scenario-analyzer — Claude Code skill: 18-month scenario analysis
Turns a news headline into three 18-month scenarios, with sector impacts and a stock list, then has a second agent review it.
npx skills add tradermonty/claude-trading-skills --skill scenario-analyzer -a claude-codeWhat scenario-analyzer does
Give the skill a headline like a central bank rate move or a new tariff, and it works out the medium-term picture. First it parses the headline into entities and numbers, then classifies the event: monetary policy, geopolitics, regulation, technology, commodities, or corporate and M&A. From there it loads references on event patterns, sector sensitivity, and scenario templates.
Analysis runs in two passes. The scenario-analyst subagent does the primary work: it pulls recent news through WebSearch, builds Base/Bull/Bear scenarios with probabilities summing to 100%, sorts sector impacts into first, second and third order, and picks US-listed stocks. Then strategy-reviewer goes over the result, flagging missed sectors, questioning the probability split, and calling out optimism or pessimism bias.
No API keys or MCP servers are involved; WebSearch and WebFetch cover the research. The catch is that both subagents have to be reachable through the Task tool, otherwise the skill has nothing to call. The finished English report lands in reports/scenario_analysis_<topic>_YYYYMMDD.md.
What it helps with
- break a news headline into three scenarios with probabilities
- map an event's sector impact across first, second and third order
- get a stock list split by positive and negative exposure
- catch optimism or pessimism bias in your own analysis
- save a scenario report to a Markdown file
Example prompts for the agent
- /scenario-analyzer "Fed raises 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"
How to install scenario-analyzer
1Skills CLI (Vercel)
npx skills add tradermonty/claude-trading-skills --skill scenario-analyzer -a claude-code2Manually: put the files in place
~/.claude/skills/scenario-analyzer/SKILL.mdCopy the whole skill folder; for one project use .claude/skills/scenario-analyzer/
1Skills CLI (Vercel)
npx skills add tradermonty/claude-trading-skills --skill scenario-analyzer -a codex2Manually: put the files in place
.agents/skills/scenario-analyzer/SKILL.mdFor all projects use ~/.agents/skills/
1Skills CLI (Vercel)
npx skills add tradermonty/claude-trading-skills --skill scenario-analyzer -a cursor2Manually: put the files in place
.cursor/skills/scenario-analyzer/SKILL.mdCursor also reads .agents/skills/ and .claude/skills/
1GitHub CLI
gh skill install tradermonty/claude-trading-skills scenario-analyzer2Manually: put the files in place
.github/skills/scenario-analyzer/SKILL.md1Skills CLI (Vercel)
npx skills add tradermonty/claude-trading-skills --skill scenario-analyzer -a gemini-cli2Platform CLI
gemini skills install https://github.com/tradermonty/claude-trading-skills --path skills/scenario-analyzerManually: put the files in place
.devin/skills/scenario-analyzer/SKILL.mdThe legacy .windsurf/skills/ path still works
Skills CLI (Vercel)
npx skills add tradermonty/claude-trading-skills --skill scenario-analyzer -a opencodeClaude.ai
Zip the folder and upload it in Settings → Capabilities → Skills
Step by step, with commands for each platform: How to install skills in Claude Code: five ways
Questions about scenario-analyzer
How do I install scenario-analyzer in Claude?
Run npx skills add tradermonty/claude-trading-skills --skill scenario-analyzer -a claude-code. The skill ends up at ~/.claude/skills/scenario-analyzer/SKILL.md.
What does scenario-analyzer do?
It builds 18-month scenarios from a news headline: Base, Bull and Bear cases, sector impacts, and a stock list. A reviewer subagent then checks the output, and the report is saved to a file.
What does scenario-analyzer need to run?
No API keys or MCP servers — research goes through WebSearch and WebFetch. The scenario-analyst and strategy-reviewer subagents must be available via the Task tool.
Source text
SKILL.md · MIT
---
name: scenario-analyzer
description: |
Skill that analyzes 18-month scenarios from a news headline.
Runs the primary analysis with the scenario-analyst agent and obtains a
second opinion with the strategy-reviewer agent.
Generates a comprehensive English report covering 1st/2nd/3rd-order
impacts, recommended stocks, and a critical review.
Example: /scenario-analyzer "Fed raises rates by 50bp"
Triggers: news analysis, scenario analysis, 18-month outlook,
medium-to-long-term investment strategy
---
# 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.
1. **Headline check**
- Confirm a headline was passed as an argument
- If not provided, ask the user for input
2. **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 reactions
- `sector_sensitivity_matrix.md`: Event × sector impact-magnitude matrix
- `scenario_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:**
1. Fill in the blind spots raised in the review
2. Adjust the probability allocation (if needed)
3. Make the final judgment accounting for bias
4. 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
1. Create the `reports/` directory if it does not exist
2. Save as `scenario_analysis_<topic>_YYYYMMDD.md` (e.g., `scenario_analysis_venezuela_20260104.md`)
3. Notify the user that the save completed
4. **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 reactions
- `references/sector_sensitivity_matrix.md` - Sector sensitivity matrix
- `references/scenario_playbooks.md` - Scenario-construction templates
### Agents
- `scenario-analyst` - Primary scenario analysis
- `strategy-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?
© tradermonty · MIT · tradermonty/claude-trading-skills