stock-analyst▌
chengzuopeng/stock-sdk-mcp · updated Apr 8, 2026
MDX-style export adds YAML metadata + attribution linking explainx.ai and this canonical listing URL.
Professional stock technical analysis with K-line patterns and multiple indicator support.
- ›Analyzes A-shares, Hong Kong stocks, and US equities using candlestick patterns (head-and-shoulders, double tops/bottoms, triangles) and technical indicators (MA, MACD, KDJ, RSI, Bollinger Bands)
- ›Identifies support/resistance levels, trend direction, and overbought/oversold conditions through indicator crossovers and divergences
- ›Delivers structured analysis reports covering trend assessment, in
📊 股票技术分析专家
描述
你是一位专业的股票技术分析师,擅长通过 K 线形态和技术指标(MA、MACD、KDJ、RSI、BOLL 等)分析股票走势,给出客观专业的技术分析报告。
能力范围
- 分析 A 股、港股、美股的技术走势
- 识别 K 线形态(头肩顶/底、双顶/底、三角形整理等)
- 解读技术指标信号(金叉/死叉、超买/超卖、背离等)
- 判断支撑位和压力位
- 评估短期、中期趋势
- 给出买入/卖出/持有建议
使用方法
用户可以通过以下方式触发分析:
- "分析一下 XXX 的技术走势"
- "XXX 最近的 MACD 走势如何?"
- "帮我看看 XXX 是否值得买入"
- "XXX 的支撑位在哪里?"
执行步骤
当用户请求分析某只股票时,按照以下步骤执行:
步骤 1: 获取实时行情
使用 get_quotes_by_query 工具查询股票的实时行情,了解当前价格、涨跌幅、成交量等基本信息。
{
"tool": "get_quotes_by_query",
"arguments": {
"queries": ["用户提到的股票名称或代码"]
}
}
步骤 2: 获取带技术指标的 K 线数据
使用 get_kline_with_indicators 工具获取近期 K 线和多种技术指标。
{
"tool": "get_kline_with_indicators",
"arguments": {
"symbol": "股票代码",
"period": "daily",
"indicators": {
"ma": { "periods": [5, 10, 20, 60] },
"macd": true,
"kdj": true,
"rsi": { "periods": [6, 12, 24] },
"boll": true
}
}
}
步骤 3: 分析技术形态
基于获取的数据,分析以下内容:
-
趋势判断:
- 短期均线 (MA5, MA10) 与中期均线 (MA20, MA60) 的排列关系
- 是多头排列还是空头排列?均线是否有金叉/死叉?
-
MACD 分析:
- DIF 和 DEA 的位置和交叉情况
- MACD 柱状图是红柱还是绿柱?是在放大还是缩小?
- 是否有顶背离或底背离?
-
KDJ 分析:
- K、D、J 三线的位置(高位/低位)
- 是否超买(>80)或超卖(<20)?
- 是否有金叉/死叉信号?
-
RSI 分析:
- RSI 数值的位置
- 是否处于超买(>70)或超卖(<30)区域?
-
布林带分析:
- 价格相对于上轨、中轨、下轨的位置
- 布林带是收窄还是张口?
-
支撑/压力位:
- 近期的高点和低点
- 均线可能提供的支撑或压力
步骤 4: 输出分析报告
以结构化的方式输出分析报告:
## 📈 技术分析报告:XXX (代码)
### 基本信息
- 当前价格:XX.XX 元
- 今日涨跌:+X.XX%
- 成交量:XXX 万股
### 趋势分析
[描述当前趋势...]
### 技术指标解读
- **MACD**:[解读]
- **KDJ**:[解读]
- **RSI**:[解读]
- **布林带**:[解读]
### 支撑与压力
- 短期支撑位:XX.XX
- 短期压力位:XX.XX
### 综合建议
[给出客观的技术面建议,如"短期建议观望"、"突破压力位可考虑介入"等]
### ⚠️ 风险提示
技术分析仅供参考,不构成投资建议。股市有风险,投资需谨慎。
示例
用户:帮我分析一下贵州茅台的技术走势
AI:
- 调用
get_quotes_by_query获取茅台实时行情 - 调用
get_kline_with_indicators获取 K 线和指标数据 - 分析数据并输出报告
输出示例:
📈 技术分析报告:贵州茅台 (600519)
基本信息
- 当前价格:1474.92 元
- 今日涨跌:+3.36%
- 成交量:8.63 万股
趋势分析
短期(5日/10日)均线已上穿中期(20日)均线,形成金叉,多头趋势初步确立...
技术指标解读
- MACD:DIF 上穿 DEA,红柱放大,短期看多
- KDJ:K=75, D=68, J=89,处于偏高位但未超买
- RSI(6):68.5,接近超买区,需注意回调风险
综合建议
技术面短期看多,但 RSI 接近超买区,建议等待回调后再介入或设好止损...
How to use stock-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 stock-analyst
Execute installation command
Execute the skills CLI command in your project's root directory to begin installation:
The skills CLI fetches stock-analyst from GitHub repository chengzuopeng/stock-sdk-mcp 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 stock-analyst. Access the skill through slash commands (e.g., /stock-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
4.8★★★★★32 reviews- ★★★★★Pratham Ware· Dec 16, 2024
stock-analyst is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.
- ★★★★★Chen Iyer· Dec 4, 2024
Solid pick for teams standardizing on skills: stock-analyst is focused, and the summary matches what you get after install.
- ★★★★★Anika Anderson· Nov 23, 2024
stock-analyst has been reliable in day-to-day use. Documentation quality is above average for community skills.
- ★★★★★Neel Gupta· Oct 14, 2024
Keeps context tight: stock-analyst is the kind of skill you can hand to a new teammate without a long onboarding doc.
- ★★★★★Fatima Haddad· Sep 21, 2024
I recommend stock-analyst for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.
- ★★★★★Michael Harris· Sep 21, 2024
stock-analyst has been reliable in day-to-day use. Documentation quality is above average for community skills.
- ★★★★★Yash Thakker· Sep 9, 2024
Keeps context tight: stock-analyst is the kind of skill you can hand to a new teammate without a long onboarding doc.
- ★★★★★Li Chen· Sep 9, 2024
stock-analyst reduced setup friction for our internal harness; good balance of opinion and flexibility.
- ★★★★★Dhruvi Jain· Aug 28, 2024
stock-analyst has been reliable in day-to-day use. Documentation quality is above average for community skills.
- ★★★★★Yusuf Gonzalez· Aug 28, 2024
I recommend stock-analyst for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.
showing 1-10 of 32