Requirements
- Target platform
- OpenClaw
- Install method
- Manual import
- Extraction
- Extract archive
- Prerequisites
- OpenClaw
- Primary doc
- SKILL.md
DuckDuckGo web search for private tracker-free searching. Use when user asks to search the web find information online or perform web-based research without...
DuckDuckGo web search for private tracker-free searching. Use when user asks to search the web find information online or perform web-based research without...
Hand the extracted package to your coding agent with a concrete install brief instead of figuring it out manually.
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.
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.
Private web search using DuckDuckGo API for tracker-free information retrieval.
Privacy-focused search (no tracking) Instant answer support Multiple search modes (web, images, videos, news) JSON output for easy parsing No API key required
import requests def search_duckduckgo(query, max_results=10): """ Perform DuckDuckGo search and return results. Args: query: Search query string max_results: Maximum number of results to return (default: 10) Returns: List of search results with title, url, description """ url = "https://api.duckduckgo.com/" params = { "q": query, "format": "json", "no_html": 1, "skip_disambig": 0 } response = requests.get(url, params=params) data = response.json() # Extract results results = [] # Abstract (instant answer) if data.get("Abstract"): results.append({ "type": "instant_answer", "title": "Instant Answer", "content": data["Abstract"], "source": data.get("AbstractSource", "DuckDuckGo") }) # Related topics if data.get("RelatedTopics"): for topic in data["RelatedTopics"][:max_results]: if isinstance(topic, dict) and topic.get("Text"): results.append({ "type": "related", "title": topic.get("FirstURL", "").split("/")[-1].replace("-", " ").title(), "content": topic["Text"], "url": topic.get("FirstURL", "") }) return results[:max_results]
from bs4 import BeautifulSoup import requests def search_with_results(query, max_results=10): """ Perform DuckDuckGo search and scrape actual results. Args: query: Search query string max_results: Maximum number of results to return Returns: List of search results with title, url, snippet """ url = "https://duckduckgo.com/html/" params = {"q": query} headers = { "User-Agent": "Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36" } response = requests.post(url, data=params, headers=headers) soup = BeautifulSoup(response.text, "html.parser") results = [] for result in soup.find_all("a", class_="result__a", href=True)[:max_results]: results.append({ "title": result.get_text(), "url": result["href"], "snippet": result.find_parent("div", class_="result__body").get_text().strip() }) return results
DuckDuckGo supports standard search operators: OperatorExampleDescription"""exact phrase"Exact phrase match-python -djangoExclude termssite:site:wikipedia.org historySearch specific sitefiletype:filetype:pdf reportSpecific file typesintitle:intitle:openclawWords in titleinurl:inurl:docs/Words in URLORdocker OR kubernetesEither term
Default mode, searches across the web. search_with_results("machine learning tutorial")
def search_images(query, max_results=10): url = "https://duckduckgo.com/i.js" params = { "q": query, "o": "json", "vqd": "", # Will be populated "f": ",,,", "p": "1" } response = requests.get(url, params=params) data = response.json() results = [] for result in data.get("results", [])[:max_results]: results.append({ "title": result.get("title", ""), "url": result.get("image", ""), "thumbnail": result.get("thumbnail", ""), "source": result.get("source", "") }) return results
Add !news to the query: search_duckduckgo("artificial intelligence !news")
Good queries: "DuckDuckGo API documentation" 2024 (specific, recent) site:github.com openclaw issues (targeted) python machine learning tutorial filetype:pdf (resource-specific) Avoid: Vague single words ("search", "find") Overly complex operators that might confuse results Questions with multiple unrelated topics
DuckDuckGo advantages: โ No personal tracking โ No search history stored โ No user profiling โ No forced personalized results
Use HTML scraping for actual results - The JSON API provides instant answers but limited result lists Add appropriate delays - Respect rate limits when making multiple queries Cache results - Store common searches to avoid repeated API calls
def search_safely(query, retries=3): for attempt in range(retries): try: results = search_with_results(query) if results: return results except Exception as e: if attempt == retries - 1: raise time.sleep(2 ** attempt) # Exponential backoff return []
def format_results_markdown(results, query): output = f"# Search Results for: {query}\n\n" for i, result in enumerate(results, 1): output += f"## {i}. {result.get('title', 'Untitled')}\n\n" output += f"**URL:** {result.get('url', 'N/A')}\n\n" output += f"{result.get('snippet', result.get('content', 'N/A'))}\n\n" output += "---\n\n" return output
import json def format_results_json(results, query): return json.dumps({ "query": query, "count": len(results), "results": results, "timestamp": datetime.now().isoformat() }, indent=2)
search_duckduckgo(f'{library_name} documentation filetype:md')
search_duckduckgo(f'{topic} 2024 news')
search_duckduckgo(f'{error_message} {tool_name} stackoverflow')
search_duckduckgo('postgresql vs mysql performance 2024')
class DuckDuckGoSearcher: def __init__(self): self.session = requests.Session() self.session.headers.update({ "User-Agent": "Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36" }) def search(self, query, mode="web", max_results=10): """ Unified search interface. Args: query: Search query mode: 'web', 'images', 'news' max_results: Maximum results Returns: Formatted results as list """ if mode == "images": return self._search_images(query, max_results) elif mode == "news": return self._search_web(f"{query} !news", max_results) else: return self._search_web(query, max_results) def _search_web(self, query, max_results): # Implementation pass def _search_images(self, query, max_results): # Implementation pass
DuckDuckGo API Wiki: https://duckduckgo.com/api Instant Answer API: https://duckduckgo.com/params Search Syntax: https://help.duckduckgo.com/duckduckgo-help-pages/results/syntax/
HTML scraping patterns for result extraction Rate limiting best practices Result parsing and filtering
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