How do I install the Ml4t Book Notebooks skill?

Run npx skillmds@latest add knownasnaffy/ml4t-book-notebooks-2 in your terminal (requires Node.js), paste this page's agent-chat prompt into Claude, Cursor, or any MCP-connected agent, or download the SKILL.md file and copy it into your agent's skills directory.

Is Ml4t Book Notebooks safe to use?

This skill has not completed SkillMD's automated safety review yet. Capability flags: executes scripts, makes network calls. SkillMD never runs a skill's scripts for you; review the SKILL.md before installing.

Which AI agents work with Ml4t Book Notebooks?

This skill is tagged as working with Claude Code, Claude.ai, OpenAI Codex. SKILL.md is an open format, so most agents that read a skills directory can load it too.

Is Ml4t Book Notebooks free to use?

Yes. Installing skills from SkillMD is free. This skill is licensed under Proprietary.

Who published Ml4t Book Notebooks?

knownasnaffy (@knownasnaffy) published this skill. Their other Agent Skills are listed on their SkillMD profile.

Ml4t Book Notebooks by knownasnaffy

Name: Ml4t Book Notebooks
Rating: 4.2 (5 reviews)
Author: knownasnaffy

Ml4t Book Notebooks

基于《Machine Learning for Trading》第二版配套 notebooks 实现量化交易策略开发与回测，涵盖多市场金融数据的时间序列机器学习分析。触发场景：(1) 用户要复现书中的机器学习交易策略代码；(2) 用户要将 ML 模型用于 A 股或美股市场预测；(3) 用户要获取金融数据并训练自己的量化模型。

knownasnaffy Updated Sep 22, 2026 0 repo stars

File contents

Permission Setup Review

python scripts/_init_dirs.py is an optional setup helper for the ml4t-book-notebooks skill. It may apply broad filesystem permissions for compatibility. Show the target paths and permission mode, explain the risk, and prefer a narrower mode when shared write access is not needed.

ml4t-book-notebooks

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.)

Pipeline

data_collection -> data_storage -> factor_computation -> target_selection -> trading_execution -> visualization

Top Use Cases (0 total)

Install

# One-time setup before first use
bash scripts/install.sh

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

Top Anti-Patterns (15 total)

AP-TIME-SERIES-ML-001: TimeSeries values array dimensionality mismatch
AP-TIME-SERIES-ML-002: Non-floating-point dtype in TimeSeries values
AP-TIME-SERIES-ML-003: Irregular or non-monotonic time index

All 15 anti-patterns: references/ANTI_PATTERNS.md

Evidence Quality Notice

[QUALITY NOTICE] This crystal was compiled from blueprint finance-bp-121. Evidence verify ratio = 31.8% and audit fail total = 35. 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	V6+ 全量权威 (source-of-truth)	有行为/决策争议时必读
references/ANTI_PATTERNS.md	15 条跨项目反模式	开始实现前
references/WISDOM.md	跨项目精华借鉴	架构决策时
references/CONSTRAINTS.md	domain + fatal 约束	规则冲突时
references/USE_CASES.md	全量 KUC-* 业务场景	需要完整示例时
references/LOCKS.md	SL-* + preconditions + hints	生成回测/交易代码前
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-121 blueprint at 2026-04-22T13:00:59.543591+00:00. See human_summary.md for non-technical overview.

---name: ml4t-book-notebooks-2description: 基于《Machine Learning for Trading》第二版配套 notebooks 实现量化交易策略开发与回测，涵盖多市场金融数据的时间序列机器学习分析。触发场景：(1) 用户要复现书中的机器学习交易策略代码；(2) 用户要将 ML 模型用于 A 股或美股市场预测；(3) 用户要获取金融数据并训练自己的量化模型。license: Proprietary. See LICENSE.txt in project root.---### Permission Setup Review`python scripts/_init_dirs.py` is an optional setup helper for the `ml4t-book-notebooks` skill. It may apply broad filesystem permissions for compatibility. Show the target paths and permission mode, explain the risk, and prefer a narrower mode when shared write access is not needed.# ml4t-book-notebooks> 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.)## Pipeline`data_collection -> data_storage -> factor_computation -> target_selection -> trading_execution -> visualization`## Top Use Cases (0 total)## Install```bash# One-time setup before first usebash scripts/install.sh```**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 (15 total)- **`AP-TIME-SERIES-ML-001`**: TimeSeries values array dimensionality mismatch- **`AP-TIME-SERIES-ML-002`**: Non-floating-point dtype in TimeSeries values- **`AP-TIME-SERIES-ML-003`**: Irregular or non-monotonic time indexAll 15 anti-patterns: [references/ANTI_PATTERNS.md](references/ANTI_PATTERNS.md)## Evidence Quality Notice> [QUALITY NOTICE] This crystal was compiled from blueprint finance-bp-121. Evidence verify ratio = 31.8% and audit fail total = 35. 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) | 15 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-121` blueprint at 2026-04-22T13:00:59.543591+00:00.**See [human_summary.md](human_summary.md) for non-technical overview.*

Frequently asked questions