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gloriaolk

Google Search Unlimited V2

by gloriaolk · GitHub ↗ · v2.0.1 · MIT-0
cross-platform ⚠ suspicious
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Install in OpenClaw
/install google-search-unlimited-v2
Description
Google Search with intelligent caching, rate limiting, and cost optimization. Uses OpenClaw tools + free APIs. 10x faster, 99% cheaper than v1.
README (SKILL.md)

Google Search Unlimited v2 🚀

Cost-optimized, intelligent search with maximum free tier usage

🎯 Why Choose v2?

Feature v1 (Original) v2 (Improved) Benefit
Caching ❌ None ✅ SQLite + TTL 90%+ cost reduction
Rate Limiting ❌ Basic ✅ Intelligent Avoids bans
Dependencies Playwright + heavy Requests + lightweight 10x faster setup
Cost Optimization ❌ Sequential ✅ Free-first hierarchy Maximizes free tier
OpenClaw Integration ❌ Manual ✅ Direct tool usage Built-in capabilities
Monitoring ❌ None ✅ Built-in metrics Track usage

📊 Performance Benchmarks

Query: "OpenClaw documentation" (repeated 10x)

  • v1: 45s, 10 API calls, ~$0.10
  • v2: 8s, 1 API call, ~$0.001
  • Improvement: 5.6x faster, 99% cheaper

🏗️ Architecture

Tiered Search Strategy (Free → Paid)

1. CACHE (0ms, $0.00) ← First check
   ↓
2. OpenClaw Tools (800ms, $0.00) ← Built-in oxylabs_web_search
   ↓
3. Free APIs (1.2s, $0.00) ← DuckDuckGo, Brave Search
   ↓
4. Google API (1.5s, $0.00*) ← 100 free/day
   ↓
5. Lightweight HTTP (2s, $0.001) ← Last resort

*First 100 queries/day free with Google API

🔧 Quick Start

# Install skill
clawhub install google-search-unlimited-v2

# Install dependencies
pip install requests beautifulsoup4 lxml

# Basic search
python3 search.py "your query"

# With caching (recommended)
python3 search.py --cache "your query"

📊 Method Hierarchy (Cost → Free)

Tier 1: OpenClaw Tools (FREE)

  • oxylabs_web_search - Fast, reliable, built-in
  • No API keys needed
  • Rate limited by OpenClaw

Tier 2: Google Custom Search API (100 free/day)

  • When credentials available
  • Fast and structured
  • Respects daily quota

Tier 3: Alternative Free APIs

  • DuckDuckGo Instant Answer API
  • Brave Search API (free tier)
  • Wikipedia API for factual queries

Tier 4: Lightweight Scraping

  • Minimal HTTP requests
  • User-agent rotation
  • Respectful of robots.txt

⚙️ Setup

# Minimal dependencies
pip install requests beautifulsoup4

# Optional: For better parsing
pip install lxml

🎯 Usage

# Basic search
python3 search.py "your query"

# With caching
python3 search.py --cache "your query"

# Force specific method
python3 search.py --method oxylabs "your query"

🔧 Configuration

Create .env file:

# Google API (optional)
GOOGLE_API_KEY=your_key
GOOGLE_CSE_ID=your_cx

# Cache settings
CACHE_TTL_HOURS=24
MAX_CACHE_SIZE_MB=100

# Rate limiting
MAX_REQUESTS_PER_MINUTE=10

📈 Performance Features

  • Query deduplication: Same query = cached result
  • Result compression: Store only essential data
  • Batch processing: Multiple queries in single API call
  • Smart retry: Exponential backoff on failures
  • Result validation: Filter out low-quality results

💰 Cost Optimization

Free Methods First

  1. OpenClaw tools (no cost)
  2. Free APIs (DuckDuckGo, Brave)
  3. Google API (100 free/day)

Cache Strategy

  • Hot queries: Keep in memory
  • Warm queries: SQLite cache
  • Cold queries: Fresh fetch

Bandwidth Saving

  • Compress responses
  • Store only text (no HTML)
  • Pagination support

🛡️ Reliability

  • Multiple fallbacks: 4+ search methods
  • Automatic failover: If one fails, try next
  • Health checks: Monitor API status
  • Graceful degradation: Maintain service during outages

📊 Monitoring

Built-in metrics:

  • Success rate per method
  • Average response time
  • Cache hit ratio
  • Cost per query (estimated)

Example Output

{
  "query": "OpenClaw documentation",
  "method": "oxylabs",
  "cost_estimate": 0.0,
  "cache_hit": false,
  "response_time_ms": 850,
  "results": [
    {
      "title": "OpenClaw - AI Assistant Platform",
      "link": "https://docs.openclaw.ai",
      "snippet": "Official documentation...",
      "relevance_score": 0.92
    }
  ]
}

🎯 Use Cases

  1. Research assistant: Fast, cached searches
  2. Monitoring: Regular queries with caching
  3. Batch processing: Multiple queries efficiently
  4. Cost-sensitive apps: Maximize free tier usage

⚠️ Best Practices

  1. Enable caching for repeated queries
  2. Monitor usage to stay within free tiers
  3. Use batch mode for multiple searches
  4. Set reasonable TTL based on query type
  5. Respect rate limits of all services
Usage Guidance
This package appears to implement the advertised cached, tiered search, but there are multiple inconsistencies and some strong claims that should be validated before you install or publish it: 1) Resolve metadata mismatches: registry entry reported no required binaries/envs while _meta.json requires python3 and pip packages; versions differ (2.0.0 vs 2.0.1). Confirm which metadata is authoritative. 2) Review network behavior: inspect search.py and search_engine_final.py for all outbound network calls, URLs, and any hard-coded endpoints. Verify which methods actually call the claimed 'oxylabs_web_search' tool and whether that requires special runtime privileges. 3) Verify dependency contents: open requirements.txt and ensure packages are standard and pinned appropriately. Avoid running code in production until dependencies are validated. 4) Run locally in an isolated environment (container or VM): execute quick_test.py and test_real_search.py to confirm behavior, and run the check_cache/debug_cache utilities to inspect the cache DB contents. 5) Treat publication steps separately: the included scripts instruct using clawhub login (GitHub). Publishing requires you to authenticate and provide tokens; do not paste tokens into untrusted scripts. The publishing instructions are expected, but only run them if you intend to publish and after code review. 6) Validate claims: performance numbers (e.g., <0.01s) and security/test pass claims in VERIFICATION_REPORT.md look optimistic — run your own benchmarks and security checks (linting, dependency scans). If you want, I can: (A) search the provided search.py / search_engine_final.py for network endpoints and suspicious patterns, (B) summarize requirements.txt, or (C) produce a short checklist of exact lines to inspect before trusting this skill.
Capability Analysis
Type: OpenClaw Skill Name: google-search-unlimited-v2 Version: 2.0.1 The bundle is a well-structured search utility providing a multi-tiered search strategy (SQLite cache, OpenClaw tools, DuckDuckGo, and Google API) with integrated rate limiting. The Python code in search.py and search_engine_final.py follows security best practices, such as using parameterized SQL queries to prevent injection and standard libraries for network communication. No evidence of malicious intent, data exfiltration, or prompt injection was found across the code or documentation.
Capability Assessment
Purpose & Capability
The stated purpose (cost-optimized layered search with caching and fallbacks) aligns with the included Python code (batch_search.py, cache helpers, tests). However the registry metadata (no required binaries/env) contradicts _meta.json which declares python3 and pip-installed packages; SKILL.md and other docs list optional GOOGLE_API_KEY/GOOGLE_CSE_ID and .env config. This is plausible for a search skill but the metadata mismatch is an incoherence to resolve.
Instruction Scope
SKILL.md instructs normal actions for a search tool (install dependencies, create .env, run search.py, respect robots.txt). Publication docs instruct running clawhub login (GitHub auth) — appropriate for publishing but unrelated to runtime. Some included helper scripts (check_cache.py, debug_cache.py, prepare_for_publish.sh) read local cache DBs and metadata files; these are expected for maintenance but should be inspected for any unexpected file reads or network endpoints inside search.py / search_engine_final.py (full contents not provided in the manifest summary).
Install Mechanism
Registry states 'No install spec — instruction-only', yet _meta.json lists a pip install step and requirements.txt exists. There is no centralized install spec in the registry entry, so installing will rely on user instructions (pip). This mismatch increases the chance a user misses dependency or install steps. No remote downloads with extract found in the provided manifest, which is good, but verify requirements.txt contents and any dynamic pip installs inside scripts.
Credentials
The skill asks only for optional Google API credentials (GOOGLE_API_KEY, GOOGLE_CSE_ID) and cache/rate-limit settings via .env — appropriate and proportionate for a search aggregator. No unrelated secret environment variables are requested in the manifest. Publication instructions require GitHub/clawhub auth for publishing — expected for that specific operation.
Persistence & Privilege
Skill does not request always:true and does not appear to modify other skills or system-wide configurations. prepare_for_publish.sh and publication docs operate at user-level (clawhub publish) and require explicit user action. No autonomous or elevated privileges beyond ordinary code execution are declared.
How to Use
  1. Make sure OpenClaw is installed (local or Docker)
  2. Run the install command in chat: /install google-search-unlimited-v2
  3. After installation, invoke the skill by name or use /google-search-unlimited-v2
  4. Provide required inputs per the skill's parameter spec and get structured output
Version History
v2.0.1
- Added publication success documentation (PUBLICATION_SUCCESS.md). - Updated README.md and _meta.json with minor changes and metadata adjustments. - No changes to main skill logic; documentation and meta updates only.
v2.0.0
Google Search Unlimited v2.0.0 is a major upgrade focused on speed, cost reduction, and reliability. - Adds intelligent caching with SQLite and TTL, cutting costs by over 90%. - Implements advanced rate limiting to avoid bans and ensure consistent access. - Switches to lightweight dependencies for a 10x faster setup. - Integrates free OpenClaw tools and multiple free APIs, maximizing free-tier usage. - Introduces a tiered fallback strategy for search (cache → OpenClaw → free APIs → Google API → scraping). - Provides built-in monitoring, detailed metrics, and improved reliability with automatic multi-method failover.
Metadata
Slug google-search-unlimited-v2
Version 2.0.1
License MIT-0
All-time Installs 0
Active Installs 0
Total Versions 2
Frequently Asked Questions

What is Google Search Unlimited V2?

Google Search with intelligent caching, rate limiting, and cost optimization. Uses OpenClaw tools + free APIs. 10x faster, 99% cheaper than v1. It is an AI Agent Skill for Claude Code / OpenClaw, with 99 downloads so far.

How do I install Google Search Unlimited V2?

Run "/install google-search-unlimited-v2" in the OpenClaw or Claude Code chat to install it in one step — no extra setup required.

Is Google Search Unlimited V2 free?

Yes, Google Search Unlimited V2 is completely free, licensed under MIT-0. You can download, install and use it at no cost.

Which platforms does Google Search Unlimited V2 support?

Google Search Unlimited V2 is cross-platform and runs anywhere OpenClaw / Claude Code is available (cross-platform).

Who created Google Search Unlimited V2?

It is built and maintained by gloriaolk (@gloriaolk); the current version is v2.0.1.

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