scenario-analyzer
Skill75 starsChanged 8 months agoMITView on GitHub
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.
1 other project uses a version of this.
Adopted by
Most recently taken up by
- IngAs8/ClaudeSkilltheir own version, first seen Sep 28, 2026
Other versions1 project uses a version of this.
Word for word · 0
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Edited · 0
None found.
Wrote their own version · 1
- IngAs8/ClaudeSkill★ 0same name
How matches are found. Word for word: the exact same text. Edited: shares passages with this file (“99% same” means 99% of its five-word phrases also appear here; 10% or more counts). Their own version: similar meaning, or, weakest, the same name. We can’t tell which project had it first. Projects are counted among the 200 most-starred candidates, and mentions are links to the repository we found, up to 50 per site, so both counts are a floor.
In this repository9 other files it gives its agents.
- backtest-expertSkill
- fii-dii-flow-trackerSkill
- india-market-breadthSkill
- india-news-trackerSkill
- india-stock-analysisSkill
- nse-vcp-screenerSkill
- options-strategy-advisorSkill
- technical-analystSkill
- weekly-fno-trade-plannerSkill
The file
We split this skill into the rules it gives an agent
6 rules. About 0 are common, 6 are distinctive, and 0 are very specific to this project.
≈0
Common · estimate
Many files like this have a rule of this kind.
≈6
Distinctive · estimate
This author's own choices. Worth a look.
0
Very specific
Tied to their project's names, files or tools. Probably skip.
- Common
- Distinctive
- Very specific
- Distinctive: line 67
Use WebSearch to find related news from the past 2 weeks
- Distinctive: line 75
Probability: Must sum to 100% across all 3
- Distinctive: line 95
Use NSE sectoral indices:
- Distinctive: line 130
All probabilities must sum to 100%
- Distinctive: line 131
Every impact claim must have a causal chain (event → mechanism → impact)
- Distinctive: line 133
Consider second-order effects (e.g., rate cut → weak INR → IT sector benefit)
≈ “Common” is an estimate: at least 1 in 5 of the 350,495 skill files we read have a rule of the same kind, not the same words. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.
Files
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 reportEvent 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
- 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
- Load References
Read: references/headline_event_patterns.md Read: references/sector_sensitivity_matrix.md Read: references/scenario_playbooks.md
Phase 2: Analysis
- 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
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
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
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
Generate Report
Save as
reports/scenario_analysis_<topic>_YYYYMMDD.mdwith sections:- Related News (5-10 recent articles with sources)
- Scenario Overview (3 scenarios with probabilities)
- Timeline (0-6m, 6-12m, 12-18m phases for base case)
- Sector Impact Matrix (1°/2°/3° impacts per sector)
- Positive Impact Stocks (3-5 with rationale)
- Negative Impact Stocks (3-5 with rationale)
- Investment Implications (actionable takeaways)
- Risk to Scenarios (what could shift probabilities)
- 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 weakensResources
references/headline_event_patterns.md
Historical Indian market event patterns and reactions.
references/sector_sensitivity_matrix.md
Event type × NSE sector impact matrix.
references/scenario_playbooks.md
Scenario construction templates with Indian market context.
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