analyze-stock
Original:🇨🇳 Chinese
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One-click comprehensive analysis of a stock/company. Collect data from five dimensions - stock price, news sentiment, industry comparison, market environment, and official company website - simultaneously through parallel sub-agents, then conduct cross-analysis, causal attribution, and trend prediction in the main thread, and output a standardized analysis report. Trigger words: Analyze XX stock, analyze TICKER, How is XX, Is XX worth buying? Supports A-shares and U.S. stocks.
8installs
Sourcejssfy/k-skills
Added on
NPX Install
npx skill4agent add jssfy/k-skills analyze-stockTags
Translated version includes tags in frontmatterSKILL.md Content (Chinese)
View Translation Comparison →Analyze Stock — One-Click Comprehensive Stock Analysis
Enter the company name or stock ticker, and data from five dimensions will be automatically collected in parallel. A standard report will be output after comprehensive analysis.
When to Use
Triggered when the user requests the following operations:
- "Analyze Tencent" / "Analyze Kweichow Moutai" / "Analyze 600519"
- "analyze NVDA" / "analyze Tesla"
- "How is XX stock performing?" / "Why has XX risen/fallen recently?"
- "Help me check XX" / "Is XX worth buying?"
Phase 0: Parse Input
Identify the following information based on user input:
-
Company Name and Stock Ticker
- Use the ticker directly if provided by the user
- If the user provides a company name, query the corresponding ticker via WebSearch
- A-share ticker format: 6-digit number (600519, 000858)
- U.S. stock ticker format: English letters (NVDA, AAPL, TSLA)
-
Identify Market Type
- 6-digit pure number → A-shares
- English letters → U.S. stocks
- Chinese company name with Chinese characters → A-shares
- Others → U.S. stocks
-
Determine Key Variables (Required by all subsequent Agents)
- : Stock ticker
{ticker} - : Full company name
{company_name} - : English company name (for U.S. stocks)
{company_name_en} - : "A-shares" or "U.S. stocks"
{market} - : Belonging industry
{industry} - : Official company website URL
{website}
If the official website or industry cannot be determined, perform a quick WebSearch first, do not skip this step.
Phase 1: Parallel Data Collection (5 Subagents)
Key Requirement: The following 5 Tasks must be sent in the same message to ensure parallel execution.
Each Agent uses .
subagent_type: "general-purpose"Agent 1: Stock Price Data and Technical Indicators
description: "Collect {ticker} stock price data"
Prompt Template:
You are a stock price data analyst. Please obtain the stock price data of {company_name}({ticker}) for the last 7 trading days.
Tasks:
1. Use WebSearch to search "{ticker} stock price last 7 days {market}" to get the latest market data
2. Organize the following information:
- Daily closing prices and price changes for the last 7 trading days
- Cumulative price change over 7 days
- Current price
- Trading volume trend (increasing/decreasing/flat)
- Key technical signals (if any: moving average bullish/bearish arrangement, RSI overbought/oversold, obvious support/resistance levels)
- Comparison with the market's price change during the same period
Output Requirements:
- Return in a structured format
- Highlight: 7-day price change, volume-price coordination, key technical signals
- Keep within 500 words
- Do not provide investment adviceIf it's A-shares and akshare is installed, you can additionally add the following instruction to the prompt:
If available, execute the following command to obtain accurate data:
python {baseDir}/scripts/data_fetcher.py --code {ticker} --data-type valuationAgent 2: News Sentiment Analysis
description: "Search recent news about {company_name}"
Prompt Template:
You are a financial news analyst. Please search for important news and public opinion about {company_name}({ticker}) in the last 7 days.
Tasks:
1. Use WebSearch to search the following keywords (at least 2 different keyword combinations):
- "{company_name} latest news" or "{company_name} latest news"
- "{ticker} stock this week" or "{ticker} stock this week"
2. Select 3-5 most important news items from the search results
3. Use WebFetch to access at least 2 of the original news articles to verify content authenticity
4. Analyze the overall sentiment of public opinion
Output Requirements:
- List 3-5 key news items, each including: date, title, source, brief content (1-2 sentences)
- Overall sentiment judgment: Positive / Negative / Neutral, with reasons
- Identify whether there are major events (earnings release, policy changes, management changes, product launches, lawsuits, etc.)
- Keep within 600 wordsAgent 3: Industry Comparison Analysis
description: "Analyze the {industry} industry situation"
Prompt Template:
You are an industry analyst. Please analyze the recent situation of the {industry} industry where {company_name}({ticker}) operates.
Tasks:
1. Use WebSearch to search:
- "{industry} industry recent trends" or "{industry} industry trends"
- "{company_name} competitors" or "{company_name} competitors"
2. Organize the following information:
- Recent overall industry trend (rising/falling/stable)
- Key factors affecting the industry (policies, technology, demand, etc.)
- Recent stock price performance of 2-3 main competitors
- General position of {company_name} in the industry
Output Requirements:
- Industry trend overview (2-3 sentences)
- Competitive landscape summary table: Company name, 7-day price change, key developments
- Relative strengths and weaknesses of the company (1-2 points)
- Keep within 500 wordsAgent 4: Market Environment Analysis
description: "Analyze the current market environment"
Prompt Template:
You are a macro market analyst. Please analyze the current global market environment, focusing on market factors related to {company_name}({ticker}).
Tasks:
1. Use WebSearch to search the latest market data:
- Recent trends of major indices: {If A-shares: "Shanghai Composite Index, Shenzhen Component Index, ChiNext Index this week"; If U.S. stocks: "S&P 500 NASDAQ Dow Jones this week"}
- "VIX index today" (Volatility Index)
- Recent major macro events or central bank dynamics
2. Evaluate:
- Market trend direction: Rising / Falling / Volatile
- Market sentiment: Risk-on (risk-seeking) / Risk-off (risk-averse)
- VIX level and its implication
- Whether there are major macro events impacting the market
Output Requirements:
- One-sentence summary of the market environment
- 7-day performance of major indices (price change)
- VIX level and volatility judgment
- 1-2 key factors affecting the current market
- Keep within 400 wordsAgent 5: Official Website and Announcement Information
description: "Crawl {company_name} official website information"
Prompt Template:
You are a corporate information researcher. Please obtain the latest official updates of {company_name}({ticker}).
Tasks:
1. Use WebFetch to access the company's official website: {website}
- Check if there are latest announcements or news on the homepage
2. Use WebSearch to search "{company_name} investor relations" or "{company_name} investor relations"
- Look for recent announcements, earnings summaries, performance forecasts
3. If it's a listed company, search for recent announcements:
- A-shares: "{company_name} announcement Juchao Information"
- U.S. stocks: "{company_name} SEC filing" or "{company_name} earnings"
Output Requirements:
- Latest official company developments (products, strategies, personnel, etc.)
- Key data from the latest earnings report/performance (if available)
- Summary of recent important announcements (if any)
- Keep within 400 words
- If the official website is inaccessible, state the situation and rely on search resultsPhase 2: Comprehensive Analysis (Main Thread)
Wait for all 5 Agents to return results, then complete the following analysis in the main thread.
Step 1: Information Summary
Integrate the results of the 5 Agents to identify:
- Consistent signals between dimensions (e.g., rising stock price + positive news + upward industry trend = strong bullish signal)
- Contradictory signals between dimensions (e.g., rising stock price but negative news = potential risks may exist)
Step 2: Causal Attribution
Analyze the reasons for stock price changes in the last 7 days, sorted by influence:
- Direct driving factors: Company-level events (earnings, announcements, products, public opinion)
- Industry transmission factors: Industry policies, changes in competitive landscape
- Market environment factors: Market trend, capital flow, macro events
Step 3: Trend Prediction
Based on the above analysis, provide:
- Short-term outlook (1-2 weeks): Consider technical signals + upcoming events
- Medium-term outlook (1-3 months): Consider fundamentals + industry trends
- Main risk points: Factors that may lead to trend reversal
Phase 3: Output Report
Output the final report in the following format:
markdown
# {company_name} ({ticker}) Comprehensive Analysis Report
> Analysis Date: {date} | Analysis Period: Last 7 Trading Days | Market: {market}
## One-Sentence Summary
{Summarize the current situation and core judgment in one sentence}
---
## I. Stock Price Overview
| Indicator | Value |
|------|------|
| Current Price | ¥/$XXX |
| 7-Day Price Change | +/-X.XX% |
| Corresponding Market | +/-X.XX% |
| Trading Volume Trend | Increasing/Decreasing/Flat |
| Technical Signals | XXX |
## II. Analysis of Stock Price Change Reasons
### Direct Driving Factors
1. ...
### Industry Transmission Factors
1. ...
### Market Environment Factors
1. ...
## III. Recent Important News
| Date | Event | Impact |
|------|------|------|
| ... | ... | Positive/Negative/Neutral |
Sentiment Tendency: **Positive/Negative/Neutral**
## IV. Industry Comparison
| Company | 7-Day Price Change | Key Developments |
|------|---------|---------|
| {company_name} | ... | ... |
| Competitor A | ... | ... |
| Competitor B | ... | ... |
## V. Market Environment
- Market Trend: ...
- Market Sentiment: Risk-on / Risk-off
- VIX: XX (Low/Normal/High/Extremely High Volatility)
- Key Macro Factors: ...
## VI. Trend Outlook
### Short-Term (1-2 Weeks)
- ...
### Medium-Term (1-3 Months)
- ...
### Main Risks
1. ...
2. ...
---
> Disclaimer: This report is automatically generated by AI, for reference only, and does not constitute any investment advice. Investment involves risks, and decisions should be made cautiously.Also save the report as a file: in the current working directory.
{company_name}-analysis-{date}.mdError Handling
- Agent timeout or failure: If an Agent fails to return results, mark the dimension as "Data Missing" in the report, and analyze the remaining dimensions as usual
- Unrecognizable stock ticker: Prompt the user to confirm the ticker or company name
- akshare not installed (A-shares): Degrade to using only WebSearch to obtain data
- Official website inaccessible: Skip crawling the official website and rely on search engine results
Notes
- Strictly limit the output word count of each Agent to prevent main thread context overflow
- The comprehensive analysis phase focuses on cross-correlation, not simple listing
- Causal analysis should distinguish between "correlation" and "causality"
- Trend predictions must clearly indicate uncertainty