Agent skill

A Share Analyst

by staruhub in staruhub/ClaudeSkills

A股分析研究助手,提供行情数据获取与技术面/基本面分析框架(仅供研究参考,不构成投资建议)。适用于:(1) 获取A股行情和历史数据,(2) 技术面分析(K线形态、MACD、KDJ、RSI、布林带等),(3) 基本面分析(财务指标、估值分析),(4) 板块热点追踪,(5) 选股策略筛选与量化因子分析,(6)…

MITAuto-check passed

Install A Share Analyst

skills CLI
$ npx skills add staruhub/ClaudeSkills --skill a-share-analyst -a claude-code

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

GitHub CLI
$ gh skill install staruhub/ClaudeSkills a-share-analyst --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/staruhub/ClaudeSkills.git skills-src && mkdir -p .claude/skills && cp -r skills-src/lab/Geek-skills-a-share-analyst .claude/skills/a-share-analyst && 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
a-share-analyst
GitHub stars
728
Token cost
~871 tokens
SKILL.md length
133 words
Files
10 (incl. scripts, references)
Skills in repo
20
Repo updated
First seen
Licence
MIT

At a glance

A股分析研究助手,提供行情数据获取与技术面/基本面分析框架(仅供研究参考,不构成投资建议)。适用于:(1) 获取A股行情和历史数据,(2) 技术面分析(K线形态、MACD、KDJ、RSI、布林带等),(3) 基本面分析(财务指标、估值分析),(4) 板块热点追踪,(5) 选股策略筛选与量化因子分析,(6)…

  • Works in 4 steps: 每日盘前分析 → 技术面分析 → 基本面分析 → …
  • SKILL.md covers 数据获取, 分析工作流程, 输出格式 and 关键脚本, plus 4 more sections
  • Runs Python scripts from its folder

What it does

A Share Analyst is an agent skill from staruhub/ClaudeSkills. A股分析研究助手,提供行情数据获取与技术面/基本面分析框架(仅供研究参考,不构成投资建议)。适用于:(1) 获取A股行情和历史数据,(2) 技术面分析(K线形态、MACD、KDJ、RSI、布林带等),(3) 基本面分析(财务指标、估值分析),(4) 板块热点追踪,(5) 选股策略筛选与量化因子分析,(6) 生成股市分析报告。当用户询问"帮我分析股票"、"今日选股"、"A股行情分析"、"技术分析"、"量化选股"时触发。不用于:预测明日涨跌或给出确定性买卖指令、代客决策、港股美股(数据源不同)、加密货币。

Its SKILL.md is about 870 tokens, which your agent loads only when the skill is triggered. The skill folder holds 12 other files, including scripts and reference files (for example `evals/routing-evals.json`, `references/candlestick_patterns.md` and `references/factor_library.md`).

The repository describes itself as: 13 curated Agent Skills for research, product decisions, decks, publishing, audits, and more — portable across skills-compatible agents. The licence is MIT.

Example prompts

  • “帮我分析股票”
  • “A股行情分析”
  • “/a-share-analyst”

Requirements

  • Python 3

Workflow steps

4 steps, taken from the step headings in SKILL.md.

  1. 每日盘前分析
  2. 技术面分析
  3. 基本面分析
  4. 智能选股策略

What it can do on your machine

Read from SKILL.md and the folder at commit 66e02d2. 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

    Ships 4 files in scripts/ (Python), which the agent can run.

    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

A Share Analyst loads about 871 tokens when it runs, and up to ~5.6k if it reads all its reference files. Until then it costs about 67 tokens; SKILL.md has 133 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~67
When it runs · the whole SKILL.md, loaded when a task matches
~871
With references · SKILL.md plus every file in references/, read only if the agent opens them
~5.6k

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); the scripts in this folder are not scanned.

SKILL.md

The full file from staruhub/ClaudeSkills at commit 66e02d2, republished under its MIT licence (© staruhub). 133 words, ~871 tokens.

Download SKILL.mdSave it as .claude/skills/a-share-analyst/SKILL.md (or your agent's skills folder). This skill also uses 9 other files; get the full folder from GitHub.
name
a-share-analyst
description
A股分析研究助手,提供行情数据获取与技术面/基本面分析框架(仅供研究参考,不构成投资建议)。适用于:(1) 获取A股行情和历史数据,(2) 技术面分析(K线形态、MACD、KDJ、RSI、布林带等),(3) 基本面分析(财务指标、估值分析),(4) 板块热点追踪,(5) 选股策略筛选与量化因子分析,(6) 生成股市分析报告。当用户询问"帮我分析股票"、"今日选股"、"A股行情分析"、"技术分析"、"量化选股"时触发。不用于:预测明日涨跌或给出确定性买卖指令、代客决策、港股美股(数据源不同)、加密货币。
version
1.1.0

A股分析师 Skill

专业的A股市场分析工具,整合多数据源,提供技术面、基本面综合分析和智能选股策略。

数据获取

使用AKShare作为主要数据源(免费、开源、无需token):

python
pip install akshare --break-system-packages
核心数据获取示例
python
import akshare as ak

# 实时行情
df = ak.stock_zh_a_spot_em()  # 全部A股实时行情

# 历史K线
df = ak.stock_zh_a_hist(symbol="000001", period="daily", adjust="qfq")

# 板块行情
df = ak.stock_board_concept_name_em()  # 概念板块
df = ak.stock_board_industry_name_em()  # 行业板块

# 龙虎榜(日期用实际查询区间,格式 YYYYMMDD)
df = ak.stock_lhb_detail_em(start_date="<起始日>", end_date="<结束日>")

# 资金流向
df = ak.stock_individual_fund_flow(stock="000001", market="sz")

分析工作流程

1. 每日盘前分析

执行顺序:

  1. 获取大盘指数(上证、深证、创业板)
  2. 分析板块热点轮动
  3. 筛选涨停股及连板股
  4. 检测北向资金流向
  5. 生成今日关注清单
2. 技术面分析

对单只股票执行:

  1. 获取历史K线数据(至少60日)
  2. 计算技术指标(见 references/technical_indicators.md)
  3. 识别K线形态(见 references/candlestick_patterns.md)
  4. 判断趋势和支撑/阻力位
  5. 生成技术面评分
3. 基本面分析

执行顺序:

  1. 获取财务数据(营收、净利润、ROE等)
  2. 计算估值指标(PE、PB、PS)
  3. 分析行业地位和竞争优势
  4. 评估成长性和安全边际
  5. 生成基本面评分
4. 智能选股策略

策略类型选择:

  • 多因子综合策略 → 执行 scripts/strategy_multi_factor.py(已实现,内置 ST/停牌过滤)
  • 趋势突破 / 价值低估 / 动量因子等单因子策略 → 目前无独立脚本,在 multi_factor 基础上调整因子权重,或按需自行实现

输出格式

个股分析报告模板
markdown
# [股票名称]([股票代码]) 分析报告

## 基本信息
- 当前价格:¥XX.XX(涨跌幅 +X.XX%)
- 市值:XXX亿  |  PE(TTM):XX.X  |  PB:X.XX

## 技术面分析
- 趋势判断:[上升/震荡/下降]
- 支撑位:¥XX.XX  |  阻力位:¥XX.XX
- 技术指标:MACD [金叉/死叉]  |  KDJ [超买/超卖/中性]  |  RSI [XX]

## 基本面分析
- 营收增速:XX%  |  净利润增速:XX%
- ROE:XX%  |  毛利率:XX%

## 综合评分
- 技术面:⭐⭐⭐⭐☆ (4/5)
- 基本面:⭐⭐⭐☆☆ (3/5)

## 操作建议
[具体建议及风险提示]
每日选股清单模板
markdown
# 每日选股清单 [日期]

## 市场概览
- 上证指数:XXXX.XX(+X.XX%)
- 深证成指:XXXXX.XX(+X.XX%)
- 创业板指:XXXX.XX(+X.XX%)

## 热点板块 TOP5
1. [板块名称] +X.XX%
2. ...

## 精选个股

### 趋势突破型
| 代码 | 名称 | 现价 | 涨幅 | 突破形态 | 评分 |
|------|------|------|------|----------|------|
| ... | ... | ... | ... | ... | ... |

### 价值低估型
| 代码 | 名称 | 现价 | PE | PB | 评分 |
|------|------|------|-----|-----|------|
| ... | ... | ... | ... | ... | ... |

## 风险提示
投资有风险,以上分析仅供参考,不构成投资建议。

关键脚本

  • scripts/fetch_market_data.py - 市场数据获取
  • scripts/technical_analysis.py - 技术指标计算(输出中性强弱描述,非买卖评级)
  • scripts/strategy_multi_factor.py - 多因子选股(含 ST/停牌过滤)
  • scripts/generate_report.py - 报告生成(需在 scripts/ 目录内运行,依赖 technical_analysis)

参考文档

  • references/technical_indicators.md - 技术指标计算公式
  • references/candlestick_patterns.md - K线形态识别
  • references/fundamental_metrics.md - 基本面指标说明
  • references/factor_library.md - 量化因子库

验收标准(每份分析交付前自查)

  • 报告末尾含"仅供参考,不构成投资建议"声明(模板已内置,不许删)
  • 数据来自本次运行的 akshare 调用,标注数据时间戳与延迟(可能有15分钟延迟)
  • 技术面/基本面结论与展示的指标数据一一对应,没有无数据支撑的判断
  • 给出的是"分析+风险"而非"买卖指令":无"满仓""抄底""必涨"类表述
  • 新策略未经历史回测时明确标注"未回测"

不做什么

  • 不预测明日涨跌,不给确定性买卖点位
  • 不代替用户决策,不推荐仓位以外的杠杆操作(模板建议:单只 ≤20%)
  • 不分析港股/美股/加密货币(数据源与规则不同)
  • 用户情绪化追问"到底买不买"时,重申边界并给风险清单,不给指令

已知陷阱

陷阱具体表现应对
akshare 接口变动库更新后函数名/字段变了,脚本报错报错时先查 akshare 当前版本文档,不硬猜字段
延迟数据当实时用 15 分钟前的价格谈"当前"报告标注数据获取时间
指标堆砌无结论MACD/KDJ/RSI 全列一遍但互相矛盾不解释指标冲突时明确说"信号分歧"及其含义
幸存者偏差选股用当前成分股回测历史策略回测结论标注该局限
节假日/停牌数据停牌股票数据缺失导致计算错误计算前过滤停牌与 ST 异常状态

evals/routing-evals.json — 触发边界回归用例,改 description 后用仓库根 scripts/run_routing_evals.py 校验。

© staruhub, MIT. 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 9 other files (scripts, references) in lab/Geek-skills-a-share-analyst of staruhub/ClaudeSkills.

  • SKILL.md
  • evals/routing-evals.json
  • references/candlestick_patterns.md
  • references/factor_library.md
  • references/fundamental_metrics.md
  • references/technical_indicators.md
  • scripts/fetch_market_data.py
  • scripts/generate_report.py
  • scripts/strategy_multi_factor.py
  • scripts/technical_analysis.py

Open the folder on GitHubat commit 66e02d2

Compare with similar skills

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SharingBuilderIO/agent-native7.1k—~3.4kAutomated safety check: PassNone
Deslop Shared Libsgarrytan/gstack136k—~3.3kAutomated safety check: NotesMIT
Skill Sharedavila7/claude-code-templates33k10 repos~729Automated safety check: PassMIT

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Questions about A Share Analyst

What does A Share Analyst do?

A股分析研究助手,提供行情数据获取与技术面/基本面分析框架(仅供研究参考,不构成投资建议)。适用于:(1) 获取A股行情和历史数据,(2) 技术面分析(K线形态、MACD、KDJ、RSI、布林带等),(3) 基本面分析(财务指标、估值分析),(4) 板块热点追踪,(5) 选股策略筛选与量化因子分析,(6)…. A Share Analyst is an agent skill from staruhub/ClaudeSkills.

How do I install A Share Analyst in Claude Code?

Run `npx skills add staruhub/ClaudeSkills --skill a-share-analyst -a claude-code`. Or copy the skill folder (lab/Geek-skills-a-share-analyst in staruhub/ClaudeSkills) into .claude/skills/a-share-analyst in your project. Claude Code loads it when a task matches its description.

How do I install A Share Analyst in Codex?

Run `npx skills add staruhub/ClaudeSkills --skill a-share-analyst -a codex`. Or copy the skill folder (lab/Geek-skills-a-share-analyst in staruhub/ClaudeSkills) into .agents/skills/a-share-analyst in your project. Codex loads it when a task matches its description.

Can I use A Share Analyst 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 staruhub/ClaudeSkills --skill a-share-analyst -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/a-share-analyst, .gemini/skills/a-share-analyst, .github/skills/a-share-analyst and .opencode/skills/a-share-analyst in your project.

What does A Share Analyst need to run?

Going by SKILL.md and its folder, A Share Analyst needs Python for the scripts in its folder. Our summary lists: Python 3.

Does A Share Analyst 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 A Share Analyst 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. The check reads SKILL.md only: the scripts in the folder are not scanned, so read them before running anything.

What licence does A Share Analyst use?

A Share Analyst 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 A Share Analyst use?

About 871 tokens (SKILL.md is roughly 3.5k 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 4.8k tokens, read only when the agent opens those files.

What are the alternatives to A Share Analyst?

Skills that share tags, products or a category with A Share Analyst: Share (ClickHouse/ClickHouse, 50k stars), Developing Share Pages (TriliumNext/Trilium, 38k stars), Sharing (BuilderIO/agent-native, 7.1k stars) and Deslop Shared Libs (garrytan/gstack, 136k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains A Share Analyst?

staruhub (a GitHub user) maintains it in staruhub/ClaudeSkills, which has 728 GitHub stars. The repository holds 20 skills in this directory. The repository was last updated on August 13, 2026.

Source: staruhub/ClaudeSkills on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.