Scenario Analyzer
Overview
This skill analyzes medium-to-long-term (18-month) investment scenarios
starting from a news headline. It invokes two specialized agents in sequence
(scenario-analyst and strategy-reviewer) and integrates multi-angle
analysis with a critical review into a comprehensive report.
When to Use This Skill
Use this skill when:
- You want to analyze the medium-to-long-term investment impact of a news headline
- You want to construct multiple 18-month scenarios
- You want sector/stock impacts organized into 1st/2nd/3rd-order effects
- You need a comprehensive analysis that includes a second opinion
Examples:
/scenario-analyzer "Fed raises interest rates by 50bp, signals more hikes ahead" /scenario-analyzer "China announces new tariffs on US semiconductors" /scenario-analyzer "OPEC+ agrees to cut oil production by 2 million barrels per day"
Prerequisites
- API Keys: None (uses only WebSearch/WebFetch)
- MCP Servers: None
- Dependencies: The scenario-analyst and strategy-reviewer agents must be available via the Task tool
Architecture
┌─────────────────────────────────────────────────────────────────────┐ │ Skill (orchestrator) │ │ │ │ Phase 1: Preparation │ │ ├─ Headline parsing │ │ ├─ Event type classification │ │ └─ Reference loading │ │ │ │ Phase 2: Agent invocation │ │ ├─ scenario-analyst (primary analysis) │ │ └─ strategy-reviewer (second opinion) │ │ │ │ Phase 3: Integration & report generation │ │ └─ reports/scenario_analysis_<topic>_YYYYMMDD.md │ └─────────────────────────────────────────────────────────────────────┘
Workflow
Phase 1: Preparation
Step 1.1: Headline Parsing
Parse the headline provided by the user.
-
Headline check
- Confirm a headline was passed as an argument
- If not provided, ask the user for input
-
Keyword extraction
- Key entities (company names, country names, institution names)
- Numeric data (rates, prices, quantities)
- Actions (raise, cut, announce, agree, etc.)
Step 1.2: Event Type Classification
Classify the headline into one of the following categories:
| Category | Examples |
|---|---|
| Monetary Policy | FOMC, ECB, BOJ, rate hike, rate cut, QE/QT |
| Geopolitics | War, sanctions, tariffs, trade friction |
| Regulation & Policy | Environmental regulation, financial regulation, antitrust |
| Technology | AI, EV, renewables, semiconductors |
| Commodities | Crude oil, gold, copper, agricultural products |
| Corporate & M&A | Acquisitions, bankruptcies, earnings, industry restructuring |
Step 1.3: Reference Loading
Based on the event type, load the relevant references:
Read references/headline_event_patterns.md Read references/sector_sensitivity_matrix.md Read references/scenario_playbooks.md
Reference contents:
headline_event_patterns.md: Historical event patterns and market reactionssector_sensitivity_matrix.md: Event × sector impact-magnitude matrixscenario_playbooks.md: Scenario-construction templates and best practices
Phase 2: Agent Invocation
Step 2.1: Invoke scenario-analyst
Use the Agent tool to invoke the primary analysis agent.
Agent tool: - subagent_type: "scenario-analyst" - prompt: | Perform an 18-month scenario analysis for the following headline. ## Target Headline [the input headline] ## Event Type [classification result] ## Reference Information [summary of the loaded references] ## Analysis Requirements 1. Use WebSearch to collect related news from the past 2 weeks 2. Construct 3 scenarios — Base/Bull/Bear (probabilities sum to 100%) 3. Analyze 1st/2nd/3rd-order impacts by sector 4. Select 3-5 positive- and 3-5 negative-impact stocks (US market only) 5. Output everything in English
Expected output:
- List of related news articles
- Details of the 3 scenarios (Base/Bull/Bear)
- Sector impact analysis (1st/2nd/3rd-order)
- Stock recommendation list
Step 2.2: Invoke strategy-reviewer
Using the scenario-analyst's results, invoke the review agent.
Agent tool: - subagent_type: "strategy-reviewer" - prompt: | Review the following scenario analysis. ## Target Headline [the input headline] ## Analysis Result [the full scenario-analyst output] ## Review Requirements Review from the following angles: 1. Overlooked sectors/stocks 2. Validity of the scenario probability allocation 3. Logical consistency of the impact analysis 4. Detection of optimism/pessimism bias 5. Proposal of alternative scenarios 6. Realism of the timeline Output constructive and specific feedback in English.
Expected output:
- Pointing out blind spots
- Opinion on the scenario probabilities
- Pointing out bias
- Proposal of alternative scenarios
- Final recommendations
Phase 3: Integration & Report Generation
Step 3.1: Integrate Results
Integrate the output of both agents to produce the final investment judgment.
Integration points:
- Fill in the blind spots raised in the review
- Adjust the probability allocation (if needed)
- Make the final judgment accounting for bias
- Formulate a concrete action plan
Step 3.2: Generate Report
Generate the final report in the following format and save it to a file.
Save location: reports/scenario_analysis_<topic>_YYYYMMDD.md
markdown# Headline Scenario Analysis Report **Analyzed at**: YYYY-MM-DD HH:MM **Target headline**: [the input headline] **Event type**: [classification category] --- ## 1. Related News Articles [news list collected by scenario-analyst] ## 2. Scenario Overview (through 18 months out) ### Base Case (XX% probability) [scenario details] ### Bull Case (XX% probability) [scenario details] ### Bear Case (XX% probability) [scenario details] ## 3. Sector / Industry Impact ### 1st-Order Impact (direct) [impact table] ### 2nd-Order Impact (value chain / related industries) [impact table] ### 3rd-Order Impact (macro / regulation / technology) [impact table] ## 4. Stocks Expected to Benefit (3-5 tickers) [stock table] ## 5. Stocks Expected to Be Hurt (3-5 tickers) [stock table] ## 6. Second Opinion / Review [strategy-reviewer output] ## 7. Final Investment Judgment & Implications ### Recommended Actions [concrete actions informed by the review] ### Risk Factors [list of key risks] ### Monitoring Points [indicators / events to follow] --- **Generated by**: scenario-analyzer skill **Agents**: scenario-analyst, strategy-reviewer
Step 3.3: Save the Report
- Create the
reports/directory if it does not exist - Save as
scenario_analysis_<topic>_YYYYMMDD.md(e.g.,scenario_analysis_venezuela_20260104.md) - Notify the user that the save completed
- Do not save directly to the project root
Output
This skill generates the following file:
| File | Format | Description |
|---|---|---|
reports/scenario_analysis_<topic>_YYYYMMDD.md | Markdown | Comprehensive scenario analysis report |
Output contents:
- List of related news articles
- 3 scenarios — Base/Bull/Bear (with probability allocation)
- Sector impact analysis (1st/2nd/3rd-order)
- Positive/negative stock recommendations
- Second opinion / review
- Final investment judgment & implications
Resources
References
references/headline_event_patterns.md- Event patterns and market reactionsreferences/sector_sensitivity_matrix.md- Sector sensitivity matrixreferences/scenario_playbooks.md- Scenario-construction templates
Agents
scenario-analyst- Primary scenario analysisstrategy-reviewer- Second opinion / review
Important Notes
Language
- All analysis and output are in English
- Stock tickers remain in their standard (English) symbols
Target Market
- Stock selection is US-listed equities only
- ADRs included
Time Horizon
- Scenarios target 18 months
- Described in 3 phases: 0-6 months / 6-12 months / 12-18 months
Probability Allocation
- Base + Bull + Bear = 100%
- Each scenario's probability is described with its rationale
Second Opinion
- Mandatory (always invoke strategy-reviewer)
- Review results are reflected in the final judgment
Output Location (Important)
- Always save under the
reports/directory - Path:
reports/scenario_analysis_<topic>_YYYYMMDD.md - Example:
reports/scenario_analysis_fed_rate_hike_20260104.md - Create the
reports/directory if it does not exist - Must not save directly to the project root
Quality Checklist
Confirm the following before finalizing the report:
- Is the headline parsed correctly?
- Is the event type classification appropriate?
- Do the 3 scenario probabilities sum to 100%?
- Are the 1st/2nd/3rd-order impacts logically connected?
- Is the stock selection backed by concrete rationale?
- Is the strategy-reviewer review included?
- Is the final judgment reflecting the review documented?
- Is the report saved to the correct path?

