A privacy-focused, API-key-free web search skill for AI agents to retrieve real-time news, images, and documentation.
Install & Download
1. ClawHub CLI
The fastest way to install a skill directly from the registry.
npx clawhub@latest install duckduckgo-search
2. Manual Installation
Copy the skill folder to one of these locations
~/.openclaw/skills/ <project>/skills/ Priority: Workspace > Local > Bundled
3. Prompt Installation
Copy this prompt to OpenClaw to install it automatically.
Help me install duckduckgo-search using Clawhub. If Clawhub is not installed, install it first (npm i -g clawhub).
Prefer to download?
Get the raw skill files in a ZIP archive.
What is DuckDuckGo Web Search Skill?
The DuckDuckGo Web Search Skill empowers AI agents within the Openclaw Skills ecosystem to perform comprehensive internet searches. Unlike traditional search APIs that require complex authentication and monthly fees, this skill provides a streamlined, privacy-centric way to fetch text results, latest news, high-quality images, and even map locations. It is built on the robust duckduckgo-search library, ensuring that user queries remain anonymous while delivering highly relevant data.
This skill is particularly valuable for developers building agents that need current event context, technical documentation, or visual assets without the overhead of managed search tiers. By integrating this into Openclaw Skills, agents can bridge the gap between static training data and the evolving live web through a reliable, lightweight interface.
DuckDuckGo Web Search Skill Use Cases
- Retrieving the latest software documentation, Python tutorials, or API references.
- Monitoring real-time technology news or global current events.
- Finding specific image assets or video resources for content generation workflows.
- Looking up local business information, addresses, and coordinates via map search.
- Fetching instant answers for factual queries to improve agent response accuracy.
How DuckDuckGo Web Search Skill Works
- The AI agent identifies a need for external information and triggers the search skill.
- The skill initializes a connection to the search engine using a context manager to ensure resource safety.
- A specific search method is called (e.g., text, news, images, or maps) based on the agent's intent.
- Advanced filters such as region (e.g., cn-zh), time limits (e.g., past week), and safe search levels are applied to the query.
- The skill executes the request and parses the raw response into a structured JSON-like format.
- Results including titles, source URLs, and content snippets are returned to the agent for synthesis or further navigation.
DuckDuckGo Web Search Skill Setup
To integrate this search capability into your Openclaw Skills environment, install the required dependency using uv or pip:
# Using uv (recommended)
uv pip install duckduckgo-search
# Or using standard pip
pip install duckduckgo-search
No API key or environment variables are required. For environments requiring network tunneling, you can initialize the skill with a proxy parameter.
DuckDuckGo Web Search Skill Data Schema & Taxonomy
The skill returns structured data objects tailored to the search type. For standard text searches, the schema follows this structure:
| Field | Description |
|---|---|
| title | The headline or page title of the search result |
| href | The direct URL to the source web page |
| body | A brief snippet or summary of the content found |
For news or image searches, additional metadata such as source, date, image_url, and thumbnail are provided to the Openclaw Skills agent for enhanced context.
DuckDuckGo Web Search Skill Advanced Features
- Regional and Language Localization: Support for specific regions like cn-zh, us-en, and jp-jp to ensure localized relevance.
- Multi-Modal Search: Dedicated methods for fetching news, high-resolution images, videos, and map-based location data.
- Privacy and Security: Built-in safe search levels (on, moderate, off) and anonymous querying via proxy support.
- Search Suggestions: Ability to fetch auto-complete phrases to refine complex search queries.
- Developer-Friendly Controls: Fine-grained control over result limits and time ranges to optimize agent performance and token usage.
SKILL.md
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