This skill helps you systematically analyze US stock market sentiment, determine whether the current market is in a state of greed or fear based on 5 core indicators, and provide position adjustment recommendations.
Works with
AI-first code editor with Composer
Before installing skills in Cursor, ensure your development environment meets these requirements:
node --versionus-market-sentimentExecute the skills CLI command in your project's root directory to begin installation:
Fetches us-market-sentiment from star23/day1global-skills and configures it for Cursor.
The CLI shows a list of agents. Use arrow keys and space to select Cursor:
Confirm successful installation by checking the skill directory location:
Restart Cursor to activate us-market-sentiment. Access via /us-market-sentiment in your agent's command palette.
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.
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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
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
Evaluate features using frameworks (RICE, ICE, Kano) and create prioritized backlogs
Example
Score 20 feature ideas using RICE framework, generate prioritized roadmap with rationale
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This skill helps you systematically analyze US stock market sentiment, determine whether the current market is in a state of greed or fear based on 5 core indicators, and provide position adjustment recommendations.
Use this skill when users ask the following types of questions:
For each indicator, use web_search to find the latest data, then evaluate according to the criteria below.
What it is: The full name is National Association of Active Investment Managers Exposure Index, published weekly by the association of active investment managers in the US. It reflects the current equity exposure of active investment managers (0 = fully in cash, 100 = fully invested, can exceed 100 indicating leverage).
Search keywords: NAAIM exposure index latest or NAAIM exposure index this week
Warning criteria:
Key interpretation: When nearly all active fund managers are fully invested, it means "everyone who can buy has already bought," and there is a lack of new buying power to push stock prices higher.
What it is: Data published by large asset custodians such as State Street, reflecting the percentage of equity allocation in the portfolios of global institutional investors (pension funds, insurance companies, sovereign wealth funds, etc.).
Search keywords: State Street institutional equity allocation or institutional investor equity allocation percentage
Warning criteria:
Key interpretation: Institutional investors as a whole are typically "late to the party" — they are most optimistic at the top (highest allocation) and most pessimistic at the bottom (lowest allocation).
What it is: Daily retail investor fund flow data tracked by JPMorgan, calculating the net buying amount of retail investors in the stock market.
Search keywords: JPMorgan retail investor net buying or retail investor flows equity
Warning criteria:
Key interpretation: Retail investors tend to pile in when the market is hottest and sell when panic is greatest. Extreme retail buying often signals a short-term top.
What it is: The current S&P 500 index price ÷ expected earnings per share over the next 12 months (Forward Earnings). This is one of Wall Street's most commonly used valuation metrics.
Search keywords: S&P 500 forward PE ratio current or S&P 500 forward earnings multiple
Warning criteria:
Key interpretation: A high P/E ratio means investors are paying more for each dollar of earnings. When the forward PE approaches historical peaks, it indicates that stock prices have already "priced in" a great deal of future growth expectations.
What it is: The borrowing multiple used by hedge funds in their investments. The higher the leverage, the more money the fund borrows to amplify its investments. Typically reported by the Prime Brokerage divisions of Goldman Sachs and Morgan Stanley.
Search keywords: hedge fund leverage ratio Goldman Sachs or hedge fund gross leverage prime brokerage
Warning criteria:
Key interpretation: High leverage is like a "powder keg" — no problem when the market is normal, but once a pullback occurs, forced liquidations trigger chain reactions, turning minor pullbacks into major crashes.
Count how many of the 5 indicators are in warning status:
| Warning Indicators | Sentiment Rating | Position Recommendation |
|---|---|---|
| 0 | 😨 Panic | Consider gradually adding positions, watch for oversold rebound opportunities |
| 1 | 📊 Neutral-Cautious | Maintain current positions, monitor trends |
| 2 | 📊 Neutral-Optimistic | Minor adjustments acceptable, mind risk controls |
| 3 | 🟡 Greed | Reduction signal: Consider reducing equity exposure by 10-20% |
| 4 | 🔴 Extreme Greed | Clear reduction: Reduce equity exposure by 20-30% |
| 5 | 🔴🔴 Extreme Greed (Full Warning) | Significantly reduce positions or establish hedging positions |
Use the following structured template to output the analysis results:
# 🎯 US Stock Market Sentiment Monitoring Report
**Date**: [Current Date]
## 📊 Indicator Dashboard
| Indicator | Current Value | Status | Signal |
|------|---------|------|------|
| NAAIM Exposure Index | [Value] | [Normal/Warning] | [Brief explanation] |
| Institutional Equity Allocation | [Value] | [Normal/Warning] | [Brief explanation] |
| Retail Net Buying | [Value] | [Normal/Warning] | [Brief explanation] |
| S&P 500 Forward PE | [Value] | [Normal/Warning] | [Brief explanation] |
| Hedge Fund Leverage | [Value] | [Normal/Warning] | [Brief explanation] |
## 🚦 Comprehensive Rating
**Sentiment Status**: [Extreme Greed / Greed / Neutral / Panic]
**Warning Indicators**: [X] / 5
## 💼 Position Recommendation
[Provide specific recommendations based on the rating]
## ⚠️ Disclaimers
- This analysis is based on publicly available market data and is for reference only
- A single indicator does not constitute a trading signal; comprehensive judgment is required
- Data may have a 1-2 week lag
- Recommendations should be considered in conjunction with your own risk tolerance
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Make data-driven prioritization decisions faster
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
Prerequisites
Time Estimate
30-60 minutes to see productivity improvements
Steps
Common Pitfalls
✓ Do
✗ Don't
💡 Pro Tips
✓ 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.
mattpocock/skills
parcadei/continuous-claude-v3
cursor/plugins
ailabs-393/ai-labs-claude-skills
pproenca/dot-skills
mattpocock/skills
Solid pick for teams standardizing on skills: us-market-sentiment is focused, and the summary matches what you get after install.
Keeps context tight: us-market-sentiment is the kind of skill you can hand to a new teammate without a long onboarding doc.
We added us-market-sentiment from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.
I recommend us-market-sentiment for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.
Useful defaults in us-market-sentiment — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.
us-market-sentiment fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.
Registry listing for us-market-sentiment matched our evaluation — installs cleanly and behaves as described in the markdown.
Solid pick for teams standardizing on skills: us-market-sentiment is focused, and the summary matches what you get after install.
Useful defaults in us-market-sentiment — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.
I recommend us-market-sentiment for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.
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