A professional research framework that builds systematic domain knowledge by intersecting longitudinal timelines with horizontal competitive landscapes.
Install & Download
1. ClawHub CLI
The fastest way to install a skill directly from the registry.
npx clawhub@latest install cross-axis-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 cross-axis-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 Cross-Axis Analysis?
The Cross-Axis Analysis framework is a high-performance methodology designed for researchers and analysts to quickly gain a 360-degree understanding of unfamiliar domains. By leveraging Openclaw Skills, this framework systematically processes data through two primary vectors: a longitudinal timeline analysis of historical development and a horizontal comparison of the current competitive landscape.
This dual-axis approach ensures that users do not just see isolated facts, but understand the path dependency of a technology, product, or company. It bridges the gap between historical decisions and current market positioning, allowing AI agents to generate insights that are both contextually rich and strategically actionable.
Cross-Axis Analysis Use Cases
- Academic research and comprehensive literature reviews to identify development trends.
- Investment analysis for stocks or crypto to understand path dependencies and future outlooks.
- Competitive intelligence for choosing schools, companies, or strategic business directions.
- Rapid onboarding into new technical or industrial fields with quick-start summaries.
- World-building and ecological research for creative writing and novel development.
How Cross-Axis Analysis Works
- Identify Subject: Define the specific research target, whether it is a product, company, technology, or person.
- Load Template: The system retrieves the standardized prompt-template.md from the references directory.
- Select Version: Choose between the Deep Version (10,000-30,000 words for strategy) or the Fast Version (≤1,500 words for immediate judgment).
- Execution: The agent replaces placeholders with the research target and executes the cross-axis logic.
- Synthesis: The AI output is organized and supplemented with human-led interpretations to deliver a final report.
Cross-Axis Analysis Setup
To implement this within your Openclaw Skills environment, ensure your prompt templates are correctly mapped:
# Navigate to your skill directory
cd skills/cross-axis-analysis
# Ensure the reference template exists
cat references/prompt-template.md
# Trigger the framework via your AI agent
# "Analyze [Target] using the cross-axis-analysis framework"
Cross-Axis Analysis Data Schema & Taxonomy
The skill organizes its research outputs based on the following structural taxonomy:
| Data Layer | Description |
|---|---|
| Longitudinal Axis | Historical milestones, turning points, and evolutionary path. |
| Horizontal Axis | Current competitors, ecosystem positioning, and market share. |
| Intersection Point | Deep insights derived from how past decisions impact current status. |
| Version Metadata | Categorization as either 'Fast' (Brief) or 'Deep' (Comprehensive). |
Cross-Axis Analysis Advanced Features
- Multi-version scaling: Toggle between 1,500-word executive summaries and 30,000-word strategic deep dives.
- Path-Dependency Analysis: Specifically connects past technical decisions to current market advantages.
- Adaptive Research Scopes: Automatically adjusts depth based on information density in niche vs. mainstream domains.
- Integration ready: Can be hooked into broader Openclaw Skills workflows for automated industry monitoring.
SKILL.md
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