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Tencent SkillHub ยท Developer Tools
Nimble Web Search
Real-time web intelligence powered by Nimble Search API. Perform intelligent web searches with 8 specialized focus modes (general, coding, news, academic, shopping, social, geo, location). This skill provides real-time search results when you need to search the web, find current information, discover URLs, research topics, or gather up-to-date data. Use when: searching for information, finding recent news, looking up academic papers, searching for coding examples, finding shopping results, discovering social media posts, researching topics, or getting latest real-time data.
skill openclawclawhub Free
Real-time web intelligence powered by Nimble Search API. Perform intelligent web searches with 8 specialized focus modes (general, coding, news, academic, shopping, social, geo, location). This skill provides real-time search results when you need to search the web, find current information, discover URLs, research topics, or gather up-to-date data. Use when: searching for information, finding recent news, looking up academic papers, searching for coding examples, finding shopping results, discovering social media posts, researching topics, or getting latest real-time data.
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- Tencent SkillHub
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- SKILL.md, scripts/validate-query.sh, scripts/search.sh, examples/basic-search.md, examples/competitive-analysis.md, examples/deep-research.md
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- Tencent SkillHub
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- 0.1.0
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Documentation
Nimble Web Search
Real-time web intelligence using Nimble Search API with specialized focus modes and AI-powered result synthesis.
Prerequisites
Nimble API Key Required - Get your key at https://www.nimbleway.com/
Configuration
Set the NIMBLE_API_KEY environment variable using your platform's method: Claude Code: // ~/.claude/settings.json { "env": { "NIMBLE_API_KEY": "your-api-key-here" } } VS Code/GitHub Copilot: Add to .github/skills/ directory in your repository Or use GitHub Actions secrets for the copilot environment Shell/Terminal: export NIMBLE_API_KEY="your-api-key-here" Any Platform: The skill checks for the NIMBLE_API_KEY environment variable regardless of how you set it.
API Key Validation
IMPORTANT: Before making any search request, verify the API key is configured: # Check if API key is set if [ -z "$NIMBLE_API_KEY" ]; then echo "โ Error: NIMBLE_API_KEY not configured" echo "" echo "Get your API key: https://www.nimbleway.com/" echo "" echo "Configure using your platform's method:" echo "- Claude Code: Add to ~/.claude/settings.json" echo "- GitHub Copilot: Use GitHub Actions secrets" echo "- Shell: export NIMBLE_API_KEY=\"your-key\"" echo "" echo "Do NOT fall back to other search tools - guide the user to configure first." exit 1 fi
Overview
Nimble Search provides real-time web intelligence with 8 specialized focus modes optimized for different types of queries. Get instant access to current web data with AI-powered answer generation, deep content extraction, URL discovery, and smart filtering by domain and date. IMPORTANT: Always Specify These Parameters When using this skill, always explicitly set the following parameters in your requests: deep_search: Default to false for 5-10x faster responses Use false (FAST MODE - 1-3 seconds): For 95% of use cases - URL discovery, research, comparisons, answer generation Use true (DEEP MODE - 5-15 seconds): Only when you specifically need full page content extracted for archiving or detailed analysis focus: Default to "general" for broad searches Change to specific mode (coding, news, academic, shopping, social, geo, location) for targeted results max_results: Default to 10 - Balanced speed and coverage Performance Awareness: By explicitly setting deep_search: false, you're choosing fast mode and should expect results in 1-3 seconds. If you set deep_search: true, expect 5-15 seconds response time.
Quick Start
Use the wrapper script for the simplest experience: # ALWAYS specify deep_search explicitly ./scripts/search.sh '{ "query": "React hooks", "deep_search": false }' The script automatically handles authentication, tracking headers, and output formatting.
When to Use Each Mode
Use deep_search: false (FAST MODE - 1-3 seconds) - Default for 95% of cases: โ Finding URLs and discovering resources โ Research and topic exploration โ Answer generation and summaries โ Product comparisons โ News monitoring โ Any time you DON'T need full article text Use deep_search: true (DEEP MODE - 5-15 seconds) - Only when specifically needed: ๐ Archiving full article content ๐ Extracting complete documentation ๐ Building text datasets ๐ Processing full page content for analysis Decision Rule: If you're not sure, use deep_search: false. You can always re-run with true if needed.
Focus Modes
Choose the appropriate focus mode based on your query type: general - Default mode for broad web searches coding - Real-time access to technical documentation, code examples, programming resources news - Real-time news articles, current events, breaking stories academic - Research papers, scholarly articles, academic resources shopping - Real-time product searches, e-commerce results, price comparisons social - Real-time social media posts, discussions, trending community content geo - Location-based searches, geographic information location - Local business searches, place-specific queries
Search Features
LLM Answer Generation Request AI-generated answers synthesized from search results Powered by Claude for high-quality summaries Include citations to source URLs Best for: Research questions, topic overviews, comparative analysis URL Discovery Extract 1-20 most relevant URLs for a query Useful for building reading lists and reference collections Returns URLs with titles and descriptions Best for: Resource gathering, link building, research preparation Deep Content Extraction Default (Recommended): deep_search=false - Fastest response, returns titles, descriptions, and URLs Optional: deep_search=true - Slower, extracts full page content Important: Most use cases work perfectly with deep_search=false (the default) Available formats when deep_search=true: markdown, plain_text, simplified_html Only enable deep search for: Detailed content analysis, archiving, or comprehensive text extraction needs Domain Filtering Include specific domains (e.g., github.com, stackoverflow.com) Exclude domains to remove unwanted sources Combine multiple domains for focused searches Best for: Targeted research, brand monitoring, competitive analysis Time Filtering Recommended: Use time_range for real-time recency filtering (hour, day, week, month, year) Alternative: Use start_date/end_date for precise date ranges (YYYY-MM-DD) Note: time_range and date filters are mutually exclusive Best for: Real-time news monitoring, recent developments, temporal analysis
Usage Patterns
All examples below use the ./scripts/search.sh wrapper for simplicity. For raw API usage, see the API Integration section.
Basic Search
Quick search in fast mode (ALWAYS specify deep_search explicitly): ./scripts/search.sh '{ "query": "React Server Components tutorial", "deep_search": false }' For technical content, specify coding focus (still fast mode): ./scripts/search.sh '{ "query": "React Server Components tutorial", "focus": "coding", "deep_search": false }'
Research with AI Summary
Get synthesized insights from multiple sources (fast mode works great with answer generation): ./scripts/search.sh '{ "query": "impact of AI on software development 2026", "deep_search": false, "include_answer": true }'
Domain-Specific Search
Target specific authoritative sources (fast mode): ./scripts/search.sh '{ "query": "async await patterns", "focus": "coding", "deep_search": false, "include_domains": ["github.com", "stackoverflow.com", "dev.to"], "max_results": 8 }'
Real-Time News Monitoring
Track current events and breaking news as they happen (fast mode): ./scripts/search.sh '{ "query": "latest developments in quantum computing", "focus": "news", "deep_search": false, "time_range": "week", "max_results": 15, "include_answer": true }'
Academic Research - Fast Mode (Recommended)
Find and synthesize scholarly content using fast mode: ./scripts/search.sh '{ "query": "machine learning interpretability methods", "focus": "academic", "deep_search": false, "max_results": 20, "include_answer": true }' When to use deep mode: Only use "deep_search": true if you need full paper content extracted for archiving: ./scripts/search.sh '{ "query": "machine learning interpretability methods", "focus": "academic", "deep_search": true, "max_results": 5, "output_format": "markdown" }' Note: Deep mode is 5-15x slower. Use only when specifically needed.
Real-Time Shopping Research
Compare products and current prices (fast mode): ./scripts/search.sh '{ "query": "best mechanical keyboards for programming", "focus": "shopping", "deep_search": false, "max_results": 10, "include_answer": true }'
When to Use Parallel Searches
Run multiple real-time searches in parallel when: Comparing perspectives: Search the same topic across different focus modes Multi-faceted research: Investigate different aspects of a topic simultaneously Competitive analysis: Search multiple domains or competitors at once Real-time monitoring: Track multiple topics or keywords concurrently Cross-validation: Verify information across different source types in real-time
Implementation Methods
Method 1: Background Processes (Recommended) Run multiple searches concurrently using the wrapper script: # Start multiple searches in parallel ./scripts/search.sh '{"query": "React", "focus": "coding"}' > react_coding.json & ./scripts/search.sh '{"query": "React", "focus": "news"}' > react_news.json & ./scripts/search.sh '{"query": "React", "focus": "academic"}' > react_academic.json & # Wait for all to complete wait # Combine results jq -s '.' react_*.json > combined_results.json Method 2: Loop with xargs (Controlled Parallelism) Process multiple queries with rate limiting: # Create queries file cat > queries.txt <<EOF {"query": "AI frameworks", "focus": "coding"} {"query": "AI regulation", "focus": "news"} {"query": "AI research", "focus": "academic"} EOF # Run with max 3 parallel processes cat queries.txt | xargs -n1 -P3 -I{} ./scripts/search.sh '{}' Method 3: Focus Mode Comparison Search the same query across different focus modes: QUERY="artificial intelligence trends" for focus in "general" "coding" "news" "academic"; do ( ./scripts/search.sh "{\"query\": \"$QUERY\", \"focus\": \"$focus\"}" \ > "${focus}_results.json" ) & done wait echo "All searches complete!"
Best Practices for Parallel Execution
Rate Limiting: Limit parallel requests to 3-5 to avoid overwhelming the API Use xargs -P3 to set maximum concurrent requests Check your API tier limits before increasing parallelism Error Handling: Capture and handle failures gracefully ./scripts/search.sh '{"query": "test"}' || echo "Search failed" >> errors.log Result Aggregation: Combine results after all searches complete # Wait for all searches wait # Merge JSON results jq -s 'map(.results) | flatten' result*.json > combined.json Progress Tracking: Monitor completion status echo "Running 5 parallel searches..." for i in {1..5}; do ./scripts/search.sh "{\"query\": \"query$i\"}" > "result$i.json" & done wait echo "All searches complete!"
Example: Multi-Perspective Research
#!/bin/bash # Research a topic across multiple focus modes simultaneously QUERY="artificial intelligence code generation" OUTPUT_DIR="./search_results" mkdir -p "$OUTPUT_DIR" # Run searches in parallel across different focus modes for focus in "general" "coding" "news" "academic"; do ( ./scripts/search.sh "{ \"query\": \"$QUERY\", \"focus\": \"$focus\", \"max_results\": 10 }" > "$OUTPUT_DIR/${focus}_results.json" ) & done # Wait for all searches to complete wait # Aggregate and analyze results jq -s '{ general: .[0].results, coding: .[1].results, news: .[2].results, academic: .[3].results }' "$OUTPUT_DIR"/*.json > "$OUTPUT_DIR/combined_analysis.json" echo "โ Multi-perspective search complete"
Performance Considerations
Optimal Parallelism: 3-5 concurrent requests balances speed and API limits Memory Usage: Each parallel request consumes memory; monitor for large result sets Network Bandwidth: Parallel requests can saturate bandwidth on slow connections API Costs: More parallel requests = faster API quota consumption
When NOT to Use Parallel Searches
Single, focused query with one clear answer Sequential research where each search informs the next API quota is limited or expensive Results need to be processed before next search Simple URL collection that doesn't require multiple perspectives
API Integration
Note: For most use cases, use the ./scripts/search.sh wrapper script shown in Usage Patterns. The raw API examples below are for advanced users who need direct API access or custom integration.
Required Configuration
Before making any API request, always validate the API key is configured: # Validate API key is set if [ -z "$NIMBLE_API_KEY" ]; then echo "โ Nimble API key not configured." echo "Get your key at https://www.nimbleway.com/" echo "" echo "Set NIMBLE_API_KEY environment variable using your platform's method." exit 1 fi The skill requires the NIMBLE_API_KEY environment variable. See Prerequisites for platform-specific setup instructions. Get your API key at: https://www.nimbleway.com/
API Endpoint
POST https://nimble-retriever.webit.live/search
Request Format
{ "query": "search query string", // REQUIRED "focus": "general", // OPTIONAL: default "general" | coding|news|academic|shopping|social|geo|location "max_results": 10, // OPTIONAL: default 10 (range: 1-100) "include_answer": false, // OPTIONAL: default false "deep_search": false, // OPTIONAL: default false (RECOMMENDED: keep false for speed) "output_format": "markdown", // OPTIONAL: default "markdown" | plain_text|simplified_html "include_domains": ["domain1.com"], // OPTIONAL: default [] (no filter) "exclude_domains": ["domain3.com"], // OPTIONAL: default [] (no filter) "time_range": "week", // OPTIONAL: hour|day|week|month|year "start_date": "2026-01-01", // OPTIONAL: Use time_range OR start_date/end_date (not both) "end_date": "2026-12-31" // OPTIONAL } Key Defaults: focus: "general" - Change to specific mode for targeted results deep_search: false - Keep false unless you need full page content max_results: 10 - Balanced speed and coverage
Response Format
{ "results": [ { "url": "https://example.com/page", "title": "Page Title", "description": "Page description", "content": "Full page content (if deep_search=true)", "published_date": "2026-01-15" } ], "include_answer": "AI-generated summary (if include_answer=true)", "urls": ["url1", "url2", "url3"], "total_results": 10 }
Focus Mode Selection
Use coding for: Programming questions Technical documentation Code examples and tutorials API references Framework guides Use news for: Real-time current events Breaking stories as they happen Recent announcements Trending topics Time-sensitive information Use academic for: Research papers Scholarly articles Scientific studies Academic journals Citations and references Use shopping for: Product searches Price comparisons E-commerce research Product reviews Buying guides Use social for: Real-time social media monitoring Live community discussions Current user-generated content Trending hashtags and topics Real-time public sentiment Use geo for: Geographic information Regional data Maps and locations Area-specific queries Use location for: Local business searches Place-specific information Nearby services Regional recommendations
Result Limits
Quick searches: 5-10 results for fast overview Comprehensive research: 15-20 results for depth Answer generation: 10-15 results for balanced synthesis URL collection: 20 results for comprehensive resource list
When to Use LLM Answers
โ Use LLM answers when: You need a synthesized overview of a topic Comparing multiple sources or approaches Summarizing recent developments Answering specific questions Creating research summaries โ Skip LLM answers when: You just need a list of URLs Building a reference collection Speed is critical You want to analyze sources manually Original source text is needed
Content Extraction
Default (Recommended): deep_search=false The default setting works for 95% of use cases: โ Fastest response times โ Returns titles, descriptions, URLs โ Works perfectly with include_answer=true โ Sufficient for research, comparisons, and URL discovery Only use deep_search=true when you specifically need: Full page content extraction Archiving complete articles Processing full text for analysis Building comprehensive datasets Performance impact: deep_search=false: ~1-3 seconds deep_search=true: ~5-15 seconds (significantly slower)
Common Issues
Authentication Failed Verify NIMBLE_API_KEY is set correctly Check API key is active at nimbleway.com Ensure key has search API access Rate Limiting Reduce max_results Add delays between requests Check your plan limits Consider upgrading API tier No Results Try different focus mode Broaden search query Remove domain filters Adjust date filters Timeout Errors Reduce max_results Disable deep content extraction Simplify query Try again after brief delay
Performance Tips
Use Defaults: Keep deep_search=false (default) for 5-10x faster responses Start Simple: Begin with just {"query": "..."} - defaults work great Choose Right Focus: Proper focus mode dramatically improves relevance (default: "general") Optimize Result Count: Default of 10 results balances speed and coverage Domain Filtering: Pre-filter sources for faster, more relevant results Avoid Deep Search: Only enable deep_search=true when you truly need full content Batch Queries: Group related searches to minimize API calls Cache Results: Store results locally when appropriate
Integration Examples
See the examples/ directory for detailed integration patterns: basic-search.md - Simple search implementation deep-research.md - Multi-step research workflow competitive-analysis.md - Domain-specific research pattern See references/ directory for detailed documentation: focus-modes.md - Complete focus mode guide search-strategies.md - Advanced search patterns api-reference.md - Full API documentation
search.sh - Main Search Wrapper
The recommended way to use the Nimble Search API: ./scripts/search.sh '{"query": "your search", "focus": "coding"}' Features: Automatic authentication with $NIMBLE_API_KEY Platform detection (claude-code, github-copilot, vscode, cli) Request tracking headers for analytics JSON validation and error handling Formatted output with jq Usage: # Basic search ./scripts/search.sh '{"query": "React hooks"}' # With all options ./scripts/search.sh '{ "query": "AI frameworks", "focus": "coding", "max_results": 15, "include_answer": true, "include_domains": ["github.com"] }'
validate-query.sh - API Configuration Test
Test your API configuration and connectivity: ./scripts/validate-query.sh "test query" general This verifies: API key is configured Endpoint is accessible Response format is correct Focus mode is supported
Category context
Code helpers, APIs, CLIs, browser automation, testing, and developer operations.
Source: Tencent SkillHub
Largest current source with strong distribution and engagement signals.
Package contents
Included in package
4 Docs2 Scripts
- SKILL.md
- examples/basic-search.md
- examples/competitive-analysis.md
- examples/deep-research.md
- scripts/search.sh
- scripts/validate-query.sh