查询A股实时行情、历史数据、技术指标、事件、资金面、热门行业/概念、板块热力图与个股行业信息。Use when 用户提到股票代码、板块、热门概念、热门行业、概念涨跌、行业涨跌、热力图、市场快讯、技术分析、财务指标、指数成分、交易日历、宏观数据或个股所属行业。

MITAuto-check passed

Install A Share Data

skills CLI
$ npx skills add shouldnotappearcalm/a-share-skill --skill a-share-data -a claude-code

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

GitHub CLI
$ gh skill install shouldnotappearcalm/a-share-skill a-share-data --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/shouldnotappearcalm/a-share-skill.git skills-src && mkdir -p .claude/skills && cp -r skills-src/a-share-data .claude/skills/a-share-data && 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-data
GitHub stars
243
Used in
1 other repo
Token cost
~1.3k tokens
SKILL.md length
122 words
Files
14 (incl. scripts, references)
Skills in repo
7
Repo updated
First seen
Licence
MIT

At a glance

查询A股实时行情、历史数据、技术指标、事件、资金面、热门行业/概念、板块热力图与个股行业信息。Use when 用户提到股票代码、板块、热门概念、热门行业、概念涨跌、行业涨跌、热力图、市场快讯、技术分析、财务指标、指数成分、交易日历、宏观数据或个股所属行业。

  • Works in 5 steps: 先识别用户意图:实时、历史、技术、事件、A股赴港上市时间节点、热门行业/热门概念/… → 命中下列任一表述时,先读… → 选择对应脚本并优先加 --json。 → …
  • 用户提到股票代码、板块、热门概念、热门行业、概念涨跌、行业涨跌、热力图、市场快讯、技术分析、财务指标、指数成分、交易日历、宏观数据或个股所属行业
  • SKILL.md covers 目标, 环境与路径, 代码格式约定 and 脚本路由规则, plus 7 more sections
  • Runs Python scripts from its folder; calls python3 and pip

What it does

A Share Data is an agent skill from shouldnotappearcalm/a-share-skill. 查询A股实时行情、历史数据、技术指标、事件、资金面、热门行业/概念、板块热力图与个股行业信息。Use when 用户提到股票代码、板块、热门概念、热门行业、概念涨跌、行业涨跌、热力图、市场快讯、技术分析、财务指标、指数成分、交易日历、宏观数据或个股所属行业。

Its SKILL.md is about 1.3k tokens, which your agent loads only when the skill is triggered. The skill folder holds 15 other files, including scripts and reference files (for example `references/api-reference.md`, `references/danginvest-api-reference.md` and `scripts/Ashare.py`).

The repository describes itself as: A股数据分析、量化选股与模拟交易 Skill 集合,支持实时行情、历史K线、技术指标、自定义交易策略与模拟买入、卖出交易账户. The licence is MIT.

When your agent uses it

  • 用户提到股票代码、板块、热门概念、热门行业、概念涨跌、行业涨跌、热力图、市场快讯、技术分析、财务指标、指数成分、交易日历、宏观数据或个股所属行业

Example prompts

  • “/a-share-data”

Requirements

  • Python 3

Workflow steps

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

  1. 先识别用户意图:实时、历史、技术、事件、A股赴港上市时间节点、热门行业/热门概念/行业或概念涨跌幅、板块热力图、7×24 快讯,或「个股所属行业」。
  2. 命中下列任一表述时,先读 references/danginvest-api-reference.md,再用 fetch_danginvest.py(勿用 fetch_realtime.py --boards-*)
  3. 选择对应脚本并优先加 --json。
  4. 参数不足时补齐默认值后执行,不先空谈。
  5. 返回时给出关键字段结论,并附可复现命令。

What it can do on your machine

Read from SKILL.md and the folder at commit 6eb8d32. 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 11 files in scripts/ (Python), which the agent can run.

    Shell commands in SKILL.md call:

    • python3
    • 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

A Share Data loads about 1.3k tokens when it runs, and up to ~5.2k if it reads all its reference files. Until then it costs about 36 tokens; SKILL.md has 122 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~36
When it runs · the whole SKILL.md, loaded when a task matches
~1.3k
With references · SKILL.md plus every file in references/, read only if the agent opens them
~5.2k

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 shouldnotappearcalm/a-share-skill at commit 6eb8d32, republished under its MIT licence (© shouldnotappearcalm). 122 words, ~1,250 tokens.

Download SKILL.mdSave it as .claude/skills/a-share-data/SKILL.md (or your agent's skills folder). This skill also uses 13 other files; get the full folder from GitHub.
name
a-share-data
description
查询A股实时行情、历史数据、技术指标、事件、资金面、热门行业/概念、板块热力图与个股行业信息。Use when 用户提到股票代码、板块、热门概念、热门行业、概念涨跌、行业涨跌、热力图、市场快讯、技术分析、财务指标、指数成分、交易日历、宏观数据或个股所属行业。

A股数据综合分析

目标

使用本技能时,优先调用本目录下脚本获取结构化数据,不依赖网页抓取。

支持能力:

  • 实时行情与市场维度
  • 历史数据与财务维度
  • 技术指标
  • 个股事件
  • A+H 双重上市公司列表(支持按 H 股上市日期筛选)
  • A股赴港上市关键事件时间节点(递表/聆讯/备案/招股/定价/配售/上市)
  • 热门行业、热门概念、行业/概念涨跌幅、板块热力图、板块成分股、7×24 市场快讯(fetch_danginvest.py;先读 references/danginvest-api-reference.md)
  • 个股行业信息(fetch_sector_info.py,数据源东方财富;个股概念不稳定,见下)

环境与路径

bash
pip install akshare MyTT pandas numpy requests
bash
SKILL_DIR="<本skill绝对路径>"
python3 "$SKILL_DIR/scripts/fetch_realtime.py" [参数]
python3 "$SKILL_DIR/scripts/fetch_history.py" [参数]
python3 "$SKILL_DIR/scripts/fetch_technical.py" [参数]
python3 "$SKILL_DIR/scripts/fetch_stock_events.py" [参数]
python3 "$SKILL_DIR/scripts/fetch_ah_stocks.py" [参数]
python3 "$SKILL_DIR/scripts/fetch_ah_ipo_timeline.py" [参数]
python3 "$SKILL_DIR/scripts/fetch_danginvest.py" [参数]
python3 "$SKILL_DIR/scripts/fetch_sector_info.py" [参数]

说明:fetch_sector_info.py 虽可能带概念参数,但东方财富个股概念接口不稳定、常为空,使用时固定加 --no-concepts,只查行业与证券简称。市场级概念板块(涨跌幅、热力图、成分股)走 fetch_danginvest.py,不要与前者混用。

代码格式约定

优先使用以下股票代码格式:

  • 纯数字:600519
  • 市场前缀:sh600519 / sz000001
  • JoinQuant:600519.XSHG

脚本路由规则

按问题类型选脚本:

  • fetch_danginvest.py:热门概念、热门行业、行业涨跌幅、概念涨跌幅、板块热力图、板块成分股、7×24 市场快讯;参数与查询惯例见 references/danginvest-api-reference.md
  • fetch_realtime.py:实时价格、分钟线、指数、北向、龙虎榜、涨跌停、资金流、全市场行情、成交明细(--boards-* 仅兼容旧用法)
  • fetch_history.py:历史K线、财务、业绩、分红、行业、指数成分、交易日历、宏观
  • fetch_technical.py:MA/MACD/KDJ/RSI/BOLL等技术指标
  • fetch_stock_events.py:业绩、增减持/回购、监管、重大合同、舆情方向
  • fetch_ah_stocks.py:A+H 双重上市公司清单、H 股上市日期区间筛选
  • fetch_ah_ipo_timeline.py:A股赴港上市关键事件节点(递表/聆讯/备案/招股/定价/配售/上市);支持 --code / --name 点查
  • fetch_sector_info.py:单只或多只股票的行业与名称(东方财富);批量时并行,默认 --workers;仅文档化行业路径,不加概念

执行流程

  1. 先识别用户意图:实时、历史、技术、事件、A股赴港上市时间节点、热门行业/热门概念/行业或概念涨跌幅、板块热力图、7×24 快讯,或「个股所属行业」。
  2. 命中下列任一表述时,先读 references/danginvest-api-reference.md,再用 fetch_danginvest.py(勿用 fetch_realtime.py --boards-*):
    • 今天/今日热门概念、什么概念涨得多、概念领涨/领跌
    • 今天/今日热门行业、什么行业涨得多、行业领涨/领跌(含大类行业、细分行业)
    • 行业涨跌幅、概念涨跌幅、板块热力图、某板块成分股
    • 7×24 市场快讯
  3. 选择对应脚本并优先加 --json。
  4. 参数不足时补齐默认值后执行,不先空谈。
  5. 返回时给出关键字段结论,并附可复现命令。

降级与容错规则

  • 历史能力统一走 fetch_history.py(已内置多源逻辑,K线链路为腾讯优先、新浪降级、东财兜底)。
  • 遇到上游限流或临时失败:
    • 同类接口先重试 1-2 次。
    • 可降级就降级,不能降级则明确标注为“上游数据源不可用”。
  • --all-stocks 已支持新浪/腾讯/雪球多源;若单一源失败,继续返回其他源合并结果。

批量数据并行与超时规范(强制)

当任务是“批量拉取”时(实时个股列表 / 多只历史K线),默认并行,不逐只串行。

  • 推荐并发:max_workers=8~12(默认 10)
  • 每只股票独立异常捕获,失败不阻断整批
  • 结果输出必须包含:样本数、成功率、总耗时、失败代码清单

超时上限(硬限制):

  • 批量实时个股列表:整批任务最多等待 30s
  • 批量历史K线(多只):整批任务最多等待 30s
  • 全市场并发任务:整批任务最多等待 60s

超时/失败处理(强制):

  • 到达超时即停止等待并返回当前结果
  • 失败就标记失败,不做长时间阻塞重试
  • 禁止无上限重试或“卡住一直等”

输出规范

  • 默认返回结构化要点,不堆长表。
  • 需要原始数据时再返回完整 JSON。
  • 明确数据源与时间点(如交易日、更新时间、盘中/休市状态)。

常用命令最小集

bash
# 实时(单只)
python3 fetch_realtime.py --quote 600519 --json
# 实时(多只,逗号分隔,最多10只)
python3 fetch_realtime.py --multi-quote 002491,002364,600519 --json
python3 fetch_realtime.py --index --json
python3 fetch_realtime.py --all-quote --sort change_pct_desc --top 50 --json
python3 fetch_realtime.py --tick 600519 --json

# 历史
python3 fetch_history.py --kline 600519 --start 2025-01-01 --end 2025-03-31 --freq d --json
python3 fetch_history.py --kline-batch 600519,000001,300750 --start 2025-10-01 --end 2026-03-31 --count 120 --workers 8 --retries 2 --json
python3 fetch_history.py --financials 600519 --start 2023-01-01 --end 2025-01-01 --json
python3 fetch_history.py --industry 300271 --with-boards --json

# 技术
python3 fetch_technical.py 600519 --freq 1d --count 120 --indicators MA,MACD,KDJ,RSI,BOLL --json

# 事件
python3 fetch_stock_events.py --code 300476 --name 胜宏科技 --dates 20250331,20241231 --limit 20 --json

# A+H 列表
python3 fetch_ah_stocks.py --json
python3 fetch_ah_stocks.py --since 2020-01-01 --until 2024-12-31 --json

# A股赴港上市关键节点
python3 fetch_ah_ipo_timeline.py --name 顺丰 --json
python3 fetch_ah_ipo_timeline.py --code 002352 --json
python3 fetch_ah_ipo_timeline.py --since 2020 --workers 4 --json

# 热门行业/热门概念/涨跌幅/快讯 → fetch_danginvest.py,见 references/danginvest-api-reference.md

# 个股行业(不加概念,见上文说明)
python3 fetch_sector_info.py --no-concepts --json 600519
python3 fetch_sector_info.py --workers 8 --no-concepts --timeout 15 --json 600519 000001 300750 600036 601318 002594 688981 300059

不要做的事

  • 不把本技能当成爬虫任务优先方案。
  • 不在无必要时输出超长原始表格。
  • 不使用已移除的旧流程文案。
  • 热门概念、热门行业、行业/概念涨跌幅、板块热力图、板块成分、市场快讯:用 fetch_danginvest.py,先读 references/danginvest-api-reference.md;勿用 fetch_realtime.py --boards-*。
  • 不承诺 fetch_sector_info.py 的个股概念字段;市场级「热门概念/概念涨跌」走 fetch_danginvest.py,不是 sector_info。

参考

  • 实时/历史/技术等脚本参数:references/api-reference.md
  • 热门行业、热门概念、行业/概念涨跌幅、热力图、成分股、快讯(触发词、默认查哪些维度、命令示例):references/danginvest-api-reference.md
  • GitHub 项目地址:https://github.com/shouldnotappearcalm/a-share-skill

© shouldnotappearcalm, 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 13 other files (scripts, references) in a-share-data of shouldnotappearcalm/a-share-skill.

  • SKILL.md
  • references/api-reference.md
  • references/danginvest-api-reference.md
  • scripts/Ashare.py
  • scripts/fetch_ah_ipo_timeline.py
  • scripts/fetch_ah_stocks.py
  • scripts/fetch_danginvest.py
  • scripts/fetch_history.py
  • scripts/fetch_history_fallback.py
  • scripts/fetch_realtime.py
  • scripts/fetch_sector_info.py
  • scripts/fetch_stock_events.py
  • scripts/fetch_technical.py
  • scripts/test_fetch_realtime_intraday.py

Open the folder on GitHubat commit 6eb8d32

Used in 1 other repository

We found 1 copy of this SKILL.md (exact, near-identical or edited) in other folders, from 1 other GitHub owner. This page covers the copy in shouldnotappearcalm/a-share-skill, which our catalogue first saw on October 7, 2026.

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-templates32k10 repos~729Automated safety check: PassMIT
Tabler Shared Lib Helperstabler/tabler42k—~1.2kAutomated safety check: PassMIT

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  • Macd Trend Resonance Stock Picker

    shouldnotappearcalm/a-share-skill

    基于“均线定方向,MACD定节奏”的A股选股与交易计划技能。Use when 用户要求把均线与MACD结合做选股、筛票、盘前候选池、趋势跟随、回踩再上、金叉确认、顶背离减仓、或希望把技术判断沉淀成可执行规则与风控模板。

    243 GitHub stars~668 tokensUpdated 10 days ago
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Questions about A Share Data

What does A Share Data do?

查询A股实时行情、历史数据、技术指标、事件、资金面、热门行业/概念、板块热力图与个股行业信息。Use when 用户提到股票代码、板块、热门概念、热门行业、概念涨跌、行业涨跌、热力图、市场快讯、技术分析、财务指标、指数成分、交易日历、宏观数据或个股所属行业。. A Share Data is an agent skill from shouldnotappearcalm/a-share-skill.

When should I use A Share Data?

A Share Data fits situations like: 用户提到股票代码、板块、热门概念、热门行业、概念涨跌、行业涨跌、热力图、市场快讯、技术分析、财务指标、指数成分、交易日历、宏观数据或个股所属行业.

How do I install A Share Data in Claude Code?

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

How do I install A Share Data in Codex?

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

Can I use A Share Data 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 shouldnotappearcalm/a-share-skill --skill a-share-data -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-data, .gemini/skills/a-share-data, .github/skills/a-share-data and .opencode/skills/a-share-data in your project.

What does A Share Data need to run?

Going by SKILL.md and its folder, A Share Data needs Python for the scripts in its folder and the command-line tools its instructions call (python3 and pip). Our summary lists: Python 3.

Does A Share Data 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 A Share Data 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 Data use?

A Share Data 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 Data use?

About 1.3k tokens (SKILL.md is roughly 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 3.9k tokens, read only when the agent opens those files.

What are the alternatives to A Share Data?

Skills that share tags, products or a category with A Share Data: Share (ClickHouse/ClickHouse, 50k stars), Sharing (BuilderIO/agent-native, 7.1k stars), Deslop Shared Libs (garrytan/gstack, 136k stars) and Skill Share (davila7/claude-code-templates, 32k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains A Share Data?

shouldnotappearcalm (a GitHub user) maintains it in shouldnotappearcalm/a-share-skill, which has 243 GitHub stars. The repository holds 7 skills in this directory. The repository was last updated on September 28, 2026.

Source: shouldnotappearcalm/a-share-skill on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.