Technical Analyst
tradermonty/claude-trading-skills
This skill should be used when analyzing weekly price charts for stocks, stock indices, cryptocurrencies, or forex pairs.
使用正式因子模型进行系统化多因子A股筛选，识别具有有利因子暴露的个股。当用户询问因子投资、多因子筛选、价值/动量/质量因子分析、因子打分、因子择时、Smart Beta策略、量化选股或基于学术因子的系统化选股时使用此技能。
Install Quant Factor Screener
$ npx skills add Geeksfino/finskills --skill quant-factor-screener -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install Geeksfino/finskills quant-factor-screener --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/Geeksfino/finskills.git skills-src && mkdir -p .claude/skills && cp -r skills-src/China-market/quant-factor-screener .claude/skills/quant-factor-screener && 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 "quant-factor-screener" agent skill from https://github.com/Geeksfino/finskills/tree/main/China-market/quant-factor-screener into .claude/skills/quant-factor-screener/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "quant-factor-screener", 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/Geeksfino/finskills/tree/main/China-market/quant-factor-screenerType 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 Geeksfino/finskills --skill quant-factor-screener -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install Geeksfino/finskills quant-factor-screener --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/Geeksfino/finskills.git skills-src && mkdir -p .agents/skills && cp -r skills-src/China-market/quant-factor-screener .agents/skills/quant-factor-screener && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "quant-factor-screener" agent skill from https://github.com/Geeksfino/finskills/tree/main/China-market/quant-factor-screener into .agents/skills/quant-factor-screener/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "quant-factor-screener", 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 Geeksfino/finskills --skill quant-factor-screener -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install Geeksfino/finskills quant-factor-screener --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/Geeksfino/finskills.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/China-market/quant-factor-screener .cursor/skills/quant-factor-screener && 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 "quant-factor-screener" agent skill from https://github.com/Geeksfino/finskills/tree/main/China-market/quant-factor-screener into .cursor/skills/quant-factor-screener/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "quant-factor-screener", 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/Geeksfino/finskills.git --path China-market/quant-factor-screener--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 Geeksfino/finskills --skill quant-factor-screener -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install Geeksfino/finskills quant-factor-screener --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/Geeksfino/finskills.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/China-market/quant-factor-screener .gemini/skills/quant-factor-screener && 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 "quant-factor-screener" agent skill from https://github.com/Geeksfino/finskills/tree/main/China-market/quant-factor-screener into .gemini/skills/quant-factor-screener/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "quant-factor-screener", 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 Geeksfino/finskills quant-factor-screenerInstalls 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 Geeksfino/finskills --skill quant-factor-screener -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
$ git clone --depth 1 https://github.com/Geeksfino/finskills.git skills-src && mkdir -p .github/skills && cp -r skills-src/China-market/quant-factor-screener .github/skills/quant-factor-screener && 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 "quant-factor-screener" agent skill from https://github.com/Geeksfino/finskills/tree/main/China-market/quant-factor-screener into .github/skills/quant-factor-screener/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "quant-factor-screener", 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 Geeksfino/finskills --skill quant-factor-screener -a opencodeOpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.
$ gh skill install Geeksfino/finskills quant-factor-screener --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/Geeksfino/finskills.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/China-market/quant-factor-screener .opencode/skills/quant-factor-screener && 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 "quant-factor-screener" agent skill from https://github.com/Geeksfino/finskills/tree/main/China-market/quant-factor-screener into .opencode/skills/quant-factor-screener/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "quant-factor-screener", 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
quant-factor-screener- GitHub stars
- 282
- Token cost
- ~589 tokens
- SKILL.md length
- 144 words
- Files
- 4 (incl. references)
- Skills in repo
- 30
- Repo updated
- First seen
- Licence
- Apache-2.0
At a glance
使用正式因子模型进行系统化多因子A股筛选，识别具有有利因子暴露的个股。当用户询问因子投资、多因子筛选、价值/动量/质量因子分析、因子打分、因子择时、Smart Beta策略、量化选股或基于学术因子的系统化选股时使用此技能。
- Works in 4 steps: 计算每只股票的原始指标 → 在行业内（行业中性时）或全选股池内排名 → 将排名转换为百分位得分（0–100） → …
- Business, Finance & HR work in your project
- SKILL.md covers 工作流程, 数据增强 and 重要注意事项
- Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md
What it does
Quant Factor Screener is an agent skill from Geeksfino/finskills. 使用正式因子模型进行系统化多因子A股筛选，识别具有有利因子暴露的个股。当用户询问因子投资、多因子筛选、价值/动量/质量因子分析、因子打分、因子择时、Smart Beta策略、量化选股或基于学术因子的系统化选股时使用此技能。
Its SKILL.md is about 590 tokens, which your agent loads only when the skill is triggered. The skill folder holds 4 other files, including reference files (for example `references/factor-methodology.md` and `references/output-template.md`).
It sits in Business, Finance & HR. The repository describes itself as: Financial engineering and risk/compliance skills for agents. The licence is Apache-2.0.
When your agent uses it
- Business, Finance & HR work in your project
Example prompts
- “/quant-factor-screener”
Workflow steps
4 steps, taken from the first numbered list in SKILL.md.
- 计算每只股票的原始指标
- 在行业内（行业中性时）或全选股池内排名
- 将排名转换为百分位得分（0–100）
- 将子指标合成为综合因子得分
What it can do on your machine
Read from SKILL.md and the folder at commit 8722415. 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.
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
Quant Factor Screener loads about 589 tokens when it runs, and up to ~3.9k if it reads all its reference files. Until then it costs about 33 tokens; SKILL.md has 144 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 Geeksfino/finskills at commit 8722415, republished under its Apache-2.0 licence (© Geeksfino). 144 words, ~589 tokens.
Download SKILL.mdSave it as
.claude/skills/quant-factor-screener/SKILL.md (or your agent's skills folder). This skill also uses 3 other files; get the full folder from GitHub.- name
- quant-factor-screener
- description
- 使用正式因子模型进行系统化多因子A股筛选，识别具有有利因子暴露的个股。当用户询问因子投资、多因子筛选、价值/动量/质量因子分析、因子打分、因子择时、Smart Beta策略、量化选股或基于学术因子的系统化选股时使用此技能。
- license
- Apache-2.0
量化因子筛选器
扮演量化权益分析师。使用基于学术因子研究的系统化多因子框架筛选A股——对价值、动量、质量、低波动、规模和成长因子进行评分和排名。
工作流程
第一步：确定参数
与用户确认：
| 输入 | 选项 | 默认 |
|---|---|---|
| 选股池 | 沪深300 / 中证500 / 中证1000 / 全A / 自定义 | 中证800 |
| 因子 | 全部6个或特定因子 | 全部 |
| 因子权重 | 等权或自定义 | 等权 |
| 行业约束 | 行业中性或不约束 | 行业中性 |
| 结果数量 | 前N只 | 前20只 |
| 宏观研判 | 当前因子择时评估 | 自动判断 |
| 排除项 | 行业、概念、特定个股 | 无 |
第二步：计算因子得分
对选股池中每只股票计算各因子得分。详细定义参见 references/factor-methodology.md。
| 因子 | 主要指标 | 默认权重 |
|---|---|---|
| 价值 | 盈利收益率、PB倒数、FCF收益率、EV/EBITDA | 1/6 |
| 动量 | 12-1月价格动量、盈利预期修正动量 | 1/6 |
| 质量 | ROE、盈利稳定性、低杠杆、应计质量 | 1/6 |
| 低波动 | 已实现波动率（1年）、Beta、下行偏差 | 1/6 |
| 规模 | 市值（越小得分越高） | 1/6 |
| 成长 | 营收增速、盈利增速、利润率扩张 | 1/6 |
对每个因子：
- 计算每只股票的原始指标
- 在行业内（行业中性时）或全选股池内排名
- 将排名转换为百分位得分（0–100）
- 将子指标合成为综合因子得分
第三步：合成得分
综合得分 = Σ (因子权重 × 因子得分)按综合得分从高到低排列所有股票。
第四步：因子择时评估
评估当前宏观环境及其对因子表现的影响。参见 references/factor-methodology.md。
| 宏观环境 | 利好因子 | 不利因子 |
|---|---|---|
| 经济复苏初期 | 规模、动量 | 低波动 |
| 经济扩张中期 | 动量、成长 | 价值 |
| 经济扩张末期 | 质量、价值 | 规模 |
| 经济下行 | 低波动、质量 | 动量、规模 |
| 经济触底 | 价值、规模、动量 | 低波动 |
基于当前研判，提供因子择时叠加以调整权重。
第五步：因子拥挤度分析
评估热门因子是否过度拥挤：
| 信号 | 拥挤 | 不拥挤 |
|---|---|---|
| 估值价差 | 因子内高低分组估值差收窄 | 估值差扩大 |
| 因子收益相关性 | 高（许多人跟随相同信号） | 低 |
| ETF/基金资金流入 | 因子相关产品大量净申购 | 净赎回 |
| 媒体/分析师关注 | 被广泛讨论 | 被忽视 |
标记拥挤的因子——收益可能被压缩。
第六步：呈现结果
格式参见 references/output-template.md：
- 宏观环境研判 — 当前阶段和因子择时观点
- 因子拥挤度面板 — 哪些因子拥挤/不拥挤
- 精选个股表 — 前N只股票的各因子得分和综合得分
- 行业分布 — 精选结果的行业分布
- 因子暴露汇总 — 精选列表的整体因子特征
- 个股简介 — 每只精选个股的简要画像
- 风险提示 — 因子回撤历史和当前风险
- 免责声明
数据增强
如需实时市场数据支撑分析，请使用金融数据工具包技能（findata-toolkit-cn）。该工具包提供A股实时行情、财务指标、董监高增减持、北向资金、宏观数据等功能，所有数据源免费，无需API密钥。
重要注意事项
- 因子不是万能的：因子有长期跑输的时候。A股的价值因子在2019–2020年严重跑输。动量因子会周期性崩溃。设定合理预期。
- 行业中性很重要：不做行业约束的因子筛选常常产出伪装成因子赌注的行业集中赌注。
- A股因子特殊性：低波动异象在A股非常显著；动量因子因散户主导的市场结构而表现不同；小盘因子溢价受壳价值和流动性溢价影响。
- 换手率因子：A股中换手率是一个独特且有效的负向因子（低换手率→高收益），这在成熟市场中不那么显著。
- 多因子更稳健：没有单一因子永远有效。组合因子可降低回撤、平滑收益。
- 交易成本：动量策略换手率高。需考虑现实的交易成本（印花税0.05%+佣金）。
- 非个人化建议：因子筛选是分析工具，不构成投资建议。个人情况各异。
© Geeksfino, 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
SKILL.md and 3 other files (references) in China-market/quant-factor-screener of Geeksfino/finskills.
- SKILL.md
- LICENSE.txt
- references/factor-methodology.md
- references/output-template.md
Open the folder on GitHubat commit 8722415
Compare with similar skills
Quant Factor Screener 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 |
|---|---|---|---|---|---|---|
| Quant Factor Screener this skillGeeksfino/finskills | 282 | — | ~589 | Automated safety check: Pass | Apache-2.0 | |
| Technical Analysttradermonty/claude-trading-skills | 3k | 4 repos | ~4.6k | Automated safety check: Pass | MIT | |
| Theme Detectortradermonty/claude-trading-skills | 3k | 2 repos | ~4.9k | Automated safety check: Pass | MIT | |
| Creating Financial ModelsChen-zexi/open-ptc-agent | 729 | 3 repos | ~1.3k | Automated safety check: Pass | MIT | |
| Stock APIzhangxiangliang/stock-api | 2k | — | ~507 | Automated safety check: Pass | MIT | |
| Itr Walakaranb192/itr-wala | 871 | — | ~3.6k | Automated safety check: Pass | MIT |
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Questions about Quant Factor Screener
What does Quant Factor Screener do?
使用正式因子模型进行系统化多因子A股筛选，识别具有有利因子暴露的个股。当用户询问因子投资、多因子筛选、价值/动量/质量因子分析、因子打分、因子择时、Smart Beta策略、量化选股或基于学术因子的系统化选股时使用此技能。. Quant Factor Screener is an agent skill from Geeksfino/finskills.
When should I use Quant Factor Screener?
Quant Factor Screener fits situations like: business, Finance & HR work in your project.
How do I install Quant Factor Screener in Claude Code?
Run `npx skills add Geeksfino/finskills --skill quant-factor-screener -a claude-code`. Or copy the skill folder (China-market/quant-factor-screener in Geeksfino/finskills) into .claude/skills/quant-factor-screener in your project. Claude Code loads it when a task matches its description.
How do I install Quant Factor Screener in Codex?
Run `npx skills add Geeksfino/finskills --skill quant-factor-screener -a codex`. Or copy the skill folder (China-market/quant-factor-screener in Geeksfino/finskills) into .agents/skills/quant-factor-screener in your project. Codex loads it when a task matches its description.
Can I use Quant Factor Screener 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 Geeksfino/finskills --skill quant-factor-screener -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/quant-factor-screener, .gemini/skills/quant-factor-screener, .github/skills/quant-factor-screener and .opencode/skills/quant-factor-screener in your project.
What does Quant Factor Screener need to run?
SKILL.md names no scripts, command-line tools or credentials: Quant Factor Screener is instructions for the agent only.
Does Quant Factor Screener 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 Quant Factor Screener 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 Quant Factor Screener use?
Quant Factor Screener is published under the Apache-2.0 licence (declared in SKILL.md). It allows redistribution, so the full SKILL.md is shown on this page.
How many tokens does Quant Factor Screener use?
About 589 tokens (SKILL.md is roughly 2.4k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full. Its references folder adds about 3.3k tokens, read only when the agent opens those files.
What are the alternatives to Quant Factor Screener?
Skills that share tags, products or a category with Quant Factor Screener: Technical Analyst (tradermonty/claude-trading-skills, 3k stars), Theme Detector (tradermonty/claude-trading-skills, 3k stars), Creating Financial Models (Chen-zexi/open-ptc-agent, 729 stars) and Stock API (zhangxiangliang/stock-api, 2k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
Who maintains Quant Factor Screener?
Geeksfino (a GitHub user) maintains it in Geeksfino/finskills, which has 282 GitHub stars. The repository holds 30 skills in this directory. The repository was last updated on March 5, 2026.
Source: Geeksfino/finskills on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.