market-news-analyst▌
tradermonty/claude-trading-skills · updated Apr 8, 2026
MDX-style export adds YAML metadata + attribution linking explainx.ai and this canonical listing URL.
Automated analysis of market-moving news from the past 10 days with impact-ranked reporting.
- ›Collects news across six categories (monetary policy, inflation, earnings, geopolitical, commodities, corporate) using WebSearch and WebFetch, prioritizing Tier 1 sources
- ›Ranks events by impact score combining price movement magnitude, breadth across asset classes, and forward-looking significance
- ›Analyzes multi-asset reactions (equities, bonds, commodities, currencies) and compares actual ma
Market News Analyst
Overview
This skill enables comprehensive analysis of market-moving news events from the past 10 days, focusing on their impact on US equity markets and commodities. The skill automatically collects news from trusted sources using WebSearch and WebFetch tools, evaluates market impact magnitude, analyzes actual market reactions, and produces structured English reports ranked by market impact significance.
Prerequisites
- Tools: WebSearch and WebFetch tools must be available for news collection
- API Keys: None required (uses built-in web search capabilities)
- Knowledge: Familiarity with financial markets terminology is helpful but not required
Output
This skill produces conversational guidance during the analysis session. When the full workflow is executed, Claude generates a comprehensive Markdown report (see Step 6 for format) that can be saved to the reports/ directory upon user request. No files are generated automatically; output is presented in the conversation.
When to Use This Skill
Use this skill when:
- User requests analysis of recent major market news (past 10 days)
- User wants to understand market reactions to specific events (FOMC decisions, earnings, geopolitical)
- User needs comprehensive market news summary with impact assessment
- User asks about correlations between news events and commodity price movements
- User requests analysis of how central bank policy announcements affected markets
Example user requests:
- "Analyze the major market news from the past 10 days"
- "How did the latest FOMC decision impact the market?"
- "What were the most important market-moving events this week?"
- "Analyze recent geopolitical news and commodity price reactions"
- "Review mega-cap tech earnings and their market impact"
Analysis Workflow
Follow this structured 6-step workflow when analyzing market news:
Step 1: News Collection via WebSearch/WebFetch
Objective: Gather comprehensive news from the past 10 days covering major market-moving events.
Search Strategy:
Execute parallel WebSearch queries covering different news categories:
Monetary Policy:
- Search: "FOMC meeting past 10 days", "Federal Reserve interest rate", "ECB policy decision", "Bank of Japan"
- Target: Central bank decisions, forward guidance changes, inflation commentary
Inflation/Economic Data:
- Search: "CPI inflation report [current month]", "jobs report NFP", "GDP data", "PPI producer prices"
- Target: Major economic data releases and surprises
Mega-Cap Earnings:
- Search: "Apple earnings [current quarter]", "Microsoft earnings", "NVIDIA earnings", "Amazon earnings", "Tesla earnings", "Meta earnings", "Google earnings"
- Target: Results, guidance, market reactions for largest companies
Geopolitical Events:
- Search: "Middle East conflict oil prices", "Ukraine war", "US China tensions", "trade war tariffs"
- Target: Conflicts, sanctions, trade disputes affecting markets
Commodity Markets:
- Search: "oil prices news past week", "gold prices", "OPEC meeting", "natural gas prices", "copper prices"
- Target: Supply disruptions, demand shifts, price movements
Corporate News:
- Search: "major M&A announcement", "bank earnings", "tech sector news", "bankruptcy", "credit rating downgrade"
- Target: Large corporate events beyond mega-caps
Recommended News Sources (Priority Order):
- Official sources: FederalReserve.gov, SEC.gov (EDGAR), Treasury.gov, BLS.gov
- Tier 1 financial news: Bloomberg, Reuters, Wall Street Journal, Financial Times
- Specialized: CNBC (real-time), MarketWatch (summaries), S&P Global Platts (commodities)
Search Execution:
- Use WebSearch for broad topic searches
- Use WebFetch for specific URLs from official sources or major news outlets
- Collect publication dates to ensure news is within 10-day window
- Capture: Event date, source, headline, key details, market context (pre-market, trading hours, after-hours)
Filtering Criteria:
- Focus on Tier 1 market-moving events (see references/market_event_patterns.md)
- Prioritize news with clear market impact (price moves, volume spikes)
- Exclude: Stock-specific small-cap news, minor product updates, routine filings
Think in English throughout collection process. Document each significant news item with:
- Date and time
- Event type (monetary policy, earnings, geopolitical, etc.)
- Source reliability tier
- Initial market reaction (if observable)
Step 2: Load Knowledge Base References
Objective: Access domain expertise to inform impact assessment.
Load relevant reference files based on collected news types:
Always Load:
references/market_event_patterns.md- Comprehensive patterns for all major event typesreferences/trusted_news_sources.md- Source credibility assessment
Conditionally Load (Based on News Collected):
If monetary policy news found:
- Focus on: market_event_patterns.md → Central Bank Monetary Policy Events section
- Key frameworks: Interest rate hike/cut reactions, QE/QT impacts, hawkish/dovish tone
If geopolitical events found:
- Load:
references/geopolitical_commodity_correlations.md - Focus on: Energy Commodities, Precious Metals, regional frameworks matching event
If mega-cap earnings found:
- Load:
references/corporate_news_impact.md - Focus on: Specific company sections, sector contagion patterns
If commodity news found:
- Load:
references/geopolitical_commodity_correlations.md - Focus on: Specific commodity sections (Oil, Gold, Copper, etc.)
Knowledge Integration: Compare collected news against historical patterns to:
- Predict expected market reactions
- Identify anomalies (market reacted differently than historical pattern)
- Assess whether reaction was typical magnitude or outsized
- Determine if contagion occurred as expected
Step 3: Impact Magnitude Assessment
Objective: Rank each news event by market impact significance.
Impact Assessment Framework:
For each news item, evaluate across three dimensions:
1. Asset Price Impact (Primary Factor):
Measure actual or estimated price movements:
Equity Markets:
-
Index-level: S&P 500, Nasdaq 100, Dow Jones
- Severe: ±2%+ in day
- Major: ±1-2%
- Moderate: ±0.5-1%
- Minor: ±0.2-0.5%
- Negligible: <0.2%
-
Sector-level: Specific sector ETFs
- Severe: ±5%+
- Major: ±3-5%
- Moderate: ±1-3%
- Minor: <1%
-
Stock-specific: Individual mega-caps
- Severe: ±10%+ (and index weight causes index move)
- Major: ±5-10%
- Moderate: ±2-5%
Commodity Markets:
-
Oil (WTI/Brent):
- Severe: ±5%+
- Major: ±3-5%
- Moderate: ±1-3%
-
Gold:
- Severe: ±3%+
- Major: ±1.5-3%
- Moderate: ±0.5-1.5%
-
Base Metals (Copper, etc.):
- Severe: ±4%+
- Major: ±2-4%
- Moderate: ±1-2%
Bond Markets:
- 10-Year Treasury Yield:
- Severe: ±20bps+ in day
- Major: ±10-20bps
- Moderate: ±5-10bps
Currency Markets:
- USD Index (DXY):
- Severe: ±1.5%+
- Major: ±0.75-1.5%
- Moderate: ±0.3-0.75%
2. Breadth of Impact (Multiplier):
Assess how many markets/sectors affected:
-
Systemic (3x multiplier): Multiple asset classes, global markets
- Examples: FOMC surprise, banking crisis, major war outbreak
-
Cross-Asset (2x multiplier): Equities + commodities, or equities + bonds
- Examples: Inflation surprise, geopolitical supply shock
-
Sector-Wide (1.5x multiplier): Entire sector or related sectors
- Examples: Tech earnings cluster, energy policy announcement
-
Stock-Specific (1x multiplier): Single company (unless mega-cap with index impact)
- Examples: Individual company earnings, M&A
3. Forward-Looking Significance (Modifier):
Consider future implications:
-
Regime Change (+50%): Fundamental market structure shift
- Examples: Fed pivot from hiking to cutting, major geopolitical realignment
-
Trend Confirmation (+25%): Reinforces existing trajectory
- Examples: Consecutive strong inflation prints, sustained earnings beats
-
Isolated Event (0%): One-off with limited forward signal
- Examples: Single data point within range, company-specific issue
-
Contrary Signal (-25%): Contradicts prevailing narrative
- Examples: Good news ignored by market, bad news rallied
Impact Score Calculation:
Impact Score = (Price Impact Score × Breadth Multiplier) + Forward-Looking Modifier
Price Impact Score:
- Severe: 10 points
- Major: 7 points
- Moderate: 4 points
- Minor: 2 points
- Negligible: 1 point
Example Calculations:
FOMC 75bps Rate Hike (hawkish tone):
- Price Impact: S&P 500 -2.5% (Severe = 10 points)
- Breadth: Systemic (equities, bonds, USD, commodities all moved) = 3x
- Forward: Trend confirmation (ongoing tightening) = +25%
- Score: (10 × 3) × 1.25 = 37.5
NVIDIA Earnings Beat:
- Price Impact: NVDA +15%, Nasdaq +1.5% (Severe = 10 points)
- Breadth: Sector-wide (semis, tech broadly) = 1.5x
- Forward: Trend confirmation (AI demand) = +25%
- Score: (10 × 1.5) × 1.25 = 18.75
Geopolitical Flare-up (Middle East):
- Price Impact: Oil +8%, S&P -1.2% (Severe = 10 points)
- Breadth: Cross-asset (oil, equities, gold) = 2x
- Forward: Isolated event (no escalation) = 0%
- Score: (10 × 2) × 1.0 = 20
Single Stock Earnings (Non-Mega-Cap):
- Price Impact: Stock +12%, no index impact (Major = 7 points)
- Breadth: Stock-specific = 1x
- Forward: Isolated = 0%
- Score: (7 × 1) × 1.0 = 7
Ranking: After scoring all news items, rank from highest to lowest impact score. This determines report ordering.
Step 4: Market Reaction Analysis
Objective: Analyze how markets actually responded to each event.
For each significant news item (Impact Score >5), conduct detailed reaction analysis:
Immediate Reaction (Intraday):
- Direction: Positive, negative, mixed
- Magnitude: Align with price impact categories
- Timing: Pre-market, during trading, after-hours
- Volatility: VIX movement, bid-ask spreads
Multi-Asset Response:
Equities:
- Index performance (S&P 500, Nasdaq, Dow, Russell 2000)
- Sector rotation (which sectors outperformed/underperformed)
- Individual stock moves (mega-caps, relevant companies)
- Growth vs Value, Large vs Small Cap divergences
Fixed Income:
- Treasury yields (2Y, 10Y, 30Y)
- Yield curve shape (steepening, flattening, inversion)
- Credit spreads (IG, HY)
- TIPS breakevens (inflation expectations)
Commodities:
- Energy: Oil (WTI, Brent), Natural Gas
- Precious Metals: Gold, Silver
- Base Metals: Copper, Aluminum (if relevant)
- Agricultural: Wheat, Corn, Soybeans (if relevant)
Currencies:
- USD Index (DXY)
- EUR/USD, USD/JPY, GBP/USD
- Emerging market currencies
- Safe havens (JPY, CHF)
Derivatives:
- VIX (volatility index)
- Options activity (put/call ratio, unusual volume)
- Futures positioning
Pattern Comparison:
Compare observed reaction against expected pattern from knowledge base:
-
Consistent: Reaction matched historical pattern
- Example: Fed hike → Tech stocks down, USD up (as expected)
-
Amplified: Reaction exceeded typical pattern
- Example: Inflation print +0.3% above consensus → Selloff 2x typical
- Investigate: Positioning, sentiment, cumulative factors
-
Dampened: Reaction less than historical pattern
- Example: Geopolitical event → Oil barely moved
- Investigate: Already priced in, other offsetting factors
-
Inverse: Reaction opposite of historical pattern
- Example: Good news ignored, bad news rallied
- Investigate: "Good news is bad news" dynamics, Fed pivot hopes
Anomaly Identification:
Flag reactions that deviate significantly from patterns:
- Market shrugged off typically market-moving news
- Overreaction to typically minor news
- Contagion failed to spread as expected
- Safe havens didn't work (correlations broke)
Sentiment Indicators:
- Risk-On vs Risk-Off: Which regime dominated
- Positioning: Evidence of crowded trades unwinding
- Momentum: Follow-through in subsequent sessions or reversal
Step 5: Correlation and Causation Assessment
Objective: Distinguish direct impacts from coincidental timing.
Multi-Event Analysis:
When multiple significant events occurred in the 10-day period, assess interactions:
Reinforcing Events:
- Same directional impact
- Example: Hawkish FOMC + hot CPI → Both bearish for equities, amplified move
- Combined impact often non-linear (greater than sum of parts)
Offsetting Events:
- Opposite directional impacts
- Example: Strong earnings (positive) + geopolitical tensions (negative) → Muted net reaction
- Identify which factor dominated
Sequential Events:
- One event set up reaction to next
- Example: First rate hike modest reaction, second rate hike severe (cumulative tightening concerns)
- Path dependence matters
Coincidental Timing:
- Events unrelated but occurred simultaneously
- Difficult to isolate individual impacts
- Note uncertainty in attribution
Geopolitical-Commodity Correlations:
For geopolitical events, specifically analyze commodity market reactions using geopolitical_commodity_correlations.md:
Energy:
- Map conflict/sanction to supply disruption risk
- Assess actual vs feared supply impact
- Duration: Temporary spike vs sustained elevation
Precious Metals:
- Safe-haven flows vs real rate drivers
- Gold response to risk-off events
- Central bank buying implications
Industrial Metals:
- Demand destruction from economic slowdown fears
- Supply chain disruptions
- China factor in copper, aluminum
Agriculture:
- Black Sea grain exports (Russia-Ukraine)
- Weather overlays
- Food security policy responses
Transmission Mechanisms:
Trace how news impacts flowed through markets:
Direct Channel:
- News → Immediate asset price reaction
- Example: OPEC cuts → Oil prices up immediately
Indirect Channels:
- News → Economic impact → Asset prices
- Example: Rate hike → Mortgage rates up → Housing slows → Homebuilder stocks down
Sentiment Channel:
- News → Risk appetite shift → Broad asset reallocation
- Example: Banking crisis → Flight to quality → Treasuries rally, stocks sell
Feedback Loops:
- Initial reaction creates secondary effects
- Example: Stock selloff → Margin calls → Forced selling → Deeper selloff
Step 6: Report Generation
Objective: Create structured English Markdown report ranked by market impact.
Report Structure:
# Market News Analysis Report - [Date Range]
## Executive Summary
[3-4 sentences covering:]
- Period analyzed (specific dates)
- Number of significant events identified
- Dominant market theme/regime (risk-on/risk-off, sector rotation)
- Top 1-2 highest-impact events
## Market Impact Rankings
[Table format, sorted by Impact Score descending]
| Rank | Event | Date | Impact Score | Asset Classes Affected | Market Reaction |
|------|-------|------|--------------|------------------------|-----------------|
| 1 | [Event] | [Date] | [Score] | [Equities, Commodities, etc.] | [Brief reaction] |
| 2 | ... | ... | ... | ... | ... |
---
## Detailed Event Analysis
[For each event in rank order, provide comprehensive analysis]
### [Rank]. [Event Name] (Impact Score: [X])
**Event Date:** [Date, Time]
**Event Type:** [MonetHow to use market-news-analyst on Cursor
AI-first code editor with Composer
Prerequisites
Before installing skills in Cursor, ensure your development environment meets these requirements:
- ›Cursor installed and configured on your development machine
- ›Node.js version 16.0+ with npm package manager (verify with
node --version) - ›Active project directory or workspace where you want to add market-news-analyst
Execute installation command
Execute the skills CLI command in your project's root directory to begin installation:
The skills CLI fetches market-news-analyst from GitHub repository tradermonty/claude-trading-skills and configures it for Cursor.
Select Cursor when prompted
The CLI will show a list of available agents. Use arrow keys to navigate and space to select Cursor:
Verify installation
Confirm successful installation by checking the skill directory location:
Reload or restart Cursor to activate market-news-analyst. Access the skill through slash commands (e.g., /market-news-analyst) or your agent's skill management interface.
Security & Verification Notice
We perform automated surface-level scans (Gen AI Scanner, Socket, Snyk) during installation. These checks detect common vulnerabilities but do not guarantee complete security. Always review skill source code and verify the publisher's reputation before production use.
Skills execute code in your development environment. Always verify the publisher's identity, review recent commits, and test in isolated environments before production deployment.
List & Monetize Your Skill
Submit your Claude Code skill and start earning
Use Cases▌
User Story & Requirements Generation
Create detailed user stories, acceptance criteria, and feature specs
Example
Generate user stories for 'password reset feature' with acceptance criteria, edge cases, and test scenarios
Reduce spec writing time by 50%, ensure comprehensive coverage
Competitive Analysis
Research competitors, compare features, identify gaps
Example
Analyze 5 competitor products, create feature comparison matrix, suggest differentiation opportunities
Complete competitive research in 2 hours instead of 2 days
Roadmap Prioritization
Evaluate features using frameworks (RICE, ICE, Kano) and create prioritized backlogs
Example
Score 20 feature ideas using RICE framework, generate prioritized roadmap with rationale
Make data-driven prioritization decisions faster
Stakeholder Communication
Draft PRDs, status updates, and stakeholder presentations
Example
Create executive summary of Q3 roadmap, monthly progress report, feature launch announcement
Save 3-5 hours/week on communication overhead
Implementation Guide▌
Prerequisites
- ›Claude Desktop or compatible AI client
- ›Access to product documentation and roadmap tools (Jira, Notion, etc.)
- ›Understanding of product management frameworks (RICE, Jobs-to-be-Done, etc.)
- ›Stakeholder contact information and communication channels
Time Estimate
30-60 minutes to see productivity improvements
Installation Steps
- 1.Install product management skill
- 2.Start with user story generation for known feature
- 3.Progress to competitive analysis: research 2-3 competitors
- 4.Use for roadmap prioritization: apply RICE/ICE scoring
- 5.Draft stakeholder communications and refine based on feedback
- 6.Build template library for recurring PM tasks
- 7.Share effective prompts with product team
Common Pitfalls
- ⚠Not validating competitive research—verify facts before sharing
- ⚠Accepting user stories without involving engineering team
- ⚠Over-relying on frameworks without qualitative judgment
- ⚠Not customizing outputs to company culture and communication style
- ⚠Skipping stakeholder validation of generated requirements
Best Practices▌
✓ Do
- +Validate research and competitive analysis with real data
- +Collaborate with engineering when generating technical requirements
- +Customize frameworks and templates to your company context
- +Use skill for first drafts, refine with stakeholder input
- +Document successful prompt patterns for PM tasks
- +Combine AI efficiency with human judgment and intuition
✗ Don't
- −Don't publish competitive analysis without fact-checking
- −Don't finalize user stories without engineering review
- −Don't make prioritization decisions solely on AI scoring
- −Don't skip customer validation of generated requirements
- −Don't ignore company-specific context and culture
💡 Pro Tips
- ★Provide context: company goals, constraints, customer feedback
- ★Ask for alternatives: 'Show 3 ways to prioritize this roadmap'
- ★Request stakeholder-specific formatting: 'Executive summary vs. engineering spec'
- ★Use skill for 70% generation + 30% customization to company needs
When to Use This▌
✓ Use When
Use for user story writing, competitive research, roadmap prioritization, stakeholder communication, and PRD drafting. Best for reducing repetitive documentation and research work.
✗ Avoid When
Avoid for strategic product vision (requires deep customer empathy), pricing decisions (needs market and financial expertise), or when face-to-face customer discovery is more valuable than speed.
Learning Path▌
- 1Basic: user stories, feature specs, status updates
- 2Intermediate: competitive analysis, prioritization frameworks, PRDs
- 3Advanced: product strategy, go-to-market planning, OKR setting
- 4Expert: product vision, market positioning, business model innovation
Discussion
Product Hunt–style comments (not star reviews)- No comments yet — start the thread.
Ratings
4.6★★★★★44 reviews- ★★★★★Min Taylor· Dec 28, 2024
market-news-analyst has been reliable in day-to-day use. Documentation quality is above average for community skills.
- ★★★★★Carlos Diallo· Dec 24, 2024
Useful defaults in market-news-analyst — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.
- ★★★★★Hassan Gupta· Dec 4, 2024
Keeps context tight: market-news-analyst is the kind of skill you can hand to a new teammate without a long onboarding doc.
- ★★★★★Meera Sethi· Nov 23, 2024
market-news-analyst is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.
- ★★★★★Carlos Ghosh· Nov 19, 2024
market-news-analyst reduced setup friction for our internal harness; good balance of opinion and flexibility.
- ★★★★★Aarav Desai· Nov 19, 2024
Solid pick for teams standardizing on skills: market-news-analyst is focused, and the summary matches what you get after install.
- ★★★★★Ama Reddy· Nov 15, 2024
We added market-news-analyst from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.
- ★★★★★Hassan Desai· Oct 14, 2024
market-news-analyst fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.
- ★★★★★Alexander Haddad· Oct 10, 2024
I recommend market-news-analyst for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.
- ★★★★★Jin Iyer· Oct 10, 2024
We added market-news-analyst from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.
showing 1-10 of 44