Tushare Data
zillionare/zillionare
面向中文自然语言的 Tushare 数据研究技能。用于把“看看这只股票最近怎么样”“帮我查财报趋势”“最近哪个板块最强”“北向资金在买什么”“给我导出一份行情数据”这类请求，转成可执行的数据获取、清洗、对比、筛选、导出与简要分析流程。适用于 A 股、指数、ETF/基金、财务、估值、资金流、公告新闻、板块概念与宏观数据等研究场景。
Reference of market rules for quant strategies: A-share price limits and T+1, Hong Kong and US trading rules, crypto policy and cross-border tax basics.
SKILL.md written in Chinese; this summary is our English description.
Install Financial Regulation Knowledge Base
$ npx skills add HKUDS/Vibe-Trading --skill regulatory-knowledge -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install HKUDS/Vibe-Trading regulatory-knowledge --agent claude-codeProject scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).
$ git clone --depth 1 https://github.com/HKUDS/Vibe-Trading.git skills-src && mkdir -p .claude/skills && cp -r skills-src/agent/src/skills/regulatory-knowledge .claude/skills/regulatory-knowledge && rm -rf skills-srcUse ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.
Claude Code skills documentation · loads skills from .claude/skills/
Install the "regulatory-knowledge" agent skill from https://github.com/HKUDS/Vibe-Trading/tree/main/agent/src/skills/regulatory-knowledge into .claude/skills/regulatory-knowledge/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "regulatory-knowledge", then confirm the skill loads.Claude Code copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$skill-installer install https://github.com/HKUDS/Vibe-Trading/tree/main/agent/src/skills/regulatory-knowledgeType this inside Codex. $skill-installer <name> installs a curated skill from openai/skills. The installer writes to $CODEX_HOME/skills (default ~/.codex/skills). Restart Codex if the skill does not show up.
$ npx skills add HKUDS/Vibe-Trading --skill regulatory-knowledge -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install HKUDS/Vibe-Trading regulatory-knowledge --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/HKUDS/Vibe-Trading.git skills-src && mkdir -p .agents/skills && cp -r skills-src/agent/src/skills/regulatory-knowledge .agents/skills/regulatory-knowledge && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "regulatory-knowledge" agent skill from https://github.com/HKUDS/Vibe-Trading/tree/main/agent/src/skills/regulatory-knowledge into .agents/skills/regulatory-knowledge/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "regulatory-knowledge", then confirm the skill loads.Codex copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add HKUDS/Vibe-Trading --skill regulatory-knowledge -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install HKUDS/Vibe-Trading regulatory-knowledge --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/HKUDS/Vibe-Trading.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/agent/src/skills/regulatory-knowledge .cursor/skills/regulatory-knowledge && rm -rf skills-srcUse ~/.cursor/skills/ instead of .cursor/skills for a personal install.
Cursor skills documentation · loads skills from .cursor/skills/, .agents/skills/, .claude/skills/, .codex/skills/
Install the "regulatory-knowledge" agent skill from https://github.com/HKUDS/Vibe-Trading/tree/main/agent/src/skills/regulatory-knowledge into .cursor/skills/regulatory-knowledge/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "regulatory-knowledge", then confirm the skill loads.Cursor copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gemini skills install https://github.com/HKUDS/Vibe-Trading.git --path agent/src/skills/regulatory-knowledge--scope user (default) or --scope workspace; --path is the subfolder of the repo that holds the skill; --consent skips the security confirmation prompt.
$ npx skills add HKUDS/Vibe-Trading --skill regulatory-knowledge -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install HKUDS/Vibe-Trading regulatory-knowledge --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/HKUDS/Vibe-Trading.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/agent/src/skills/regulatory-knowledge .gemini/skills/regulatory-knowledge && rm -rf skills-srcUse ~/.gemini/skills/ instead of .gemini/skills for a personal install, then run /skills reload.
Gemini CLI skills documentation · loads skills from .gemini/skills/, .agents/skills/
Install the "regulatory-knowledge" agent skill from https://github.com/HKUDS/Vibe-Trading/tree/main/agent/src/skills/regulatory-knowledge into .gemini/skills/regulatory-knowledge/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "regulatory-knowledge", then confirm the skill loads.Gemini CLI copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gh skill install HKUDS/Vibe-Trading regulatory-knowledgeInstalls for Copilot at project scope by default; add --scope user for a personal install. Preview a skill first with gh skill preview. Needs GitHub CLI 2.90.0 or later (public preview).
$ npx skills add HKUDS/Vibe-Trading --skill regulatory-knowledge -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
$ git clone --depth 1 https://github.com/HKUDS/Vibe-Trading.git skills-src && mkdir -p .github/skills && cp -r skills-src/agent/src/skills/regulatory-knowledge .github/skills/regulatory-knowledge && rm -rf skills-srcUse ~/.copilot/skills/ instead of .github/skills for a personal install. Commit .github/skills so cloud agent and code review can use it.
GitHub Copilot skills documentation · loads skills from .github/skills/, .claude/skills/, .agents/skills/
Install the "regulatory-knowledge" agent skill from https://github.com/HKUDS/Vibe-Trading/tree/main/agent/src/skills/regulatory-knowledge into .github/skills/regulatory-knowledge/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "regulatory-knowledge", then confirm the skill loads.GitHub Copilot copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add HKUDS/Vibe-Trading --skill regulatory-knowledge -a opencodeOpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.
$ gh skill install HKUDS/Vibe-Trading regulatory-knowledge --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/HKUDS/Vibe-Trading.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/agent/src/skills/regulatory-knowledge .opencode/skills/regulatory-knowledge && rm -rf skills-srcUse ~/.config/opencode/skills/ instead of .opencode/skills for a personal install.
OpenCode skills documentation · loads skills from .opencode/skills/, .claude/skills/, .agents/skills/
Install the "regulatory-knowledge" agent skill from https://github.com/HKUDS/Vibe-Trading/tree/main/agent/src/skills/regulatory-knowledge into .opencode/skills/regulatory-knowledge/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "regulatory-knowledge", then confirm the skill loads.OpenCode copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
Facts
- Skill name
regulatory-knowledge- GitHub stars
- 35k
- Token cost
- ~1.3k tokens
- SKILL.md length
- 63 words
- Files
- 1
- Skills in repo
- 89
- Repo updated
- First seen
- Licence
- MIT
At a glance
Reference of market rules for quant strategies: A-share price limits and T+1, Hong Kong and US trading rules, crypto policy and cross-border tax basics.
- Works in 3 steps: 回测规则约束矩阵 → 跨市场策略的合规检查 → 税务影响
- Building trading-rule constraints into a backtest engine for A-shares
- SKILL.md covers 概述, 核心概念, 分析框架 and 输出格式, plus 2 more sections
- Calls pip
What it does
A Chinese-language reference for the market rules a quantitative strategy has to respect. It covers mainland A-share price limits by board, T+1 settlement, margin financing and securities lending, opening and closing auctions and block trades, followed by Hong Kong and US trading rules, cryptocurrency regulation by region and the basics of cross-border taxation.
The skill ties each rule to its effect on backtests, for example that orders at the price limit may not fill and that a T+1 market cannot close a position on the day of the signal. It also provides a rule-constraint matrix across markets, a compliance checklist for cross-market strategies, a tax-impact section and a report format for compliance checks. It warns that rules change over time, so a backtest should use the rules in force on each date. The only dependencies listed are pandas and numpy.
When your agent uses it
- Building trading-rule constraints into a backtest engine for A-shares
- Adapting a strategy that trades across the A-share, Hong Kong and US markets
- Setting compliance and risk-control parameters for a trading strategy
- Folding tax effects into the expected returns of a strategy
Example prompts
- “Which price-limit and T+1 constraints do I need to model in my A-share backtest?”
- “Check whether a long-short pair of one A-share and one Hong Kong stock raises any compliance issues.”
- “Explain how the US pattern day trader rule would limit my intraday strategy.”
- “How should dividend taxes be reflected in the returns of my A-share strategy?”
Requirements
- Python with `pandas` and `numpy`
Workflow steps
3 steps, taken from the step headings in SKILL.md.
What it can do on your machine
Read from SKILL.md and the folder at commit e532650. It shows what the files ask for, not the result of running them.
Tool permissions
Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.
From allowed-tools in the SKILL.md frontmatter.
Runs code
Shell commands in SKILL.md call:
pip
From the folder's file list and the shell code blocks in SKILL.md.
Network
No URLs in SKILL.md. Its commands use pip, which can reach the network depending on how they are called.
From URLs in SKILL.md, links to its own repository left out.
Credentials
Names no API keys, tokens, secrets or passwords.
From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.
Context cost
Financial Regulation Knowledge Base loads about 1.3k tokens when it runs. Until then it costs about 20 tokens; SKILL.md has 63 words of instructions outside code blocks.
Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.
Safety
Auto-check passed
The automated check found no risky patterns in SKILL.md.
Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.
SKILL.md
The full file from HKUDS/Vibe-Trading at commit e532650, republished under its MIT licence (© HKUDS). 63 words, ~1,319 tokens.
Download SKILL.mdSave it as
.claude/skills/regulatory-knowledge/SKILL.md (or your agent's skills folder).- name
- regulatory-knowledge
- description
- 金融监管知识库：A股涨跌停/ST退市新规/融券、港股T+0/做空机制、美股PDT/熔断、加密监管政策、跨境税务基础
- category
- tool
金融监管知识库
概述
量化交易必须理解的各市场监管规则。错误的交易规则假设会导致回测失真（如A股回测不考虑涨跌停限制）、实盘违规（如美股PDT限制）或税务损失。
适用场景：
- 回测引擎中正确实现交易规则约束
- 跨市场策略的规则差异处理
- 合规风控参数设置
- 税务影响纳入策略收益计算
核心概念
A股交易规则
涨跌停制度：
| 板块 | 涨跌停 | 新股首日 | ST涨跌停 |
|---|---|---|---|
| 主板(沪深) | ±10% | +44%/-36% | ±5% |
| 创业板 | ±20% | 前5日无限制 | ±20% |
| 科创板 | ±20% | 前5日无限制 | ±20% |
| 北交所 | ±30% | 前5日无限制 | ±30% |
回测影响:
涨停时买入可能无法成交（封板）→ 信号延迟
跌停时卖出可能无法成交（封板）→ 止损失效
回测实现:
if daily_return >= limit_up:
buy_signal无法执行, 推迟到次日
if daily_return <= limit_down:
sell_signal可能无法执行, 用跌停价模拟成交T+1制度：
A股: T日买入 → T+1日才能卖出
回测影响: 信号在T日产生 → T+1日开盘执行买入 → T+2日最早可卖出
常见错误: 回测中T日信号T日就平仓 → 虚增收益
例外:
- 融券做空: 可T+0(融券卖出当日买券还券)
- ETF套利: 一级市场申赎可实现T+0变相交易
- 可转债: 实行T+0交易融资融券/转融通：
融资(杠杆做多):
保证金比例: ≥100% (即最大杠杆2倍)
维持担保比例: ≥130% (低于则追保; <110%强平)
标的范围: 约1600只(流动性好的主板/创业板股票)
融券(做空):
券源: 证券公司自有+转融通借入
费率: 年化8-10%(远高于美股的1-2%)
限制: 2023年后限制融券T+0, 券源大幅收紧
回测影响:
做空策略在A股成本极高, 需扣除8-10%/年的融券费用
实际可融券标的 < 理论标的 (券源有限)集合竞价与连续竞价：
早盘集合竞价: 9:15-9:25 (9:15-9:20可撤单, 9:20-9:25不可撤单)
9:25 产生开盘价
连续竞价: 9:30-11:30, 13:00-14:57
尾盘集合竞价: 14:57-15:00 (不可撤单)
回测影响:
- 日线回测默认用T+1开盘价成交
- 尾盘3分钟集合竞价: 大单集中, VWAP策略需注意
- 集合竞价期间的限价单可能影响开盘价大宗交易：
时间: 15:00-15:30 (收盘后)
折价: 通常折价3-8% (相对收盘价)
限制: 买入后6个月内不能在二级市场卖出(大股东减持用)
信号意义:
大宗交易频繁 + 折价大 → 可能有减持需求(利空)
大宗交易后6个月解禁 → 关注解禁日卖压港股交易规则
交易时间:
早盘竞价: 9:00-9:30
连续交易: 9:30-12:00, 13:00-16:00
收市竞价: 16:00-16:10
核心差异(vs A股):
✓ T+0交易 (当日买当日可卖)
✓ 无涨跌停限制 (个股单日可涨跌50%+)
✓ 做空机制完善 (融券成本低, 约1-3%/年)
✓ 暗盘交易 (IPO上市前一晚的灰市交易)
✗ 流动性差 (日成交额仅A股的1/10-1/5)
✗ 仙股多 (大量股价<0.1港元的小票)
做空规则:
- 只能以不低于最佳卖盘价做空 (uptick rule变体)
- 需先借入股份才能做空 (naked short prohibited)
- 做空头寸需每日报告 (达到0.02%阈值时)
交收制度:
T+2交收 (买入T+2日才能提取股份)
但交易可T+0 (预付制度下)
回测影响:
- 无涨跌停 → 极端波动大, 止损更重要
- T+0 → 日内策略可行
- 流动性低 → 小盘股滑点大, 冲击成本需纳入美股交易规则
交易时间(北京时间):
夏令时: 21:30-04:00
冬令时: 22:30-05:00
盘前: 16:00-21:30 / 17:00-22:30
盘后: 04:00-08:00 / 05:00-09:00
PDT规则(Pattern Day Trader):
条件: 5个交易日内日内交易(当日开平) ≥ 4次
触发后: 账户需维持 ≥ $25,000 余额
低于$25,000: 账户被限制90天只能平仓
规避方法:
- 使用现金账户(Cash Account, T+2交收, 无PDT限制但资金效率低)
- 账户维持 > $25,000
- 控制日内交易频率 < 4次/5日
熔断机制:
Level 1: S&P 500下跌 7% → 暂停15分钟 (15:25后不触发)
Level 2: S&P 500下跌13% → 暂停15分钟 (15:25后不触发)
Level 3: S&P 500下跌20% → 当日停止交易
个股LULD(Limit Up-Limit Down):
涨跌幅超过参考价±5%(大盘股)/±10%(小盘股) → 暂停5分钟
RegSHO(做空规则):
- Locate requirement: 做空前必须确认可借到股份
- Close-out: 连续13天无法交割 → 强制平仓
- Short Sale Circuit Breaker: 个股跌>10% → 当日+次日只能uptick做空
回测影响:
- 美股无日常涨跌停 → 但有LULD暂停
- T+0交易(保证金账户) → 日内策略可行
- 盘前盘后交易量低, 滑点大加密货币监管
主要市场政策(截至2026):
中国大陆: 禁止交易所运营和ICO, 但持有不违法
香港: VASP牌照制度, 合规交易所(HashKey等)
美国: SEC/CFTC双重监管, BTC/ETH现货ETF已获批
欧盟: MiCA法规2024年全面生效
日本: FSA监管, 交易所需注册
新加坡: MAS监管, Payment Services Act
稳定币监管趋势:
- USDT: 储备金透明度争议, 部分地区限制
- USDC: 合规性更好, Circle受美国监管
- 各国推进央行数字货币(CBDC)可能替代
DeFi合规:
- 大部分DeFi协议目前处于监管灰色地带
- 趋势: 要求前端KYC, 链上交易仍自由
- 风险: 智能合约风险不受投资者保护法覆盖
回测影响:
- 加密市场7×24交易, 无休市
- 无涨跌停限制, 极端波动可达50%+/日
- 交易所间价差可达1-3%(套利机会但也有风险)
- OKX等主流所杠杆最高125x(合约), 回测需正确计算爆仓价分析框架
1. 回测规则约束矩阵
| 规则 | A股 | 港股 | 美股 | 加密(OKX) |
|------|-----|------|------|-----------|
| 涨跌停 | ±10/20/30% | 无 | LULD暂停 | 无 |
| T+N | T+1 | T+0 | T+0(保证金) | T+0 |
| 做空 | 融券(贵) | 容易 | 容易 | 永续合约 |
| 交易时间 | 4h/日 | 5.5h/日 | 6.5h/日 | 24/7 |
| 手续费 | 0.025%+印花税0.05% | 0.03%+印花税0.1% | $0(部分) | 0.02-0.05% |
| 最小交易单位 | 100股 | 1手(不等) | 1股 | 0.001BTC |2. 跨市场策略的合规检查
检查清单:
□ 交易时间是否重叠(时区转换)
□ 各市场假期差异(A股春节/国庆 vs 美股圣诞/感恩节)
□ 汇率风险是否纳入(人民币/港币/美元/USDT)
□ 做空可行性(A股策略中做空信号能否执行)
□ 最小交易单位约束(A股100股整手 → 小资金可能无法精确配比)
□ 印花税/证管费等隐含成本是否纳入
A股真实交易成本:
佣金: 0.025% (万2.5, 最低5元/笔)
印花税: 0.05% (卖出时, 2023年减半)
过户费: 0.001%
规费: 0.00687%
合计(单边): 约0.08%
合计(双边): 约0.16%
影响: 月换手1次 → 年化成本约1.9%
月换手4次 → 年化成本约7.7%3. 税务影响
A股:
股票买卖: 免个人所得税（2024年继续免征）
股息税: 持有>1年免税; 1个月-1年=10%; <1个月=20%
基金分红: 免个人所得税
回测影响: 高股息策略需考虑持有期的税务差异
年化股息5% × 20%税率 = 1%的税务拖累（短期持有时）
港股(通过港股通):
股息税: 20%（H股）或 10%（红筹/民企）
资本利得: 免税
注意: 港股通股息税由中国结算代扣
美股:
股息税: 10%(中美税收协定)
资本利得: 目前中国居民暂免, 但需关注政策变化
W-8BEN表格: 券商要求填写以享受协定税率
加密货币:
中国: 暂无明确税收规定（但大额交易可能被追溯）
美国: 资本利得税(短期=普通收入税率, 长期=0/15/20%)
回测影响: 如计入税务, 频繁交易策略的净收益下降显著输出格式
合规检查报告：
=== 策略合规检查 ===
策略: A股+港股 多空配对交易
标的: 600519.SH (贵州茅台) + 0700.HK (腾讯)
=== 规则约束 ===
A股做空: 需融券 → 600519融券费率约8%/年, 券源有限
港股做空: 0700.HK做空成本约1.5%/年, 券源充足
T+N差异: A股T+1 vs 港股T+0 → 配对信号执行有时差
涨跌停: A股±10% 可能阻止止损执行
交易时间: A股9:30-15:00 vs 港股9:30-16:00 → 14:57-16:00港股单边暴露
=== 成本估算 ===
A股交易成本: 0.16%/双边
港股交易成本: 0.26%/双边 (含印花税0.1%)
融券成本(A股): 8%/年
融券成本(港股): 1.5%/年
汇率对冲成本: 约1%/年
=== 建议 ===
1. A股端用股指期货替代融券做空 → 成本降至2-3%/年
2. 配对交易信号在14:57前执行A股端, 港股端可延迟
3. 汇率风险: 人民币/港币波动约±3%/年, 小于策略预期收益则可不对冲注意事项
- 规则动态变化：监管规则频繁调整（如2023年印花税减半、融券T+0限制），回测需按历史时点使用对应规则
- 回测 vs 实盘差距：涨跌停封板无法成交是回测最大失真来源，高换手策略需严格建模
- A股特殊时段：集合竞价9:15-9:25和尾盘14:57-15:00规则与连续竞价不同，信号执行需区分
- 跨市场假期：A股春节休市约10天，期间港美股和加密市场正常交易，需处理信号中断
- 监管风险溢价：加密市场政策不确定性本身是风险因子，应在策略中纳入
- 券商差异：不同券商的佣金率、融券费率、系统延迟差异显著，回测参数应取保守值
依赖
pip install pandas numpy© HKUDS, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file
Files
Just SKILL.md in agent/src/skills/regulatory-knowledge of HKUDS/Vibe-Trading.
Open the folder on GitHubat commit e532650
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Questions about Financial Regulation Knowledge Base
What does Financial Regulation Knowledge Base do?
Reference of market rules for quant strategies: A-share price limits and T+1, Hong Kong and US trading rules, crypto policy and cross-border tax basics. A Chinese-language reference for the market rules a quantitative strategy has to respect. It covers mainland A-share price limits by board, T+1 settlement, margin financing and securities lending, opening and closing auctions and block trades, followed by Hong Kong and US trading rules, cryptocurrency regulation by region and the basics of cross-border taxation.
When should I use Financial Regulation Knowledge Base?
Financial Regulation Knowledge Base fits situations like: building trading-rule constraints into a backtest engine for A-shares; adapting a strategy that trades across the A-share, Hong Kong and US markets; setting compliance and risk-control parameters for a trading strategy; folding tax effects into the expected returns of a strategy.
How do I install Financial Regulation Knowledge Base in Claude Code?
Run `npx skills add HKUDS/Vibe-Trading --skill regulatory-knowledge -a claude-code`. Or copy the skill folder (agent/src/skills/regulatory-knowledge in HKUDS/Vibe-Trading) into .claude/skills/regulatory-knowledge in your project. Claude Code loads it when a task matches its description.
How do I install Financial Regulation Knowledge Base in Codex?
Run `npx skills add HKUDS/Vibe-Trading --skill regulatory-knowledge -a codex`. Or copy the skill folder (agent/src/skills/regulatory-knowledge in HKUDS/Vibe-Trading) into .agents/skills/regulatory-knowledge in your project. Codex loads it when a task matches its description.
Can I use Financial Regulation Knowledge Base in Cursor, Gemini CLI or GitHub Copilot?
Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add HKUDS/Vibe-Trading --skill regulatory-knowledge -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/regulatory-knowledge, .gemini/skills/regulatory-knowledge, .github/skills/regulatory-knowledge and .opencode/skills/regulatory-knowledge in your project.
What does Financial Regulation Knowledge Base need to run?
Going by SKILL.md and its folder, Financial Regulation Knowledge Base needs the command-line tools its instructions call (pip). Our summary lists: Python with `pandas` and `numpy`.
Does Financial Regulation Knowledge Base access the network?
SKILL.md contains no URLs. Its commands use pip, which can reach the network depending on how they are called. This is read from the text; nothing was executed.
Is Financial Regulation Knowledge Base safe to install?
Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.
What licence does Financial Regulation Knowledge Base use?
Financial Regulation Knowledge Base is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.
How many tokens does Financial Regulation Knowledge Base use?
About 1.3k tokens (SKILL.md is roughly 5.3k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.
What are the alternatives to Financial Regulation Knowledge Base?
Skills that share tags, products or a category with Financial Regulation Knowledge Base: Tushare Data (zillionare/zillionare, 321 stars), Quant Blog Writing (zillionare/zillionare, 321 stars), Vectorbt (agiprolabs/claude-trading-skills, 410 stars) and Multi-Symbol Market Scanner (tradesdontlie/tradingview-mcp, 6.8k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
Who maintains Financial Regulation Knowledge Base?
HKUDS (a GitHub organization) maintains it in HKUDS/Vibe-Trading, which has 35,043 GitHub stars. The repository holds 89 skills in this directory. The repository was last updated on October 8, 2026.
Source: HKUDS/Vibe-Trading on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.