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。
Factor discovery. An agent skill from VernonOY/alpha-skills.
Install Alpha Discover
$ npx skills add VernonOY/alpha-skills --skill alpha-discover -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install VernonOY/alpha-skills alpha-discover --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/VernonOY/alpha-skills.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/alpha-discover .claude/skills/alpha-discover && 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 "alpha-discover" agent skill from https://github.com/VernonOY/alpha-skills/tree/main/skills/alpha-discover into .claude/skills/alpha-discover/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "alpha-discover", 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/VernonOY/alpha-skills/tree/main/skills/alpha-discoverType 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 VernonOY/alpha-skills --skill alpha-discover -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install VernonOY/alpha-skills alpha-discover --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/VernonOY/alpha-skills.git skills-src && mkdir -p .agents/skills && cp -r skills-src/skills/alpha-discover .agents/skills/alpha-discover && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "alpha-discover" agent skill from https://github.com/VernonOY/alpha-skills/tree/main/skills/alpha-discover into .agents/skills/alpha-discover/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "alpha-discover", 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 VernonOY/alpha-skills --skill alpha-discover -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install VernonOY/alpha-skills alpha-discover --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/VernonOY/alpha-skills.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/skills/alpha-discover .cursor/skills/alpha-discover && 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 "alpha-discover" agent skill from https://github.com/VernonOY/alpha-skills/tree/main/skills/alpha-discover into .cursor/skills/alpha-discover/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "alpha-discover", 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/VernonOY/alpha-skills.git --path skills/alpha-discover--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 VernonOY/alpha-skills --skill alpha-discover -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install VernonOY/alpha-skills alpha-discover --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/VernonOY/alpha-skills.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/skills/alpha-discover .gemini/skills/alpha-discover && 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 "alpha-discover" agent skill from https://github.com/VernonOY/alpha-skills/tree/main/skills/alpha-discover into .gemini/skills/alpha-discover/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "alpha-discover", 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 VernonOY/alpha-skills alpha-discoverInstalls 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 VernonOY/alpha-skills --skill alpha-discover -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
$ git clone --depth 1 https://github.com/VernonOY/alpha-skills.git skills-src && mkdir -p .github/skills && cp -r skills-src/skills/alpha-discover .github/skills/alpha-discover && 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 "alpha-discover" agent skill from https://github.com/VernonOY/alpha-skills/tree/main/skills/alpha-discover into .github/skills/alpha-discover/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "alpha-discover", 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 VernonOY/alpha-skills --skill alpha-discover -a opencodeOpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.
$ gh skill install VernonOY/alpha-skills alpha-discover --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/VernonOY/alpha-skills.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/skills/alpha-discover .opencode/skills/alpha-discover && 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 "alpha-discover" agent skill from https://github.com/VernonOY/alpha-skills/tree/main/skills/alpha-discover into .opencode/skills/alpha-discover/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "alpha-discover", 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
alpha-discover- GitHub stars
- 117
- Token cost
- ~1.6k tokens
- SKILL.md length
- 512 words
- Files
- 1
- Skills in repo
- 9
- Repo updated
- First seen
- Licence
- Apache-2.0
At a glance
Factor discovery. An agent skill from VernonOY/alpha-skills.
- Works in 4 steps: 理解用户意图 / Understand User Intent → 映射到内置因子或生成新表达式 / Map to Built-in or… → 展示设计结果 / Present Design Result → …
- Tasks that involve Trading and backtesting
- SKILL.md covers Bilingual Terms / 双语术语, 项目定位 / Project Context, 因子设计流程 / Factor Design Pipeline and 复合因子设计 / Composite Factor Design, plus 1 more section
- Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md
What it does
Alpha Discover is an agent skill from VernonOY/alpha-skills. Factor discovery. Design factors from natural language descriptions. 因子发现。根据自然语言描述设计因子。 Triggers: "design a factor", "find a factor", "帮我找一个因子", "设计因子"
Its SKILL.md is about 1.6k tokens, which your agent loads only when the skill is triggered. It is a single SKILL.md file with no bundled scripts.
It sits in Business, Finance & HR, covering Trading and backtesting. The repository describes itself as: Quantitative factor research skills for AI coding assistants. The licence is Apache-2.0.
When your agent uses it
- Tasks that involve Trading and backtesting
Example prompts
- “design a factor”
- “find a factor”
- “帮我找一个因子”
- “/alpha-discover”
Requirements
- Python 3
Workflow steps
4 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 f58f80a. 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
No scripts in the folder and no shell commands in SKILL.md (its code samples are markdown and python).
From the folder's file list and the shell code blocks in SKILL.md.
Network
No URLs in SKILL.md.
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
Alpha Discover loads about 1.6k tokens when it runs. Until then it costs about 42 tokens; SKILL.md has 512 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 VernonOY/alpha-skills at commit f58f80a, republished under its Apache-2.0 licence (© VernonOY). 512 words, ~1,574 tokens.
Download SKILL.mdSave it as
.claude/skills/alpha-discover/SKILL.md (or your agent's skills folder).- name
- alpha-discover
- description
- Factor discovery. Design factors from natural language descriptions. 因子发现。根据自然语言描述设计因子。 Triggers: "design a factor", "find a factor", "帮我找一个因子", "设计因子"
alpha-discover — Factor Discovery / 因子发现
你是一个资深量化研究员。当用户描述一个因子idea时，将其转化为可计算的因子定义，并自动评估。 You are a senior quant researcher. Convert user's factor ideas into computable definitions and auto-evaluate.
Bilingual Terms / 双语术语
| English | 中文 |
|---|---|
| Factor | 因子 |
| IC (Information Coefficient) | 信息系数 |
| ICIR (IC Information Ratio) | IC信息比率 |
| Quintile | 五分位/分组 |
| Long-Short | 多空 |
| Sharpe Ratio | 夏普比率 |
| Max Drawdown | 最大回撤 |
| Monotonicity | 单调性 |
| Robustness | 鲁棒性 |
| Holding Period | 持有期 |
| Factor Registry | 因子注册表 |
| Backtest | 回测 |
| Gate Check | 门控检查 |
项目定位 / Project Context
Multi-Market Support / 多市场支持:
Alpha Skills support A-share (default), HK, and US stocks via data adapters: Alpha Skills 通过数据适配器支持A股（默认）、港股和美股：
# .claude/alpha-agent.config.md
MARKET: A-share # or "HK" or "US"
DATA_MODULE: (leave empty for A-share Tushare default)
# or "examples.us_data_yfinance"
# or "examples.hk_data_yfinance"When a custom DATA_MODULE is set, the skill loads MARKET_CONFIG from that module to determine benchmark, cost rate, and trading rules. 设置自定义DATA_MODULE时，skill从该模块加载MARKET_CONFIG来确定基准、成本和交易规则。
因子设计流程 / Factor Design Pipeline
Language Rule / 语言规则:
- If the user speaks English, output in English
- If the user speaks Chinese, output in Chinese
- Table headers always show both languages: "IC Mean IC均值"
Step 1: 理解用户意图 / Understand User Intent
分析用户的描述，识别：
- 因子类型 Factor Type（量价 Price-Volume / 基本面 Fundamental / 估值 Valuation / 技术面 Technical / 资金流 Capital Flow / 复合 Composite）
- 核心逻辑 Core Logic（动量 Momentum / 反转 Reversal / 波动 Volatility / 价值 Value / 质量 Quality / 成长 Growth 等）
- 涉及的数据字段 Data Fields（close/volume/daily_basic/fina等）
- 时间窗口偏好 Time Window（用户有没有提到"短期""20天" / "short-term", "20 days"等）
Step 2: 映射到内置因子或生成新表达式 / Map to Built-in or Generate New Expression
情况A: 可映射到内置因子 / Case A: Maps to Built-in Factor
内置因子列表 / Built-in Factor List：
| Name 名称 | Function Call 函数调用 | Required Data 所需数据 |
|---|---|---|
| momentum_N | momentum(close, N) | close |
| reversal_N | reversal(close, N) | close |
| volatility_N | volatility(close, N) | close |
| pv_diverge | price_volume_divergence(close, volume, 20) | close, volume |
| turnover_N | turnover_rate(daily_basic, N) | daily_basic |
| abnormal_turnover | abnormal_turnover(daily_basic) | daily_basic |
| rsi_N | rsi(close, N) | close |
| macd | macd_divergence(close) | close |
| bollinger | bollinger_position(close) | close |
| atr_ratio | atr_ratio(high, low, close) | high, low, close |
| pe_ttm | pe_ttm(daily_basic) | daily_basic |
| pb | pb(daily_basic) | daily_basic |
| ps_ttm | ps_ttm(daily_basic) | daily_basic |
| dividend_yield | dividend_yield(daily_basic) | daily_basic |
| roe | roe(fina) | fina |
| roa | roa(fina) | fina |
| gross_margin | gross_margin(fina) | fina |
| net_profit_growth | net_profit_growth(fina) | fina |
| revenue_growth | revenue_growth(fina) | fina |
| earnings_accel | earnings_acceleration(fina) | fina |
| peg | peg(daily_basic, fina) | daily_basic, fina |
| quality | quality_score(fina) | fina |
| value | value_score(daily_basic) | daily_basic |
| growth_momentum | growth_momentum(fina, close) | fina, close |
如果用户描述能映射到内置因子，告知用户并建议直接评估。 If the description maps to a built-in factor, inform the user and suggest direct evaluation.
Show full SKILL.md (196 more words)Show less
情况B: 需要设计新因子 / Case B: New Factor Needed
使用现有算子组合生成Python代码。可用的基础操作 / Available base operations：
close.pct_change(N)— N-day return / N日收益率close.rolling(N).mean()— N-day moving average / N日均线close.rolling(N).std()— N-day volatility / N日波动率close.rolling(N).corr(volume)— Rolling correlation / 滚动相关性close.ewm(span=N).mean()— Exponential moving average / 指数移动平均close.diff(N)— N-day change / N日变化量close.rank(axis=1, pct=True)— Cross-sectional rank / 截面排名
生成的因子代码应遵循约定 / Generated factor code conventions：
- 输入 Input: DataFrame (index=日期 date, columns=股票代码 stock code)
- 输出 Output: DataFrame (同格式 same format, 值越大越看好 higher=more bullish)
- 如原始含义"越小越好"，取负 / If lower is better, negate
Step 3: 展示设计结果 / Present Design Result
输出格式 / Output Format：
📐 Factor Design / 因子设计
Name 名称: <factor_name>
Category 类别: <Price-Volume 量价 / Fundamental 基本面 / Valuation 估值 / Composite 复合>
Logic 逻辑: <one-sentence economic intuition / 一句话解释因子经济直觉>
Expression 表达式: <Python code or built-in function call>
Required Data 所需数据: <close/volume/daily_basic/fina>
Evaluate this factor? / 是否评估这个因子？Step 4: 用户确认后自动评估 / Auto-evaluate After Confirmation
如果用户确认要评估，按照 alpha-evaluate skill 的流程执行完整评估。 If the user confirms, run the full evaluation pipeline per alpha-evaluate skill.
复合因子设计 / Composite Factor Design
当用户要求"结合多个维度"或"综合因子" / When user asks for "combine multiple dimensions" or "composite factor"：
- 选择2-4个子因子 / Select 2-4 sub-factors
- 各子因子截面标准化 / Cross-sectional standardize each (
standardize()) - 加权求和（默认等权，可调整）/ Weighted sum (equal weight by default, adjustable)
- 生成Python代码示例 / Generate Python code example
示例 / Example：
# 因子函数和预处理函数定义参见 alpha-evaluate skill（自包含，无外部依赖）
# Factor and preprocessing function definitions: see alpha-evaluate skill (self-contained, no external deps)
# def reversal(close, period=5): return -close.pct_change(period)
# def price_volume_divergence(close, volume, period=20): ...
# def rsi(close, period=14): ...
# def standardize(df, mad_n=5): ...
f1 = standardize(reversal(close, 5))
f2 = standardize(price_volume_divergence(close, volume, 20))
f3 = standardize(rsi(close, 14))
composite = 0.4 * f1 + 0.4 * f2 + 0.2 * f3注意事项 / Notes
- 始终解释因子的经济直觉 / Always explain the economic intuition（为什么这个因子可能有效 / why this factor might work）
- 警告潜在的陷阱 / Warn about pitfalls（如未来函数 look-ahead bias、过拟合风险 overfitting risk）
- 基本面因子必须使用ann_date对齐 / Fundamental factors must align by ann_date（项目已处理 handled by project）
- 如果用户描述太模糊，追问细节 / If description is too vague, ask for details
- 建议先用内置因子，再考虑自定义 / Suggest built-in factors before custom ones
© VernonOY, Apache-2.0. 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 skills/alpha-discover of VernonOY/alpha-skills.
Open the folder on GitHubat commit f58f80a
Compare with similar skills
Alpha Discover next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.
| Skill | Stars | Used in | Tokens | Auto-check | Licence | Repo updated |
|---|---|---|---|---|---|---|
| Alpha Discover this skillVernonOY/alpha-skills | 117 | — | ~1.6k | Automated safety check: Pass | Apache-2.0 | |
| Tushare Datazillionare/zillionare | 321 | 2 repos | ~2.3k | Automated safety check: Pass | None | |
| Tradingview MCPatilaahmettaner/tradingview-mcp | 5k | — | ~1.3k | Automated safety check: Pass | MIT | |
| Digital Oraclekomako-workshop/digital-oracle | 875 | — | ~5.9k | Automated safety check: Pass | MIT | |
| Polyclawchainstacklabs/polyclaw | 359 | 1 repos | ~2k | Automated safety check: Pass | Apache-2.0 | |
| Markdownfacioquo/stock-indicators-dotnet | 1.2k | — | ~812 | Automated safety check: Pass | Apache-2.0 |
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Categories
Questions about Alpha Discover
What does Alpha Discover do?
Factor discovery. An agent skill from VernonOY/alpha-skills. Alpha Discover is an agent skill from VernonOY/alpha-skills. Factor discovery.
When should I use Alpha Discover?
Alpha Discover fits situations like: tasks that involve Trading and backtesting.
How do I install Alpha Discover in Claude Code?
Run `npx skills add VernonOY/alpha-skills --skill alpha-discover -a claude-code`. Or copy the skill folder (skills/alpha-discover in VernonOY/alpha-skills) into .claude/skills/alpha-discover in your project. Claude Code loads it when a task matches its description.
How do I install Alpha Discover in Codex?
Run `npx skills add VernonOY/alpha-skills --skill alpha-discover -a codex`. Or copy the skill folder (skills/alpha-discover in VernonOY/alpha-skills) into .agents/skills/alpha-discover in your project. Codex loads it when a task matches its description.
Can I use Alpha Discover 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 VernonOY/alpha-skills --skill alpha-discover -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/alpha-discover, .gemini/skills/alpha-discover, .github/skills/alpha-discover and .opencode/skills/alpha-discover in your project.
What does Alpha Discover need to run?
SKILL.md names no scripts, command-line tools or credentials: Alpha Discover is instructions for the agent only. Our summary lists: Python 3.
Does Alpha Discover access the network?
SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.
Is Alpha Discover 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 Alpha Discover use?
Alpha Discover is published under the Apache-2.0 licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.
How many tokens does Alpha Discover use?
About 1.6k tokens (SKILL.md is roughly 6.3k 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 Alpha Discover?
Skills that share tags, products or a category with Alpha Discover: Tushare Data (zillionare/zillionare, 321 stars), Tradingview MCP (atilaahmettaner/tradingview-mcp, 5k stars), Digital Oracle (komako-workshop/digital-oracle, 875 stars) and Polyclaw (chainstacklabs/polyclaw, 359 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
Who maintains Alpha Discover?
VernonOY (a GitHub user) maintains it in VernonOY/alpha-skills, which has 117 GitHub stars. The repository holds 9 skills in this directory. The repository was last updated on April 14, 2026.
Source: VernonOY/alpha-skills on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.