An autonomous research agent that executes multi-angle searches, extracts deep-page content, and synthesizes data into structured, cited reports.
Install & Download
1. ClawHub CLI
The fastest way to install a skill directly from the registry.
npx clawhub@latest install web-searcher
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 web-searcher 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 Web Searcher?
The web-searcher agent is a specialized tool within the Openclaw Skills library designed to transform how AI agents interact with the live web. Unlike standard search tools that return simple lists of links, this skill enables an agent to act as a digital librarian and analyst. It intelligently parses complex queries into multiple search angles, evaluates source authority, and extracts specific data points to build a comprehensive knowledge base for any given topic.
By integrating this skill into your workflow, you empower your agent to perform deep-dive investigations that go beyond surface-level results. It leverages advanced search strategies to cross-reference facts, identify industry trends, and compile detailed comparisons, making it an essential component for any developer building sophisticated research-driven applications using Openclaw Skills.
Web Searcher Use Cases
- Deep-dive factual verification across multiple authoritative sources.
- Market research and product comparisons with structured feature tables.
- Corporate intelligence and professional profiling via news and primary domain analysis.
- Technical documentation synthesis and distillation of complex step-by-step guides.
- Monitoring time-sensitive information using specific freshness parameters.
How Web Searcher Works
- The agent parses the initial request into 2-5 distinct search queries to ensure comprehensive coverage.
- It executes the search phase using rate-limited queries to identify the most relevant URLs.
- A deep dive phase follows where the agent fetches full page content (up to 5000 characters) from the most promising sources.
- Extracted data is cross-referenced to identify consensus, flag contradictions, and determine the confidence level of each claim.
- The skill synthesizes all findings into a structured Markdown report including key findings, detailed analysis, and a cited bibliography.
Web Searcher Setup
To deploy the web-searcher skill, ensure your environment is configured with the necessary search API credentials. You can then register the skill within your Openclaw Skills directory.
# Install the skill into your local agent environment
openclaw install web-searcher
# Run a test research query
openclaw run web-searcher --query "Current state of generative AI in 2024"
Web Searcher Data Schema & Taxonomy
The web-searcher skill produces a standardized research object to maintain data integrity across different Openclaw Skills implementations:
| Section | Content Description |
|---|---|
| Key Findings | Bullet points of major facts with inline source citations. |
| Details | A narrative expansion of the research topic and contextual analysis. |
| Sources | A list of titles and URLs used, including a summary of information retrieved from each. |
| Confidence & Gaps | Metadata identifying the reliability of the report and specifically noting what information could not be found. |
Web Searcher Advanced Features
- Intelligent rate limiting to prevent token waste and API throttling.
- Support for freshness parameters to filter results by day, week, month, or year.
- Automatic content truncation at 5000 characters to optimize context window usage.
- Multi-source cross-referencing to ensure high-confidence reporting.
- Sub-task spawning for massive research requests that exceed single-agent capacity.
SKILL.md
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