A professional-grade research framework that automates systematic academic, market, and competitive analysis with mandatory quality gates.
Install & Download
1. ClawHub CLI
The fastest way to install a skill directly from the registry.
npx clawhub@latest install deep-research-v2
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 deep-research-v2 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 Deep Research Pro?
Deep Research Pro is a cutting-edge skill designed to transform AI agents into expert analysts. By implementing a rigorous 7-phase methodology, it ensures that data collection goes beyond surface-level summaries to provide critical insights and cross-validated evidence. This is an essential component of the Openclaw Skills ecosystem for users requiring high-fidelity intelligence in academic or corporate environments.
The skill prioritizes methodological rigor, evaluating sources based on authority, timeliness, and reproducibility. Whether you are conducting a patent search, a competitive landscape analysis, or an academic literature review, Deep Research Pro provides a structured and traceable workflow that outputs professional reports with verifiable evidence levels.
Deep Research Pro Use Cases
- Automated academic literature reviews using OpenAlex and Google Scholar.
- Deep market research and competitive analysis for product development.
- Policy and regulatory research across government and standard-setting organizations.
- Critical patent analysis and technical trend forecasting.
How Deep Research Pro Works
- Research Planning: Defines core questions and designs a retrieval matrix in research-plan.md.
- Multi-Source Retrieval: Aggregates data from academic, industry, and patent databases.
- Quality Screening: Filters sources based on a weighted scoring system (Authority, Timeliness, etc.).
- Deep Analysis: Extracts key insights and assigns evidence grades (A-D) to findings.
- Cross-Validation: Compares industry data against academic findings to identify potential biases.
- Synthesis Reporting: Generates a structured final report with traceable citations.
- Feedback Loop: Iterates on the report based on user feedback or specific challenges to conclusions.
Deep Research Pro Setup
To integrate this capability into your agent via Openclaw Skills, ensure the following dependencies are available:
# Install system dependencies
sudo apt-get install jq bc
# Configure API access for academic data
export OPENALEX_API_KEY="your_key_here"
Deep Research Pro Data Schema & Taxonomy
The skill maintains a strict hierarchical directory structure for every project:
| Directory | File | Description |
|---|---|---|
analysis/ |
insights.md |
Core discoveries and evidence grades |
analysis/ |
validation-matrix.md |
Comparison of data across different source types |
sources/ |
raw-sources.json |
The initial dataset before filtering |
reports/ |
final-report.md |
The comprehensive final analysis output |
Deep Research Pro Advanced Features
- Evidence Grading System: Automatically assigns A to D grades based on source methodology and sample size.
- Configurable Depth: Toggle between shallow (quick overview) and deep (full 7-phase) research modes.
- Bias Detection: Cross-references industry reports against academic journals to highlight conflicts of interest.
- Automated Citations: Generates bibliographies with clickable links and quality scorecards for every source.
SKILL.md
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