- Skill ID
- tradermonty/claude-trading-skills/scenario-analyzer
- Publisher
- tradermonty
- Repository
- claude-trading-skills
- Installs
- 0
- Files
- 5
- Synced
- Sep 23, 2026
Open any RiverX project, open the Skills panel in the chat, and search for this identifier. The files are fetched from the source repository at install time.
tradermonty/claude-trading-skills/scenario-analyzerInstalls these files- SKILL.md
- references/headline_event_patterns.md
- references/scenario_playbooks.md
- references/sector_sensitivity_matrix.md
- scripts/tests/test_skill_contract.py
What this skill tells the agent
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.mdReference 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 EnglishExpected 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
# 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-reviewerStep 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
More from tradermonty
Use this skill in a project
Open any RiverX project, search the Skills panel for tradermonty/claude-trading-skills/scenario-analyzer, and install it in one click.
