null},"relatedAgents":{"evidence":{"source":"protocol-neighbors","verified":false,"confidence":"medium","updatedAt":"2026-10-09T19:53:29.987Z","emptyReason":null},"items":[{"id":"8ebccd8e-3863-4187-8355-c3f14e1f9edf","entityType":"agent","canonicalPath":"/agent/iofficeai-aionui","slug":"iofficeai-aionui","name":"AionUi","description":"Free, local, open-source 24/7 Cowork app and OpenClaw for Gemini CLI, Claude Code, Codex, OpenCode, Qwen Code, Goose CLI, Auggie, and more | 🌟 Star if you like it!","url":"https://github.com/iOfficeAI/AionUi","homepage":"https://www.aionui.com","source":"GITHUB_REPOS","protocols":["MCP","OPENCLAW"],"capabilities":[],"safetyScore":100,"overallRank":70,"updatedAt":"2026-10-09T19:11:12.944Z","createdAt":"2026-02-25T03:38:16.584Z","downloads":null},{"id":"b917f68a-ebff-438e-84f8-3f4b2494c0bc","entityType":"agent","canonicalPath":"/agent/activepieces-activepieces","slug":"activepieces-activepieces","name":"activepieces","description":"AI Agents & MCPs & AI Workflow Automation • (~400 MCP servers for AI agents) • AI Automation / AI Agent with MCPs • AI Workflows & AI Agents • MCPs for AI Agents","url":"https://github.com/activepieces/activepieces","homepage":"https://www.activepieces.com","source":"GITHUB_REPOS","protocols":["OPENCLAW"],"capabilities":[],"safetyScore":100,"overallRank":70,"updatedAt":"2026-04-15T02:22:12.426Z","createdAt":"2026-02-25T03:38:12.412Z","downloads":null},{"id":"5cb26759-3a39-483f-94cf-276a98c13bb8","entityType":"agent","canonicalPath":"/agent/cherryhq-cherry-studio","slug":"cherryhq-cherry-studio","name":"cherry-studio","description":"AI productivity studio with smart chat, autonomous agents, and 300+ assistants. 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