Nimble Web Search

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 "❌ 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:

• ✅ Finding URLs and discovering resources
• ✅ Research and topic exploration
• ✅ Answer generation and summaries
• ✅ Product comparisons
• ✅ News monitoring
• ✅ Any time you DON'T need full article text

Use deep_search: true (DEEP MODE - 5-15 seconds) - Only when specifically needed:

• 📄 Archiving full article content
• 📄 Extracting complete documentation
• 📄 Building text datasets
• 📄 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.

Core Capabilities

Focus Modes

Choose the appropriate focus mode based on your query type:

1. general - Default mode for broad web searches
2. coding - Real-time access to technical documentation, code examples, programming resources
3. news - Real-time news articles, current events, breaking stories
4. academic - Research papers, scholarly articles, academic resources
5. shopping - Real-time product searches, e-commerce results, price comparisons
6. social - Real-time social media posts, discussions, trending community content
7. geo - Location-based searches, geographic information
8. 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
}'

Parallel Search Strategies

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

1. 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

2. Error Handling: Capture and handle failures gracefully

   ./scripts/search.sh '{"query": "test"}' || echo "Search failed" >> errors.log

3. 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

4. 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 "✓ 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