A professional deep-research skill that reconstructs a subject's life-cycle and compares it against peers to generate original strategic insights.
Install & Download
1. ClawHub CLI
The fastest way to install a skill directly from the registry.
npx clawhub@latest install cell-horizontal-vertical-analysis
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 cell-horizontal-vertical-analysis 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 Horizontal Vertical Analysis?
Horizontal Vertical Analysis is a sophisticated research framework designed to transform vague inquiries into high-judgment reports. This methodology operates on two primary axes: the vertical axis, which rebuilds the chronological life-cycle and causal history of a subject, and the horizontal axis, which compares the subject against current competitors, substitutes, and market peers. By crossing these axes, the skill moves beyond simple data aggregation to deliver original insights that explain why a subject has evolved into its current state. As part of the Openclaw Skills ecosystem, it prioritizes evidence-based logic, distinguishing clearly between facts, inferences, and unknown variables.
Horizontal Vertical Analysis Use Cases
- Systematic study of a specific product, company, or emerging technology.
- Competitive landscape analysis and peer benchmarking for strategic planning.
- Reconstructing historical development paths to identify path dependencies and future trends.
- Preparing professional research documents for investment due diligence or curriculum development.
- Generating structured market reports that require a clear distinction between raw data and analytical judgment.
How Horizontal Vertical Analysis Works
- Scoping: Define the research object, type (product, person, concept, etc.), and desired depth level.
- Skeleton Building: Establish a source map and timeline framework to ensure information sufficiency before analysis.
- Vertical Execution: Map the subject's evolution from origin to the present, identifying key milestones and causal drivers.
- Horizontal Execution: Benchmarking against 3-5 representative peers to identify market positioning and unique value gaps.
- Insight Intersection: Analyze how historical decisions shaped current strengths or weaknesses to produce unique judgments.
- Report Delivery: Generate a structured Markdown report, which can be exported to PDF for formal delivery.
Horizontal Vertical Analysis Setup
To integrate this research framework into your environment, install it through your agent's skill manager. Ensure Python is available if you intend to use the PDF export functionality.
# Example installation via CLI
openclaw add horizontal-vertical-analysis
Configure your default research depth (quick, standard, or deep) in your agent's preference file to streamline the Openclaw Skills workflow.
Horizontal Vertical Analysis Data Schema & Taxonomy
The skill utilizes a structured metadata approach to organize research findings and ensure reproducibility:
| Component | Format | Description |
|---|---|---|
| Source Map | JSON/List | Tracks primary and secondary sources for evidence validation |
| Timeline | Array | Chronological sequence of milestones with causal annotations |
| Comparison Matrix | Table | Horizontal mapping of features and positioning vs competitors |
| Evidence Tagging | Metadata | Categorizes statements as Fact, Inference, or Unknown |
| Research Schema | JSON | A strict schema for structured recording of all research nodes |
Horizontal Vertical Analysis Advanced Features
- Multi-tier Analysis Modes: Choose between Quick (summary), Standard (full analysis), or Deep (exhaustive research with matrix mapping).
- Automated PDF Export: Includes a dedicated Python script to convert Markdown research reports into professional PDF documents.
- Evidence Validation Strategy: Implements a double-verification policy for key facts using primary source priority.
- Domain-Specific Lenses: Adjusts analysis focus based on whether the subject is a person, technology, or market phenomenon.
- Structural Logic Checks: Hard rules prevent the agent from treating inferences as facts or generating superficial 'fluff' content.
SKILL.md
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