Agent skill

Undervalued Stock Screener

by Geeksfino in Geeksfino/finskills

扫描A股市场,筛选基本面强劲但市值被低估的上市公司。当用户询问低估值股票、价值投资筛选、A股便宜股票、低PE或低PB公司、基本面强但被低估的公司、或要求运行估值筛选器时使用此技能。

Apache-2.0Auto-check passedBusiness, Finance & HR

Install Undervalued Stock Screener

skills CLI
$ npx skills add Geeksfino/finskills --skill undervalued-stock-screener -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install Geeksfino/finskills undervalued-stock-screener --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/Geeksfino/finskills.git skills-src && mkdir -p .claude/skills && cp -r skills-src/China-market/undervalued-stock-screener .claude/skills/undervalued-stock-screener && rm -rf skills-src

Use ~/.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/

Facts

Skill name
undervalued-stock-screener
GitHub stars
282
Token cost
~469 tokens
SKILL.md length
86 words
Files
4 (incl. references)
Skills in repo
30
Repo updated
First seen
Licence
Apache-2.0

At a glance

扫描A股市场,筛选基本面强劲但市值被低估的上市公司。当用户询问低估值股票、价值投资筛选、A股便宜股票、低PE或低PB公司、基本面强但被低估的公司、或要求运行估值筛选器时使用此技能。

  • Works in 4 steps: 筛选范围 — 全市场、特定申万一级行业、主板/创业板/科创板/北交所、或自定义股票池 → 市值范围 —… → 结果数量 — 默认:10家 → …
  • Tasks that involve Stock and market analysis
  • SKILL.md covers 工作流程, 筛选条件摘要, 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

Undervalued Stock Screener is an agent skill from Geeksfino/finskills. 扫描A股市场,筛选基本面强劲但市值被低估的上市公司。当用户询问低估值股票、价值投资筛选、A股便宜股票、低PE或低PB公司、基本面强但被低估的公司、或要求运行估值筛选器时使用此技能。

Its SKILL.md is about 470 tokens, which your agent loads only when the skill is triggered. The skill folder holds 4 other files, including reference files (for example `references/output-template.md` and `references/screening-methodology.md`).

It sits in Business, Finance & HR, covering Stock and market analysis. The repository describes itself as: Financial engineering and risk/compliance skills for agents. The licence is Apache-2.0.

When your agent uses it

  • Tasks that involve Stock and market analysis

Example prompts

  • “/undervalued-stock-screener”

Workflow steps

4 steps, taken from the first numbered list in SKILL.md.

  1. 筛选范围 — 全市场、特定申万一级行业、主板/创业板/科创板/北交所、或自定义股票池
  2. 市值范围 — 无限制(默认)、大盘(>500亿)、中盘(100–500亿)、小盘(<100亿)
  3. 结果数量 — 默认:10家
  4. 侧重点 — 综合评估(默认)、深度价值(低PB导向)、成长价值(PEG导向)、红利价值

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

Undervalued Stock Screener loads about 469 tokens when it runs, and up to ~3k if it reads all its reference files. Until then it costs about 29 tokens; SKILL.md has 86 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~29
When it runs · the whole SKILL.md, loaded when a task matches
~469
With references · SKILL.md plus every file in references/, read only if the agent opens them
~3k

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). 86 words, ~469 tokens.

Download SKILL.mdSave it as .claude/skills/undervalued-stock-screener/SKILL.md (or your agent's skills folder). This skill also uses 3 other files; get the full folder from GitHub.
name
undervalued-stock-screener
description
扫描A股市场,筛选基本面强劲但市值被低估的上市公司。当用户询问低估值股票、价值投资筛选、A股便宜股票、低PE或低PB公司、基本面强但被低估的公司、或要求运行估值筛选器时使用此技能。
license
Apache-2.0

低估值股票筛选器

扮演专业的权益研究分析师。扫描A股市场,筛选出基本面强劲但被市场低估的上市公司。

工作流程

第一步:确定参数

与用户确认:

  1. 筛选范围 — 全市场、特定申万一级行业、主板/创业板/科创板/北交所、或自定义股票池
  2. 市值范围 — 无限制(默认)、大盘(>500亿)、中盘(100–500亿)、小盘(<100亿)
  3. 结果数量 — 默认:10家
  4. 侧重点 — 综合评估(默认)、深度价值(低PB导向)、成长价值(PEG导向)、红利价值

默认参数:全市场、无市值限制、10家、综合评估。

第二步:应用筛选条件

对全部候选股票应用以下筛选条件。详细标准参见 references/screening-methodology.md。

筛选条件标准
PE估值滚动PE低于所属申万行业中位数
PB估值PB低于所属行业中位数(配合ROE筛选)
营收与利润增长近3–5年营收和归母净利润复合增长率为正
资产负债率低于行业中位数(金融行业除外)
自由现金流正值且近3年累计为正
ROIC/ROEROE高于行业平均水平

自动排除:ST/*ST公司、上市不满2年的公司、近12个月净利润为负的公司。

第三步:深度分析

对通过筛选的股票逐一分析。关注:

  1. 业务概述 — 主营业务、竞争优势(护城河)、行业地位
  2. 低估原因分析 — 为什么市场给出了低估值
  3. 核心风险 — 可能使低估合理化的因素
  4. 估值区间估计 — 基于多种方法的合理估值范围
第四步:编制报告

以结构化报告呈现,格式参见 references/output-template.md。

筛选条件摘要

条件过滤目的A股特殊考量
PE < 行业中位数排除过度溢价公司A股整体PE中枢高于成熟市场,使用行业相对法
PB < 行业中位数识别资产折价银行/地产PB长期破净需额外判断
营收/利润正增长排除衰退中的"价值陷阱"关注扣非净利润(排除一次性损益)
低资产负债率排除财务风险金融行业需使用行业专属指标
正自由现金流确认盈利质量高应收账款/存货的公司需警惕
高ROE/ROIC确认资本效率关注杜邦分析,区分高杠杆驱动vs真实盈利能力

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

  • A股估值中枢偏高:A股历史估值中枢高于美股等成熟市场(部分因审批制/注册制初期供给不足),因此使用行业相对估值法更为适用。
  • 扣非净利润:A股公司非经常性损益项目(政府补贴、投资收益、资产处置)较多,应使用扣非后净利润评估持续盈利能力。
  • 壳价值与注册制:注册制全面推行后壳价值逐渐下降,传统的"小盘股溢价"正在消退。
  • 行业差异极大:银行PB长期在0.5–0.8x不代表低估(可能反映资产质量担忧),科技行业高PE可能合理(高增长预期)。须在行业内部比较。
  • 国企vs民企:国企可能存在"国企折价"(治理效率担忧),但近年国企改革正在缩小这一差距。
  • 非投资建议:低估值筛选仅为信息整理工具,不构成投资建议。"便宜"不等于"值得买"。

© 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/undervalued-stock-screener of Geeksfino/finskills.

  • SKILL.md
  • LICENSE.txt
  • references/output-template.md
  • references/screening-methodology.md

Open the folder on GitHubat commit 8722415

Compare with similar skills

Undervalued Stock 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.

Undervalued Stock Screener compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
Undervalued Stock Screener this skillGeeksfino/finskills282—~469Automated safety check: PassApache-2.0
Stock APIzhangxiangliang/stock-api2k—~507Automated safety check: PassMIT
Tushare Datazillionare/zillionare3222 repos~2.3kAutomated safety check: PassNone
Tradingview MCPatilaahmettaner/tradingview-mcp5k—~1.3kAutomated safety check: PassMIT
Digital Oraclekomako-workshop/digital-oracle878—~5.9kAutomated safety check: PassMIT
Longbridge Researchhelsome/folio2713 repos~2.1kAutomated safety check: PassMIT

Similar skills

  • Stock API

    zhangxiangliang/stock-api

    Fetch real-time stock quotes, K-line (candlestick) history, and search symbols for China A-shares, Hong Kong, and US markets.

    2k GitHub stars~507 tokensUpdated yesterday
    Business, Finance & HRAuto-check passed
  • 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。

    322 GitHub starsUsed in 2 repos~2.3k tokens
    Business, Finance & HRAuto-check passed
  • Tradingview MCP

    atilaahmettaner/tradingview-mcp

    AI Trading Intelligence — live prices, 30+ technical indicators, backtesting (6 strategies), walk-forward overfitting detection, trade logs, equity curves, licensed news sentiment (Marketaux), and…

    5k GitHub stars~1.3k tokensUpdated yesterday
    Business, Finance & HRAuto-check passed
  • Digital Oracle

    komako-workshop/digital-oracle

    Answer prediction questions using market trading data, not opinions.

    878 GitHub stars~5.9k tokensUpdated 2 mo ago
    Business, Finance & HRAuto-check passed
  • Longbridge Research

    helsome/folio

    Institution ratings, consensus price targets, EPS/revenue forecasts, finance calendar, shareholder data, fund holders, insider trades (SEC Form 4), short interest, industry rankings, peer group…

    271 GitHub starsUsed in 3 repos~2.1k tokens
    Business, Finance & HRAuto-check passed
  • Longbridge Earnings

    helsome/folio

    Earnings analysis — pre- and post-earnings. An agent skill from helsome/folio.

    271 GitHub starsUsed in 1 repo~2.5k tokens
    Business, Finance & HRAuto-check passed

More from Geeksfino/finskills

All 30 skills in this repo
  • US Market Data Toolkit

    Geeksfino/finskills

    Free Python scripts that fetch US stock data, SEC filings, insider trades and macro indicators, and run financial score calculators and portfolio analytics.

    282 GitHub stars~1.2k tokensUpdated 7 mo ago
    Auto-check passed
  • Runs a forensic review of one company's financial statements covering DuPont profitability, earnings quality, financial health scores and fraud-risk signals.

    282 GitHub stars~1.8k tokensUpdated 7 mo ago
    Auto-check passed
  • Quantitative Factor Screener

    Geeksfino/finskills

    Screens a stock universe with a six-factor model, scores value, momentum, quality, low volatility, size and growth, ranks by composite score and notes which factors suit the macro regime.

    282 GitHub stars~1.3k tokensUpdated 7 mo ago
    Auto-check passed
  • Tech Hype vs Fundamentals

    Geeksfino/finskills

    Compares leading tech stocks to separate hype-driven valuations from fundamentally justified ones and to flag undervalued names the market overlooks.

    282 GitHub stars~1.3k tokensUpdated 7 mo ago
    Auto-check passed
  • Analyze Dividend Aristocrats (25+ years of consecutive dividend increases) for income reliability and total return.

    282 GitHub stars~1.2k tokensUpdated 7 mo ago
    Auto-check passed
  • ESG Stock Screener

    Geeksfino/finskills

    Screens US stocks through an ESG lens, applies optional exclusion lists, scores the environmental, social and governance pillars and judges whether ESG quality is improving.

    282 GitHub stars~1.4k tokensUpdated 7 mo ago
    Auto-check passed

Questions about Undervalued Stock Screener

What does Undervalued Stock Screener do?

扫描A股市场,筛选基本面强劲但市值被低估的上市公司。当用户询问低估值股票、价值投资筛选、A股便宜股票、低PE或低PB公司、基本面强但被低估的公司、或要求运行估值筛选器时使用此技能。. Undervalued Stock Screener is an agent skill from Geeksfino/finskills.

When should I use Undervalued Stock Screener?

Undervalued Stock Screener fits situations like: tasks that involve Stock and market analysis.

How do I install Undervalued Stock Screener in Claude Code?

Run `npx skills add Geeksfino/finskills --skill undervalued-stock-screener -a claude-code`. Or copy the skill folder (China-market/undervalued-stock-screener in Geeksfino/finskills) into .claude/skills/undervalued-stock-screener in your project. Claude Code loads it when a task matches its description.

How do I install Undervalued Stock Screener in Codex?

Run `npx skills add Geeksfino/finskills --skill undervalued-stock-screener -a codex`. Or copy the skill folder (China-market/undervalued-stock-screener in Geeksfino/finskills) into .agents/skills/undervalued-stock-screener in your project. Codex loads it when a task matches its description.

Can I use Undervalued Stock 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 undervalued-stock-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/undervalued-stock-screener, .gemini/skills/undervalued-stock-screener, .github/skills/undervalued-stock-screener and .opencode/skills/undervalued-stock-screener in your project.

What does Undervalued Stock Screener need to run?

SKILL.md names no scripts, command-line tools or credentials: Undervalued Stock Screener is instructions for the agent only.

Does Undervalued Stock 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 Undervalued Stock 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 Undervalued Stock Screener use?

Undervalued Stock 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 Undervalued Stock Screener use?

About 469 tokens (SKILL.md is roughly 1.9k 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 2.5k tokens, read only when the agent opens those files.

What are the alternatives to Undervalued Stock Screener?

Skills that share tags, products or a category with Undervalued Stock Screener: Stock API (zhangxiangliang/stock-api, 2k stars), Tushare Data (zillionare/zillionare, 322 stars), Tradingview MCP (atilaahmettaner/tradingview-mcp, 5k stars) and Digital Oracle (komako-workshop/digital-oracle, 878 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Undervalued Stock 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.