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scenario-analyzer

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

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含まれるファイル(5)

  • SKILL.md10.4 KB
  • references/headline_event_patterns.md7.9 KB
  • references/scenario_playbooks.md8.6 KB
  • references/sector_sensitivity_matrix.md9.5 KB
  • scripts/tests/test_skill_contract.py1.4 KB

SKILL.md(原文)

インストールする前に、エージェントに与えられる指示の中身を確認できます。

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:

CategoryExamples
Monetary PolicyFOMC, ECB, BOJ, rate hike, rate cut, QE/QT
GeopoliticsWar, sanctions, tariffs, trade friction
Regulation & PolicyEnvironmental regulation, financial regulation, antitrust
TechnologyAI, EV, renewables, semiconductors
CommoditiesCrude oil, gold, copper, agricultural products
Corporate & M&AAcquisitions, 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

# 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:

FileFormatDescription
reports/scenario_analysis_<topic>_YYYYMMDD.mdMarkdownComprehensive 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?

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