Skill: tangweigang-jpg/czsc-chan-theory (version 0.3.3)

--- name: czsc-chan-theory description: |- CZSC 缠论技术分析工具，支持 K 线生成、笔线段识别、分型信号提取与 A 股回测可视化。 license: Proprietary. See LICENSE.txt in project root. compatibility: Designed for Doramagic-host ecosystem (Claude Code / openclaw / Cursor). Requires Python 3.12+ with uv package manager. metadata: version: "v6.1" blueprint_id: "finance-bp-091" compiled_at: "2026-04-22T13:00:38.716020+00:00" capability_markets: "cn-astock" capability_activities: "backtesting, factor-research" sop_version: "crystal-compilation-v6.1" --- # 缠论技术分析 (czsc-chan-theory) > CZSC 缠论技术分析工具，支持 K 线生成、笔线段识别、分型信号提取与 A 股回测可视化。 ## Pipeline `data_collection -> data_storage -> factor_computation -> target_selection -> trading_execution -> visualization` ## Top Use Cases (10 total) ### Sphinx Documentation Configuration (`UC-101`) Configuring Sphinx documentation builder for the czsc project, ensuring proper Python path setup and Rust version priority **Triggers**: documentation, sphinx, configuration ### CZSC Performance Benchmarking (`UC-102`) Benchmarking CZSC analysis performance with varying K-line counts to measure initialization speed and memory usage **Triggers**: benchmark, performance, speed ### Volatility Classification Signal (`UC-104`) Classifying market volatility into three tiers (low/middle/high) based on recent K-line price ranges for signal generation **Triggers**: volatility, classification, signal For all **10** use cases, see [references/USE_CASES.md](references/USE_CASES.md). **Execute trigger**: `When user intent matches intent_router.uc_entries[].positive_terms AND user uses action verb (run/execute/跑/执行/backtest/fetch/collect)` ## What I'll Ask You - Target market: A-share (default), HK, or crypto? (US stocks in ZVT are half-baked — stockus_nasdaq_AAPL exists but coverage is thin) - Data source / provider: eastmoney (free, no account), joinquant (account+paid), baostock (free, good history), akshare, or qmt (broker)? - Strategy type: MACD golden-cross, MA crossover, volume breakout, fundamental screen, or custom factor? - Time range: start_timestamp and end_timestamp for backtest period - Target entity IDs: specific stocks (stock_sh_600000) or index components (SZ1000)? ## Semantic Locks (Fatal) | ID | Rule | On Violation | |---|---|---| | `SL-01` | Execute sell orders before buy orders in every trading cycle | halt | | `SL-02` | Trading signals MUST use next-bar execution (no look-ahead) | halt | | `SL-03` | Entity IDs MUST follow format entity_type_exchange_code | halt | | `SL-04` | DataFrame index MUST be MultiIndex (entity_id, timestamp) | halt | | `SL-05` | TradingSignal MUST have EXACTLY ONE of: position_pct, order_money, order_amount | halt | | `SL-06` | filter_result column semantics: True=BUY, False=SELL, None/NaN=NO ACTION | halt | | `SL-07` | Transformer MUST run BEFORE Accumulator in factor pipeline | halt | | `SL-08` | MACD parameters locked: fast=12, slow=26, signal=9 | halt | Full lock definitions: [references/LOCKS.md](references/LOCKS.md) ## Top Anti-Patterns (25 total) - **`AP-ZVT-183`**: 除权因子为 inf/NaN 时直接参与乘法导致复权静默失败 - **`AP-ZVT-179`**: 第三方数据接口超限后异常被吞噬，数据静默缺失 - **`AP-ZVT-183B`**: HFQ（后复权）与 QFQ（前复权）K 线表使用错误导致因子计算漂移 All 25 anti-patterns: [references/ANTI_PATTERNS.md](references/ANTI_PATTERNS.md) ## Evidence Quality Notice > [QUALITY NOTICE] This crystal was compiled from blueprint finance-bp-091. Evidence verify ratio = 60.4% and audit fail total = 13. Generated results may have uncaptured requirement gaps. Verify critical decisions against source files (LATEST.yaml / LATEST.jsonl). ## Reference Files | File | Contents | When to Load | |---|---|---| | [references/seed.yaml](references/seed.yaml) | V6+ 全量权威 (source-of-truth) | 有行为/决策争议时必读 | | [references/ANTI_PATTERNS.md](references/ANTI_PATTERNS.md) | 25 条跨项目反模式 | 开始实现前 | | [references/WISDOM.md](references/WISDOM.md) | 跨项目精华借鉴 | 架构决策时 | | [references/CONSTRAINTS.md](references/CONSTRAINTS.md) | domain + fatal 约束 | 规则冲突时 | | [references/USE_CASES.md](references/USE_CASES.md) | 全量 KUC-* 业务场景 | 需要完整示例时 | | [references/LOCKS.md](references/LOCKS.md) | SL-* + preconditions + hints | 生成回测/交易代码前 | | [references/COMPONENTS.md](references/COMPONENTS.md) | AST 组件地图（按 module 拆分）| 查 API 时 | --- *Compiled by Doramagic crystal-compilation-v6.1 from `finance-bp-091` blueprint at 2026-04-22T13:00:38.716020+00:00.* *See [human_summary.md](human_summary.md) for non-technical overview.*

path: human_summary.md
content: # Human Summary

> I help you build quant strategies on A-share with ZVT — from data fetch to backtest, one flow. Just tell me what you want; I'll write the code, you don't have to dig docs. (Heads up: ZVT natively supports A-share, HK, and crypto. US stocks — stockus_nasdaq_AAPL — are half-baked; don't bother for serious work.)

## What I Can Do

- **tagline**: I help you build quant strategies on A-share with ZVT — from data fetch to backtest, one flow. Just tell me what you want; I'll write the code, you don't have to dig docs. (Heads up: ZVT natively supports A-share, HK, and crypto. US stocks — stockus_nasdaq_AAPL — are half-baked; don't bother for serious work.)
- **use_cases**: ['Trading View K-Line Visualization', 'CZSC Performance Benchmarking', 'Sphinx Documentation Configuration', 'A-share MACD daily golden-cross backtest with hfq price adjustment from eastmoney', 'End-to-end ZVT pipeline: FinanceRecorder + GoodCompanyFactor + StockTrader', 'Multi-factor strategy with TargetSelector (AND mode) combining MACD + volume breakout', 'Index composition data collection (SZ1000, SZ2000) with EM recorder']

## What I Ask You

- Target market: A-share (default), HK, or crypto? (US stocks in ZVT are half-baked — stockus_nasdaq_AAPL exists but coverage is thin)
- Data source / provider: eastmoney (free, no account), joinquant (account+paid), baostock (free, good history), akshare, or qmt (broker)?
- Strategy type: MACD golden-cross, MA crossover, volume breakout, fundamental screen, or custom factor?
- Time range: start_timestamp and end_timestamp for backtest period
- Target entity IDs: specific stocks (stock_sh_600000) or index components (SZ1000)?


path: references/COMPONENTS.md
content: # Component Capability Map

**Project**: finance-bp-091--czsc
**Scan date**: 2026-04-22
**Stats**: {'total_files': 6, 'total_classes': 33, 'total_functions': 0, 'total_stages': 6}

## Modules (6)

- [data_collection_layer](components/data_collection_layer.md): 5 classes
- [chan_theory_analysis](components/chan_theory_analysis.md): 5 classes
- [signal_computation](components/signal_computation.md): 5 classes
- [event_&_position_management](components/event_-_position_management.md): 5 classes
- [trading_execution](components/trading_execution.md): 7 classes
- [backtest_&_performance_analysis](components/backtest_-_performance_analysis.md): 6 classes


path: references/USE_CASES.md
content: # Known Use Cases (KUC)

Total: **10**

## `KUC-101`
**Source**: `docs/source/conf.py`

Configuring Sphinx documentation builder for the czsc project, ensuring proper Python path setup and Rust version priority.

## `KUC-102`
**Source**: `examples/develop/czsc_benchmark.py`

Benchmarking CZSC analysis performance with varying K-line counts to measure initialization speed and memory usage.

## `KUC-103`
**Source**: `examples/develop/test_trading_view_kline.py`

Testing and demonstrating K-line visualization using trading_view_kline function with mock data.

## `KUC-104`
**Source**: `examples/signals_dev/bar_volatility_V241013.py`

Classifying market volatility into three tiers (low/middle/high) based on recent K-line price ranges for signal generation.

## `KUC-105`
**Source**: `examples/signals_dev/signal_match.py`

Parsing and analyzing signal definitions from czsc.signals module using SignalsParser for research and configuration purposes.

## `KUC-106`
**Source**: `examples/use_backtest_report.py`

Generating HTML and PDF backtest reports from trading strategy performance data for analysis and presentation.

## `KUC-107`
**Source**: `examples/use_cta_research.py`

Using CTAResearch framework to develop and test CTA trading strategies with mock data through backtesting.

## `KUC-108`
**Source**: `examples/use_html_report_builder.py`

Creating flexible HTML reports with custom headers, performance metrics, charts, and tables using HtmlReportBuilder.

## `KUC-109`
**Source**: `examples/use_optimize.py`

Optimizing entry and exit trading signals by systematically searching candidate signal combinations to find optimal parameters.

## `KUC-110`
**Source**: `examples/事件策略研究工具使用案例.ipynb`

Researching event-based trading strategies using CZSC objects for K-line analysis,笔 detection, and chart visualization.


Security scan verdicts — ClawScan: suspicious | static analysis: clean | VirusTotal: clean | SkillSpector: suspicious (CRITICAL)