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Analyze news headlines, policy announcements, or geopolitical events to build 18-month probabilistic scenarios for Indian markets. Use when the user provides a headline or asks about the market impact of RBI policy, government announcements, global events, budget, or

shell
$ npx -y skills add ajeeshworkspace/indian-trading-skills --skill scenario-analyzer --agent claude-code

How it fires

How this skill gets triggered: by you, by Claude, or both.

  • Fires itselfAuto-invocation. Claude auto-loads it when your prompt matches the work.
  • You can call itInvoke it directly when you want it.
  • Slash command/scenario-analyzer
How auto-invocation works

Context preview

The summary Claude sees to decide when to auto-load this skill.

Analyze news headlines, policy announcements, or geopolitical events to build 18-month probabilistic scenarios for Indian markets. Use when the user provides a headline or asks about the market impact of RBI policy, government announcements, global events, budget, or

SKILL.md

scenario-analyzer.SKILL.md
name: scenario-analyzer
description: Analyze news headlines, policy announcements, or geopolitical events to build 18-month probabilistic scenarios for Indian markets. Use when the user provides a headline or asks about the market impact of RBI policy, government announcements, global events, budget, or sector-specific news on NSE/BSE stocks.

Scenario Analyzer (India Markets)

Overview

This skill takes a news headline or event and builds probabilistic 18-month scenarios with cascading 1st, 2nd, and 3rd order sector impacts and specific stock recommendations for the Indian market.

Architecture

Skill (Orchestrator)
├── Phase 1: Preparation
│   ├── Headline parsing (keywords, entities, actions, numbers)
│   ├── Event classification
│   └── Load references
├── Phase 2: Analysis
│   ├── Collect related news (past 2 weeks via WebSearch)
│   ├── Build 3 scenarios (Base/Bull/Bear, probabilities sum to 100%)
│   ├── Map 1°/2°/3° sector impacts
│   └── Identify 3-5 positive + 3-5 negative impact stocks
└── Phase 3: Report Generation
    ├── Compile findings
    ├── Assess scenario probability distribution
    └── Save report

Event Classification

Classify the headline into one of these categories:

| Category | Indian Context Examples | |----------|----------------------| | **Monetary Policy** | RBI rate decision, CRR/SLR change, liquidity measures | | **Fiscal Policy** | Union Budget, GST changes, PLI schemes, disinvestment | | **Geopolitical** | India-China border, India-Pakistan, Russia-Ukraine, Middle East | | **Commodity** | Crude oil shock, gold prices, metal tariffs, food inflation | | **Regulatory** | SEBI rules, RBI NPA norms, telecom spectrum, pharma FDA | | **Corporate** | Major M&A, earnings surprise, promoter pledging, fraud | | **Global Macro** | Fed rate decision, US recession, China slowdown, tariffs | | **Weather/Agriculture** | Monsoon forecast, crop damage, food prices | | **Elections/Political** | State elections, central govt policy shifts |

Workflow

Phase 1: Preparation

1. **Parse the Headline**

  • Extract key entities (companies, sectors, countries, institutions)
  • Identify the action (increase, decrease, ban, approve, delay)
  • Note any numbers (rate changes, ₹ amounts, percentages)
  • Classify the event type

2. **Load References**

   Read: references/headline_event_patterns.md
   Read: references/sector_sensitivity_matrix.md
   Read: references/scenario_playbooks.md

Phase 2: Analysis

3. **Collect Context**

  • Use WebSearch to find related news from the past 2 weeks
  • Identify any pre-existing trends or expectations
  • Note market's initial reaction if available

4. **Build 3 Scenarios**

For each scenario:

  • **Name**: Descriptive title
  • **Probability**: Must sum to 100% across all 3
  • **Timeline**: 3 phases (0-6 months, 6-12 months, 12-18 months)
  • **Description**: What unfolds in each phase
  • **Key Assumptions**: What must hold true

Typical structure:

  • **Base Case (40-55%)**: Most likely outcome given current trajectory
  • **Bull Case (20-35%)**: Optimistic scenario with positive catalysts
  • **Bear Case (15-30%)**: Pessimistic scenario with adverse developments

5. **Map Sector Impacts**

For each scenario, assess impacts using the sector sensitivity matrix:

| Order | Definition | Example (RBI Rate Cut) | |-------|-----------|----------------------| | 1st | Direct, immediate | Banks: NIM compression, Housing: demand boost | | 2nd | Indirect, 3-6 months | Auto: loan demand, Real estate: prices | | 3rd | Tertiary, 6-18 months | Cement: construction demand, Durables: consumer spending |

Use NSE sectoral indices:

  • Nifty Bank, Nifty IT, Nifty Pharma, Nifty Auto, Nifty FMCG
  • Nifty Metal, Nifty Realty, Nifty Energy, Nifty Infra
  • Nifty PSU Bank, Nifty Private Bank, Nifty Financial Services

6. **Identify Stock Impacts**

For each scenario:

  • 3-5 stocks that benefit most (positive impact)
  • 3-5 stocks that suffer most (negative impact)

For each stock, provide:

  • Ticker (NSE symbol)
  • Current price (use broker MCP `get_ltp` — Groww or Zerodha Kite — if available)
  • Impact channel (why this stock is affected)
  • Magnitude estimate (High/Medium/Low)

Phase 3: Report Generation

7. **Generate Report**

Save as `reports/scenario_analysis_<topic>_YYYYMMDD.md` with sections:

1. **Related News** (5-10 recent articles with sources) 2. **Scenario Overview** (3 scenarios with probabilities) 3. **Timeline** (0-6m, 6-12m, 12-18m phases for base case) 4. **Sector Impact Matrix** (1°/2°/3° impacts per sector) 5. **Positive Impact Stocks** (3-5 with rationale) 6. **Negative Impact Stocks** (3-5 with rationale) 7. **Investment Implications** (actionable takeaways) 8. **Risk to Scenarios** (what could shift probabilities) 9. **Disclaimer**

Quality Standards

  • All probabilities must sum to 100%
  • Every impact claim must have a causal chain (event → mechanism → impact)
  • Stock picks must include the impact channel, not just "will benefit"
  • Consider second-order effects (e.g., rate cut → weak INR → IT sector benefit)
  • Flag any confirmation bias in scenario construction
  • Include both sectors that benefit AND those that lose

Example Usage

User: "RBI cuts repo rate by 25 bps to 6%"

Analyst:
1. Classification: Monetary Policy
2. Key entities: RBI, repo rate, 25 bps, 6%
3. Collects recent RBI commentary and market expectations
4. Scenarios:
   - Base (50%): One more cut expected → banks pass on, housing demand rises
   - Bull (30%): Cycle of 75-100 bps cuts → strong credit growth, equity rally
   - Bear (20%): Global inflation returns → RBI pauses → rate-sensitive sell-off
5. 1° impacts: Banks, NBFCs, Housing Finance, Auto
6. 2° impacts: Real Estate, Consumer Durables
7. 3° impacts: Cement, Infrastructure
8. Stock picks: HDFCBANK, BAJFINANCE, GODREJPROP (positive); IT exporters if INR we
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Turn Claude into your Indian market research analyst. 10 specialized skills covering NSE/BSE equities, F&O derivatives, institutional flows, market breadth, live news tracking, and weekly trade planning — all built for Indian markets.

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