stock-sentiment
Stock sentiment analysis and financial data for US equity research. Analyze multi-engine AI sentiment (Grok, DeepSeek, GPT-5), SEC EDGAR filings, Seeking Alpha ratings, earnings call transcripts, social media sentiment, news insights, FRED macro indicators, and OHLCV prices for 2000+ stocks. Use when researching stocks, checking sentiment, analyzing SEC filings, or exploring market data.
Why use this skill?
Analyze US equities with OpenClaw. Access SEC filings, AI-powered sentiment, earnings transcripts, and macro indicators via 27 specialized MCP tools.
Install via CLI (Recommended)
clawhub install openclaw/skills/skills/haiyang0932/stock-sentimentWhat This Skill Does
The stock-sentiment skill is a comprehensive financial intelligence toolkit for the OpenClaw agent, providing deep-dive research capabilities into US equity markets. It integrates 27 specialized MCP tools that aggregate data from SEC EDGAR filings, Seeking Alpha, FRED macro indicators, and multi-engine AI sentiment feeds (including Grok, DeepSeek, and GPT-5). This skill enables users to move beyond simple price tracking, allowing for sophisticated analysis of company financial health, transcript-based sentiment shifts, and broad market macro trends. By bridging the gap between raw data and AI-summarized insights, it acts as a primary research analyst for any OpenClaw user exploring the stock market.
Installation
To integrate this skill, use the ClawHub CLI. Ensure your environment is configured to support MCP protocols and run the following command in your terminal:
clawhub install openclaw/skills/skills/haiyang0932/stock-sentiment
Once installed, you can immediately begin querying using the provided toolset. While a free tier is available, high-frequency users should set the ALPHAFACTORYX_MCP_TOKEN environment variable to access higher rate limits and daily request quotas.
Use Cases
- Fundamental Research: Pulling 10-K and 10-Q filings directly from the SEC to analyze management's language and financial disclosures.
- Sentiment Analysis: Evaluating how the market reacts to news by leveraging aggregated insights from AI models like DeepSeek and GPT-5.
- Macro Context: Correlating specific stock performance against FRED macro indicators like CPI, GDP, or yield curves to understand systemic risk.
- Earnings Intelligence: Searching through specific earnings call transcripts to identify phrases like 'margin expansion' or 'supply chain disruption' before making investment decisions.
Example Prompts
- "Analyze the latest 10-K filing for AAPL and summarize the primary revenue risks mentioned by management."
- "What is the current AI sentiment score for NVIDIA based on the latest news articles and X sentiment?"
- "Compare the current VIX level with historical data from FRED to assess market volatility for my equity portfolio."
Tips & Limitations
To maximize the utility of this skill, prioritize the use of search-specific tools like sa_transcript_search when you have a specific hypothesis to test. Avoid parsing entire 10-K filings manually; instead, use the edgar_search function to query specific segments. Be aware that the free tier is limited to 20 requests per day, so bundle your research workflows. Note that while AI sentiment indicators provide powerful signals, they should be used as a supplement to, not a replacement for, fundamental financial analysis.
Metadata
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Find the right skillPaste this into your clawhub.json to enable this plugin.
{
"plugins": {
"official-haiyang0932-stock-sentiment": {
"enabled": true,
"auto_update": true
}
}
}Tags(AI)
Flags: network-access, external-api