An intelligent research agent that aggregates, de-duplicates, and verifies information from academic, social, news, and web sources.
Install & Download
1. ClawHub CLI
The fastest way to install a skill directly from the registry.
npx clawhub@latest install multi-source-research
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 multi-source-research 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 Multi-Source Research Assistant?
The Multi-Source Research Assistant is a sophisticated capability designed for the Openclaw Skills ecosystem, enabling developers and researchers to conduct deep-dive investigations across a fragmented digital landscape. It integrates traditional web search with specialized academic platforms, real-time social media streams, and authoritative news aggregators. By synthesizing these diverse data streams into a single structured report, the skill eliminates the manual effort of cross-referencing information.
This skill is particularly valuable for those who need a holistic view of a topic, balancing technical academic data with the latest public sentiment and mainstream coverage. Within the context of Openclaw Skills, it acts as a centralized intelligence hub that prioritizes data integrity through automated deduplication and credibility scoring, ensuring that the insights generated are both comprehensive and trustworthy.
Multi-Source Research Assistant Use Cases
- Conducting deep academic literature reviews across platforms like CNKI and arXiv.
- Performing real-time public opinion monitoring on social media channels like Weibo and Zhihu.
- Gathering multi-dimensional data for competitive intelligence and market research.
- Executing news aggregation and verification for investigative reporting.
- Identifying emerging trends by cross-referencing academic preprints with social media discussions.
How Multi-Source Research Assistant Works
- Requirement Analysis: The agent parses the user's query to define the research theme, time frame, and key focus areas.
- Parallel Querying: It simultaneously accesses web engines, academic databases, social networks, and news portals.
- Information Deduplication: Similar content is identified and merged, preserving the most complete version while removing redundancy.
- Credibility Assessment: Each source is assigned a reliability grade (A, B, or C) based on its origin and authority.
- Structured Reporting: The skill generates a comprehensive Markdown report categorized by source statistics, core findings, and academic references.
Multi-Source Research Assistant Setup
To integrate this research capability into your workflow using Openclaw Skills, use the following installation and configuration steps:
# Install the multi-source research skill
openclaw install multi-source-research
# Configure credentials for academic or premium data sources
openclaw config set RESEARCH_SOURCES_KEY=your_api_key_here
Ensure that your environment has network access to the target platforms and respects the robots.txt protocols of the indexed sites.
Multi-Source Research Assistant Data Schema & Taxonomy
The Multi-Source Research Assistant organizes data based on a strict credibility hierarchy and source taxonomy:
| Grade | Source Category | Priority |
|---|---|---|
| Grade A | Government websites, core academic journals, official media | High |
| Grade B | Mainstream news outlets, established digital platforms | Medium |
| Grade C | Social media, self-published content, microblogs | Low |
Output reports follow a standardized metadata structure including source counts, sorted key findings, citation lists, and sentiment dynamic indicators.
Multi-Source Research Assistant Advanced Features
- Intelligent deduplication engine that merges overlapping information from disparate sources.
- Source-weighted credibility filtering to prioritize authoritative data over social noise.
- Cross-validation logic that highlights potential misinformation by comparing mainstream news with social media trends.
- Structured Markdown output templates designed for seamless integration into larger documentation projects.
- Support for multiple academic platforms including Google Scholar and Wanfang Data within the Openclaw Skills framework.
SKILL.md
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