Initial commit: A-share stock analysis project with screening, backtesting, and multi-factor analysis tools

2026-07-01 06:39:40 +00:00
commit d80c208004
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+---
+name: market-overview
+description: Assess current A-share market environment including index trends, market breadth, sector rotation, and position sizing recommendation
+---
+
+## What I Do
+
+Evaluate the overall A-share market environment to determine:
+1. Whether the market is favorable for medium-term trading
+2. Suggested position sizing in RMB (capital-aware, for ~5万 account)
+3. Current hot sectors and rotation patterns
+4. Key risk factors
+
+## Capital Context (CRITICAL)
+
+**The user has ~5万 RMB capital.** Position sizing must be translated to concrete RMB amounts, not abstract percentages alone.
+
+### Position Sizing for 5万 Account
+
+| Signal | Total Position | Max Per Stock | Holding Count |
+|--------|---------------|---------------|---------------|
+| **Heavy (bullish)** | ¥35,000–40,000 (70–80%) | ¥10,000–15,000 each | 3–4 positions |
+| **Moderate (neutral)** | ¥15,000–25,000 (30–50%) | ¥5,000–10,000 each | 2–3 positions |
+| **Light (bearish)** | <¥15,000 (<30%) | <¥5,000 each | 1–2 positions |
+
+Always present both: percentage of capital AND the corresponding RMB range.
+
+## Assessment Dimensions
+
+### Index Trend
+- Shanghai Composite (000001), Shenzhen Component (399001), ChiNext (399006)
+- Direction, strength, and stage of trend
+- Key support/resistance levels
+- 20/60-day MA relationship
+
+### Market Breadth
+- Advancing vs declining stocks ratio
+- Volume trend (expanding / contracting)
+- New highs vs new lows
+- % of stocks above 20-day MA
+
+### Sector Rotation
+- Leading and lagging sectors
+- Sector fund flow
+- Continuity of sector trends (how many days in a row?)
+
+## When to Use Me
+
+Use when the user asks to:
+- Check market conditions
+- Decide position size
+- Understand sector rotation
+- Before running any stock screening
+
+## Workflow
+
+1. Fetch major index data via `stock-data index`
+2. Fetch sector performance via `stock-data sector`
+3. Analyze market breadth indicators
+4. Identify sector hotspots and rotation signals
+5. Output a structured market assessment:
+
+### Output Format
+
+1. **Market Signal**: Strong / Moderate / Weak — with justification
+2. **Index Summary**: each index trend + key level
+3. **Market Breadth**: breadth reading and what it means
+4. **Hot Sectors**: top 3–5 sectors with momentum
+5. **Position Recommendation**:
+   - Signal-based allocation in RMB and %
+   - Max per stock in RMB
+   - Suggested holding count
+6. **Key Risks**: specific market risks to watch this week
+
+## Risk Disclaimer
+
+Always remind the user: results are for reference only. Market conditions can change rapidly. Position sizing is a suggestion, not financial advice.
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+---
+name: stock-analyzer
+description: Deep analysis of a single A-share stock covering technical, fundamental, capital flow, and sentiment dimensions
+---
+
+## What I Do
+
+Generate a comprehensive analysis report for a single stock:
+1. Fetch all relevant data for the stock
+2. Analyze across four dimensions
+3. Score each dimension (0-100)
+4. Provide overall rating and actionable insights
+
+## Capital Context (CRITICAL)
+
+**The user has ~5万 RMB capital.** Every analysis must include:
+
+- **Affordability check**: confirm the stock price × 100 shares is within reach
+- **Position sizing advice**: based on market conditions and stock risk profile, suggest how many lots the user should buy
+- **Risk in RMB**: always show stop-loss and take-profit levels in both percentage AND absolute RMB amount
+- **Transaction cost**: calculate estimated round-trip cost for the suggested position
+
+### Affordability Check
+```
+这股票一手要多少钱？ 股价 × 100 = ____ 元
+用户能买几手？ 分配的仓位金额 ÷ (股价 × 100) = ____ 手
+```
+
+## Analysis Dimensions
+
+### Technical Analysis
+- Trend positioning: identify if stock is in uptrend/downtrend/sideways
+- Moving average status: check MA alignment (5/10/20/60 day)
+- Support/Resistance levels: identify key price levels
+- Volume analysis: volume trend, volume-price divergence signals
+- RSI/MACD: oscillator readings and signals
+
+### Capital Flow Analysis
+- Main fund flow: net inflow trend over 3/5/10 days
+- Northbound capital: recent changes (if available)
+- Large order ratio: institutional activity signals
+
+### Fundamental Analysis
+- Valuation: PE/PB historical percentile
+- Profitability: ROE trend
+- Growth: revenue and profit YoY growth
+- Quick health check: debt ratio, cash flow
+
+### Sentiment Analysis
+- Recent news: key announcements in past 30 days
+- Analyst ratings: direction of recent rating changes
+
+## Scoring
+
+Weighted composite score (0-100):
+- Technical: 35%
+- Capital Flow: 30%
+- Fundamental: 25%
+- Sentiment: 10%
+
+## When to Use Me
+
+Use when the user asks to:
+- Analyze a specific stock by name or code
+- Evaluate whether a stock is worth buying
+- Get a detailed report on a stock
+
+## Workflow
+
+1. Get stock code (ask user if not provided)
+2. Call `stock-data` tools to fetch all data
+3. Analyze each dimension, calculate scores
+4. Perform affordability check (price × 100 vs 5万 budget)
+5. Present a structured report with:
+
+### Report Sections
+
+1. **Basic Info**: name, code, price, sector, market cap, 1手 cost
+2. **Overall Score**: composite rating with grade (A/B/C/D)
+3. **Dimension Breakdown**: each dimension's score with key observations
+4. **Technical Check**: trend, support/resistance, volume signal
+5. **Capital Flow Check**: recent money flow pattern and what it means
+6. **Fundamental Check**: valuation context, growth trajectory
+7. **News & Sentiment**: key events, sentiment direction
+8. **Position Suggestion**:
+   - Suggested lot count (based on market signal + stock risk)
+   - Total cost in RMB
+   - Estimated round-trip transaction cost
+9. **Risk Management**:
+   - Stop-loss level: price (¥) and loss amount (¥) with percentage
+   - Take-profit target: price (¥) and gain amount (¥) with percentage
+10. **Verdict**: Watch / Consider / Caution / Avoid — with one-sentence reason
+11. **Risk Disclaimer**: results for reference only
+
+## Risk Disclaimer
+
+Always remind the user: results are for reference only. Past performance does not guarantee future results. The user bears all trading risk.
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+---
+name: stock-backtest
+description: Design, run, and interpret strategy backtests for A-share stocks
+---
+
+## What I Do
+
+Guide the agent through backtesting trading strategies:
+1. Help design strategy rules from user descriptions
+2. Run backtests on historical data
+3. Interpret results and identify potential issues
+4. Suggest improvements
+
+## Capital Context (CRITICAL)
+
+**The user has ~5万 RMB capital.** Backtest interpretation must be capital-aware:
+
+- When presenting metrics, translate key numbers to the user's context:
+  - "Annualized return 15% = ¥7,500 on 5万"
+  - "Max drawdown 12% = ¥6,000 worst-case loss"
+  - "Average win ¥800, average loss ¥1,200 per trade"
+- Assess whether a strategy is **practically usable** with 5万 considering position sizing constraints
+- Flag if a strategy requires more positions than 5万 can support
+
+## Key Backtest Metrics
+
+- **Cumulative return**: total return over the period
+- **Annualized return**: normalized yearly return (translate to ¥ on 5万)
+- **Win rate**: percentage of profitable trades
+- **Max drawdown**: worst peak-to-trough decline (translate to ¥)
+- **Sharpe ratio**: risk-adjusted return
+- **Benchmark comparison**: vs CSI 300 index
+
+## Strategy Parameters
+
+Common strategy elements to help users define:
+- Entry conditions (e.g., MA crossover, breakout, pullback)
+- Exit conditions (e.g., stop loss %, take profit %, trailing stop, time-based)
+- Position sizing (e.g., fixed %, Kelly fraction)
+- Test period and stock universe
+
+## When to Use Me
+
+Use when the user asks to:
+- Backtest a trading strategy
+- Verify a strategy's historical performance
+- Compare multiple strategies
+- Evaluate whether a strategy is worth using
+
+## Workflow
+
+1. Clarify strategy rules with user
+2. Translate rules into testable parameters
+3. Run backtest via `stock-backtest` tools
+4. Present results with interpretation:
+
+### Output Format
+
+1. **Strategy Summary**: rules in plain language
+2. **Performance Metrics**: all key metrics in table form
+3. **Capital Context Translation**:
+   | Metric | Value | On 5万 Capital |
+   |--------|-------|----------------|
+   | Annualized Return | 18% | ¥9,000/year |
+   | Max Drawdown | 15% | ¥7,500 worst case |
+   | Avg Win per Trade | ¥450 | — |
+   | Avg Loss per Trade | ¥600 | — |
+4. **Equity Curve Description**: shape, drawdown periods, recovery time
+5. **Benchmark Comparison**: outperformance/underperformance vs CSI 300
+6. **Practicality Assessment for 5万**: 
+   - Can the user afford the position sizes?
+   - Does the strategy require too many concurrent positions?
+   - Is the max drawdown psychologically tolerable?
+7. **Potential Concerns**: overfitting, look-ahead bias, survivorship bias, regime dependence
+
+## Risk Disclaimer
+
+Always remind: backtest results reflect historical data. Live performance will differ. Strategies can fail in new market regimes. The user bears all trading risk.
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+---
+name: stock-screener
+description: Multi-factor A-share stock screening workflow for medium-to-short-term selection
+---
+
+## What I Do
+
+Guide the agent through a structured stock screening process:
+1. Understand user preferences (industry, market cap, holding period)
+2. Assess market environment via `market-overview` skill
+3. Call screening tools to find candidates
+4. Score and rank candidates by multi-factor model
+5. Output **Top 3-5** picks with rationale, position sizing, and cost estimates
+
+## Capital Context (CRITICAL)
+
+**The user has ~5万 RMB capital.** Every recommendation must account for this:
+
+- **Stock price filter**: each recommended stock must cost ¥10–¥50 per share so the user can afford at least 1手 (100 shares). Stocks >¥200 need explicit justification (concentrated bet). Stocks >¥500 are completely inaccessible — never recommend them.
+- **Portfolio concentration**: default output is 3–5 stocks, not 10+. The user holds 2–4 stocks max.
+- **Position sizing**: for each recommended stock, suggest a specific lot count and total cost in RMB.
+- **Transaction cost**: for each recommended position, calculate estimated one-way cost (commission + stamp tax). Surface it alongside the position suggestion.
+
+### Position Sizing Table (5万 context)
+
+| Market Signal | Total Exposure | Max Per Stock | Holding Count |
+|---------------|---------------|---------------|---------------|
+| Strong uptrend | 35,000–40,000 (70–80%) | 10,000–15,000 | 3–4 positions |
+| Neutral/sideways | 15,000–25,000 (30–50%) | 5,000–10,000 | 2–3 positions |
+| Weak/downtrend | <15,000 (<30%) | <5,000 | 1–2 positions |
+
+### Affordability Check
+
+Before recommending any stock, verify:
+```
+股价 × 100 shares ≤ 计划分配给该股的仓位金额
+```
+Example: ¥38 stock × 100 = ¥3,800. With ¥10,000 allocation, the user can buy 2手 (200 shares, ¥7,600).
+
+## Screening Dimensions
+
+- **Technical (35%)**: Trend strength, moving average alignment, volume-price coordination, RSI position
+- **Capital Flow (30%)**: Main fund net inflow trend, northbound capital, large order ratio
+- **Fundamental (25%)**: PE percentile, ROE, profit growth, revenue growth
+- **Sentiment (10%)**: News heat, analyst rating direction
+
+## When to Use Me
+
+Use when the user asks to:
+- Find/screen stocks for investment
+- Get stock recommendations
+- Filter stocks by any criteria
+
+## Workflow
+
+1. Ask the user about preferences if not specified (sector, style, time horizon)
+2. Load `market-overview` skill to check if market is favorable and get position sizing signal
+3. Use `stock-screen` tools to filter candidates (default top_n=5)
+4. For each top candidate, verify affordability:
+   - Check share price, calculate minimum buy cost (price × 100)
+   - Cross-check against the position sizing budget
+   - Filter out any stock the user cannot afford
+5. For remaining candidates, run quick analysis with relevant tools
+6. Present a ranked list with:
+   - Rank and composite score (0-100)
+   - Key strengths (why buy?) and risks (what can go wrong?)
+   - Suggested position: lot count × share price = total cost
+   - Estimated transaction cost for this position
+   - Stop-loss price in both ¥ and percentage
+
+### Output Format Example
+
+| Rank | Stock | Price | Score | Position | Cost | Stop-Loss | Rationale |
+|------|-------|-------|-------|----------|------|-----------|-----------|
+| 1 | 600XXX | ¥28.5 | 82 | 3手 (300股) = ¥8,550 | 交易费~¥14 | ¥25.7 (-10%, -¥855) | 放量突破+主力净流入 |
+
+## Risk Disclaimer
+
+Always remind: results are for reference only. Past performance does not guarantee future results. The user bears all trading risk.
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+import { tool } from "@opencode-ai/plugin";
+import path from "path";
+
+const SCRIPTS_DIR = (ctx: { worktree: string }) =>
+  path.join(ctx.worktree, "scripts");
+
+async function runPython(
+  ctx: { worktree: string },
+  fn: string,
+  args: Record<string, unknown>,
+): Promise<string> {
+  const scriptPath = path.join(SCRIPTS_DIR(ctx), "backtest_engine.py");
+  const argsJson = JSON.stringify(args);
+  const result = await Bun.$`python3 ${scriptPath} ${fn} ${argsJson}`.text();
+  return result.trim();
+}
+
+export const run = tool({
+  description: "Run a backtest for a trading strategy on specified stock universe and period",
+  args: {
+    strategy_name: tool.schema.string().optional().describe("Name of a predefined strategy, or omit to use custom rules"),
+    entry_rule: tool.schema.string().optional().describe("Custom entry condition (Python expression using df columns like close, ma20, ma60, volume, etc.)"),
+    exit_rule: tool.schema.string().optional().describe("Custom exit condition (Python expression) or 'stop_loss:0.05,take_profit:0.15,max_hold:20'"),
+    universe: tool.schema.enum(["hs300", "zz500", "all", "custom"]).default("hs300").describe("Stock universe to test on"),
+    symbols: tool.schema.string().optional().describe("Comma-separated stock codes for custom universe"),
+    start_date: tool.schema.string().default("20210101").describe("Start date YYYYMMDD"),
+    end_date: tool.schema.string().default("20251231").describe("End date YYYYMMDD"),
+  },
+  async execute(args, context) {
+    return runPython(context, "run", args);
+  },
+});
+
+export const predefined = tool({
+  description: "List all predefined backtest strategies with descriptions",
+  args: {},
+  async execute(args, context) {
+    return runPython(context, "predefined", args);
+  },
+});
+
+export const compare = tool({
+  description: "Compare multiple predefined strategies on the same universe and period",
+  args: {
+    strategies: tool.schema.string().describe("Comma-separated strategy names to compare"),
+    universe: tool.schema.enum(["hs300", "zz500", "all"]).default("hs300").describe("Stock universe"),
+    start_date: tool.schema.string().default("20210101").describe("Start date YYYYMMDD"),
+    end_date: tool.schema.string().default("20251231").describe("End date YYYYMMDD"),
+  },
+  async execute(args, context) {
+    return runPython(context, "compare", args);
+  },
+});
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+import { tool } from "@opencode-ai/plugin";
+import path from "path";
+
+const SCRIPTS_DIR = (ctx: { worktree: string }) =>
+  path.join(ctx.worktree, "scripts");
+
+async function runPython(
+  ctx: { worktree: string },
+  script: string,
+  fn: string,
+  args: Record<string, unknown>,
+): Promise<string> {
+  const scriptPath = path.join(SCRIPTS_DIR(ctx), script);
+  const argsJson = JSON.stringify(args);
+  const result = await Bun.$`python3 ${scriptPath} ${fn} ${argsJson}`.text();
+  return result.trim();
+}
+
+export const quote = tool({
+  description: "Get daily/weekly K-line and real-time quotes for a stock",
+  args: {
+    symbol: tool.schema.string().describe("Stock code (e.g. 600519 for Kweichow Moutai)"),
+    period: tool.schema.enum(["daily", "weekly", "monthly"]).default("daily").describe("K-line period"),
+    start_date: tool.schema.string().optional().describe("Start date YYYYMMDD, defaults to 90 days ago"),
+    end_date: tool.schema.string().optional().describe("End date YYYYMMDD, defaults to today"),
+  },
+  async execute(args, context) {
+    return runPython(context, "market_data.py", "quote", args);
+  },
+});
+
+export const financial = tool({
+  description: "Get financial statement indicators for a stock",
+  args: {
+    symbol: tool.schema.string().describe("Stock code (e.g. 600519)"),
+  },
+  async execute(args, context) {
+    return runPython(context, "market_data.py", "financial", args);
+  },
+});
+
+export const moneyflow = tool({
+  description: "Get capital flow data (main fund, northbound) for a stock",
+  args: {
+    symbol: tool.schema.string().describe("Stock code (e.g. 600519)"),
+    days: tool.schema.number().default(10).describe("Number of recent days"),
+  },
+  async execute(args, context) {
+    return runPython(context, "market_data.py", "moneyflow", args);
+  },
+});
+
+export const news = tool({
+  description: "Get recent news and announcements for a stock",
+  args: {
+    symbol: tool.schema.string().describe("Stock code (e.g. 600519)"),
+    limit: tool.schema.number().default(20).describe("Max number of news items"),
+  },
+  async execute(args, context) {
+    return runPython(context, "sentiment.py", "news", args);
+  },
+});
+
+export const index = tool({
+  description: "Get major A-share index data (Shanghai Composite, Shenzhen Component, ChiNext)",
+  args: {
+    index_code: tool.schema.enum(["sh", "sz", "cyb", "all"]).default("all").describe("Index to fetch"),
+    days: tool.schema.number().default(30).describe("Number of recent trading days"),
+  },
+  async execute(args, context) {
+    return runPython(context, "market_data.py", "index", args);
+  },
+});
+
+export const sector = tool({
+  description: "Get sector/industry performance and ranking",
+  args: {
+    date: tool.schema.string().optional().describe("Date YYYYMMDD, defaults to latest"),
+  },
+  async execute(args, context) {
+    return runPython(context, "market_data.py", "sector", args);
+  },
+});
@@ -0,0 +1,61 @@
+import { tool } from "@opencode-ai/plugin";
+import path from "path";
+
+const SCRIPTS_DIR = (ctx: { worktree: string }) =>
+  path.join(ctx.worktree, "scripts");
+
+async function runPython(
+  ctx: { worktree: string },
+  fn: string,
+  args: Record<string, unknown>,
+): Promise<string> {
+  const scriptPath = path.join(SCRIPTS_DIR(ctx), "stock_screener.py");
+  const argsJson = JSON.stringify(args);
+  const result = await Bun.$`python3 ${scriptPath} ${fn} ${argsJson}`.text();
+  return result.trim();
+}
+
+export const multi_factor = tool({
+  description: "Screen stocks using multi-factor scoring model (technical + capital flow + fundamental + sentiment)",
+  args: {
+    strategy: tool.schema.enum(["comprehensive", "momentum", "value", "breakout"]).default("comprehensive").describe("Screening strategy"),
+    sector: tool.schema.string().optional().describe("Filter by sector/industry name"),
+    market_cap: tool.schema.enum(["large", "medium", "small", "all"]).default("all").describe("Market cap filter"),
+    top_n: tool.schema.number().default(5).describe("Number of top stocks to return (user has 5万 capital, keep it tight)"),
+  },
+  async execute(args, context) {
+    return runPython(context, "multi_factor", args);
+  },
+});
+
+export const strong = tool({
+  description: "Screen for strong-trend stocks (MA bull alignment + relative strength)",
+  args: {
+    sector: tool.schema.string().optional().describe("Filter by sector/industry name"),
+    top_n: tool.schema.number().default(5).describe("Number of top stocks to return (user has 5万 capital, keep it tight)"),
+  },
+  async execute(args, context) {
+    return runPython(context, "strong", args);
+  },
+});
+
+export const breakout = tool({
+  description: "Screen for volume breakout stocks (price breaking resistance with expanding volume)",
+  args: {
+    lookback_days: tool.schema.number().default(60).describe("Lookback period for resistance identification"),
+    top_n: tool.schema.number().default(5).describe("Number of top stocks to return (user has 5万 capital, keep it tight)"),
+  },
+  async execute(args, context) {
+    return runPython(context, "breakout", args);
+  },
+});
+
+export const oversold = tool({
+  description: "Screen for oversold stocks with potential rebound signals",
+  args: {
+    top_n: tool.schema.number().default(5).describe("Number of top stocks to return (user has 5万 capital, keep it tight)"),
+  },
+  async execute(args, context) {
+    return runPython(context, "oversold", args);
+  },
+});