An AI-powered financial intelligence tool that transforms news headlines into detailed 18-month investment scenarios using a multi-agent workflow.
The fastest way to install a skill directly from the registry.
npx clawhub@latest install scenario-analyzer
Copy the skill folder to one of these locations
~/.openclaw/skills/ <project>/skills/ Priority: Workspace > Local > Bundled
Copy this prompt to OpenClaw to install it automatically.
Help me install scenario-analyzer using Clawhub. If Clawhub is not installed, install it first (npm i -g clawhub).
Get the raw skill files in a ZIP archive.
Scenario Analyzer is a sophisticated technical skill designed for Openclaw Skills that automates the complex process of macroeconomic and market analysis. By processing news headlines, it orchestrates a collaborative workflow between two specialized AI agents to project financial impacts over an 18-month horizon. This tool is essential for investors seeking automated, high-fidelity reports that detail primary, secondary, and tertiary market effects.
The core value of this skill lies in its multi-agent approach. The primary analyst agent constructs Base, Bull, and Bear cases with allocated probabilities, while a strategy reviewer agent provides critical second opinions to ensure logical consistency and bias reduction. This ensures that the generated investment intelligence is not just fast, but also rigorously vetted and highly actionable.
To utilize this skill within your Openclaw Skills environment, ensure you have the required reference files and agent configurations in place. Prepare your directory structure as follows:
mkdir -p reports
# Ensure references/headline_event_patterns.md exists
# Ensure references/sector_sensitivity_matrix.md exists
# Ensure references/scenario_playbooks.md exists
Run the skill using the slash command followed by your target headline:
/headline-scenario-analyzer "Fed raises interest rates by 50bp"
The skill maintains a structured output and metadata taxonomy to ensure high-quality financial intelligence. Data is organized as follows:
| Component | Format | Description |
|---|---|---|
| Analysis Timeframe | 3 Phases | 0-6 months, 6-12 months, and 12-18 months. |
| Scenario Probabilities | Percentage | Base + Bull + Bear scenarios totaling 100%. |
| Impact Levels | 1st/2nd/3rd | Direct, value-chain, and macro/regulatory impacts. |
| Output Path | Markdown File | Saved to reports/scenario_analysis_<topic>_YYYYMMDD.md. |
| Target Markets | US Markets | Focuses on US-listed equities and ADRs. |
Loading
An AI agent skill designed to produce formal academic research papers following strict IEEE and ACM formatting and citation standards.

A senior frontend specialist designed to architect and implement production-grade React 19 applications with TypeScript and modern state patterns.

A sophisticated investment management skill that integrates with Alpaca to provide real-time portfolio auditing, risk assessment, and rebalancing logic.

A specialized security analyst skill for conducting automated SAST scans, manual code audits, and infrastructure security reviews within Openclaw Skills.

An advanced AI analysis tool that interprets sector performance charts to identify market cycles and predict rotation patterns.

An AI coding skill designed to implement enterprise-grade security, authentication, and OWASP Top 10 prevention in your codebase.








































