An advanced analytical skill that synthesizes fragmented research materials into structured, consulting-grade professional reports.
Install & Download
1. ClawHub CLI
The fastest way to install a skill directly from the registry.
npx clawhub@latest install deep-research-report
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-report 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 Report Generator?
The Deep Research Report Generator is a sophisticated tool designed for the Openclaw Skills ecosystem that automates the creation of high-level analytical documents. It takes raw, often fragmented research inputs—such as market data, industry news, and financial stats—and applies a rigorous logical framework to produce a report that mirrors the quality of professional brokerage or consulting firms.
This skill goes beyond simple summarization by distinguishing between facts, inferences, and subjective judgments. It is engineered to identify core contradictions within data and provide a forward-looking perspective, making it an essential asset for professionals who require high-density information synthesis within their Openclaw Skills environment.
Deep Research Report Generator Use Cases
- Creating deep-dive industry chain analysis reports from multi-source technical data.
- Generating investment value assessments for specific companies using financial and business inputs.
- Synthesizing policy interpretations to understand market impacts and regulatory shifts.
- Constructing strategic market outlooks by merging disparate data points into a cohesive narrative.
How Deep Research Report Generator Works
- The process is initiated when the user provides research materials and uses specific trigger keywords such as deep research or industry report within an Openclaw Skills session.
- The system analyzes the input to extract core contradictions, key trends, and primary conclusions while filtering out redundant information.
- It establishes a multi-layered logical chain that connects the research background to current facts, deep driving logics, and potential bottlenecks.
- The analytical engine categorizes information into distinct hierarchies: raw facts, logical inferences, and professional judgments.
- It constructs a formal 8-section report structure, including a comprehensive abstract, risk factor analysis, and future scenario modeling.
- The completed report is automatically exported to a specific Obsidian vault path using a standardized date-prefixed naming convention.
Deep Research Report Generator Setup
To deploy this skill within your Openclaw Skills setup, ensure that your local directory structure is prepared to receive the generated reports. No complex external dependencies are required as the logic is self-contained.
# Ensure your Obsidian Vault path exists
mkdir -p "Obsidian-Vault/10_投资金融/12_行业研究/"
Deep Research Report Generator Data Schema & Taxonomy
The skill maintains a strict data taxonomy to ensure all generated reports are compatible with professional knowledge management systems like Obsidian.
| Attribute | Specification |
|---|---|
| Storage Path | Obsidian-Vault/10_投资金融/12_行业研究/ |
| File Format | Markdown (.md) |
| Filename Pattern | YYYY-MM-DD_Report_Title.md |
| Report Structure | 8-Part logic (Abstract to Conclusion) |
| Metadata Tags | Facts, Inferences, Judgments, Risk Variables |
Deep Research Report Generator Advanced Features
- Evidence Gap Detection: Explicitly flags conclusions where the provided evidence is insufficient for high-certainty judgment.
- Multi-Variable Tracking: Identifies and highlights the most critical variables to monitor for future trend changes.
- Confidence Rating: Annotates the highest certainty conclusions with specific confidence scores.
- Consulting-Grade Logic: Uses a background-status-driver-risk-evolution logic chain to ensure professional depth.
- Automated Conflict Resolution: Automatically reconciles or highlights conflicting information found within the input materials.
SKILL.md
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