A systematic multi-source investigation skill for AI agents that prioritizes methodology tracking and source evaluation over surface-level searches.
Install & Download
1. ClawHub CLI
The fastest way to install a skill directly from the registry.
npx clawhub@latest install in-depth-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 in-depth-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 Deep Research?
Deep Research is designed for AI agents that need to go beyond simple web lookups. It provides a structured framework for conducting exhaustive investigations, ensuring that findings are not just summarized but cross-referenced, evaluated for bias, and documented with a clear methodology. By utilizing Openclaw Skills like this one, developers can empower agents to tackle high-stakes questions where accuracy and depth are non-negotiable.
This skill transforms raw information retrieval into a professional-grade research process. It includes protocols for scoping requirements, vetting authority, and identifying knowledge gaps, making it an essential tool for any complex decision-making workflow powered by Openclaw Skills.
Deep Research Use Cases
- Conducting thorough competitive market analysis.
- Investigating primary technical documentation for complex software integrations.
- Fact-checking high-stakes claims with multi-vector source verification.
- Identifying research gaps and unknown variables in project planning.
- Performing academic or legal discovery with documented methodology.
How Deep Research Works
- Scope: Define the research depth (Quick to Exhaustive) and specific questions to be answered.
- Search: Execute a multi-vector search strategy, tracking queries and citation trails.
- Evaluate: Audit every source for authority, recency, evidence, and potential bias.
- Deepen: Iteratively follow promising threads and fill identified gaps in the findings.
- Synthesize: Reconcile contradictions and weight information based on source quality.
- Document: Create a transparent research trail including all sources and search queries.
- Deliver: Format the final output as an executive summary, academic report, or working document.
Deep Research Setup
To implement Deep Research within your agent framework, ensure the necessary reference files are present in your project directory. Openclaw Skills work best when methodology and source evaluation templates are pre-defined.
# Initialize the research directory
mkdir -p research/logs
# Create required reference files
touch methodology.md sources.md output-formats.md
Configure your agent to recognize the Deep Research protocol by pointing it to these markdown templates for consistency.
Deep Research Data Schema & Taxonomy
The Deep Research skill organizes data through a structured taxonomy of sources and methodology logs. It tracks the following metadata:
| Attribute | Description |
|---|---|
| Authority | Credentials and reputation of the source author. |
| Recency | Timestamp of the information to ensure validity. |
| Evidence | Data-backed claims vs. anecdotal assertions. |
| Bias | Identified conflicts of interest or agendas. |
| Confidence | High/Medium/Low rating based on corroboration. |
It generates a comprehensive research trail including sources.md for citation management and methodology.md for auditability.
Deep Research Advanced Features
- Multi-vector search approach using multiple engines and primary sources.
- Iterative deepening that adjusts search breadth based on initial findings.
- Explicit contradiction reconciliation for conflicting data points.
- Detailed gap analysis to identify what information remains unknown.
- Customizable output formats ranging from executive summaries to full academic citations within Openclaw Skills environments.
SKILL.md
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