Agent skill

A Share Board Analysis

by aifinlab in aifinlab/FinClaw

A股涨跌停板分析/连板追踪/涨停板统计。当用户说"涨停"、"跌停"、"涨停板"、"连板"、"打板"、"炸板"、"涨停分析"、"今天多少家涨停"、"连板股"、"首板"、"二板"、"三板"、"涨停原因"、"XX涨停了"、"涨停板分析"时触发。MUST USE when user asks about limit-up/limit-down board analysis, consecutive…

Apache-2.0Auto-check passedData & Analytics

Install A Share Board Analysis

skills CLI
$ npx skills add aifinlab/FinClaw --skill a-share-board-analysis -a claude-code

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

GitHub CLI
$ gh skill install aifinlab/FinClaw a-share-board-analysis --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/aifinlab/FinClaw.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/a-share-board-analysis .claude/skills/a-share-board-analysis && 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-board-analysis
GitHub stars
255
Token cost
~665 tokens
SKILL.md length
94 words
Files
2 (incl. references)
Skills in repo
74
Repo updated
First seen
Licence
Apache-2.0

At a glance

A股涨跌停板分析/连板追踪/涨停板统计。当用户说"涨停"、"跌停"、"涨停板"、"连板"、"打板"、"炸板"、"涨停分析"、"今天多少家涨停"、"连板股"、"首板"、"二板"、"三板"、"涨停原因"、"XX涨停了"、"涨停板分析"时触发。MUST USE when user asks about limit-up/limit-down board analysis, consecutive…

  • Works in 5 steps: 确定分析范围 → 数据获取 → 涨跌停分析 → …
  • User asks about limit-up/limit-down board analysis
  • SKILL.md covers 数据源, Workflow, 关键规则 and 使用示例
  • Calls python

What it does

A Share Board Analysis is an agent skill from aifinlab/FinClaw. A股涨跌停板分析/连板追踪/涨停板统计。当用户说"涨停"、"跌停"、"涨停板"、"连板"、"打板"、"炸板"、"涨停分析"、"今天多少家涨停"、"连板股"、"首板"、"二板"、"三板"、"涨停原因"、"XX涨停了"、"涨停板分析"时触发。MUST USE when user asks about limit-up/limit-down board analysis, consecutive board tracking, or daily limit statistics for A-shares. 分析当日涨跌停数量、连板梯队、涨停原因归类、炸板率,追踪连板龙头股走势。支持研报风格(formal)和快速解读风格(brief)。

Its SKILL.md is about 670 tokens, which your agent loads only when the skill is triggered. The skill folder holds 2 other files, including reference files (for example `references/board-analysis-guide.md`).

It sits in Data & Analytics, covering Statistics. The licence is Apache-2.0.

When your agent uses it

  • User asks about limit-up/limit-down board analysis
  • Consecutive board tracking
  • Daily limit statistics for A-shares

Example prompts

  • “今天多少家涨停”
  • “/a-share-board-analysis”

Requirements

  • Python 3

Workflow steps

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

  1. 确定分析范围
  2. 数据获取
  3. 涨跌停分析
  4. 连板龙头追踪
  5. 输出

What it can do on your machine

Read from SKILL.md and the folder at commit 9e62862. 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

    Shell commands in SKILL.md call:

    • 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

A Share Board Analysis loads about 665 tokens when it runs, and up to ~2.2k if it reads all its reference files. Until then it costs about 85 tokens; SKILL.md has 94 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~85
When it runs · the whole SKILL.md, loaded when a task matches
~665
With references · SKILL.md plus every file in references/, read only if the agent opens them
~2.2k

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); files beside SKILL.md are not scanned.

SKILL.md

The full file from aifinlab/FinClaw at commit 9e62862, republished under its Apache-2.0 licence (© aifinlab). 94 words, ~665 tokens.

Download SKILL.mdSave it as .claude/skills/a-share-board-analysis/SKILL.md (or your agent's skills folder). This skill also uses 1 other file; get the full folder from GitHub.
name
a-share-board-analysis
description
A股涨跌停板分析/连板追踪/涨停板统计。当用户说"涨停"、"跌停"、"涨停板"、"连板"、"打板"、"炸板"、"涨停分析"、"今天多少家涨停"、"连板股"、"首板"、"二板"、"三板"、"涨停原因"、"XX涨停了"、"涨停板分析"时触发。MUST USE when user asks about limit-up/limit-down board analysis, consecutive board tracking, or daily limit statistics for A-shares. 分析当日涨跌停数量、连板梯队、涨停原因归类、炸板率,追踪连板龙头股走势。支持研报风格(formal)和快速解读风格(brief)。

A股涨跌停板分析助手

数据源

bash
SCRIPTS="$SKILLS_ROOT/cn-stock-data/scripts"

# 涨停池(当日涨停股票列表,含连板天数、涨停原因等)
python -c "import akshare as ak; df=ak.stock_zt_pool_em(date='YYYYMMDD'); print(df.to_json(orient='records', force_ascii=False))"

# 跌停池(当日跌停股票列表)
python -c "import akshare as ak; df=ak.stock_zt_pool_dtgc_em(date='YYYYMMDD'); print(df.to_json(orient='records', force_ascii=False))"

# 炸板池(当日曾触及涨停但未封住的股票)
python -c "import akshare as ak; df=ak.stock_zt_pool_zbgc_em(date='YYYYMMDD'); print(df.to_json(orient='records', force_ascii=False))"

# 强势股池(当日涨幅较大的非涨停股)
python -c "import akshare as ak; df=ak.stock_zt_pool_strong_em(date='YYYYMMDD'); print(df.to_json(orient='records', force_ascii=False))"

# 个股行情(通过 cn-stock-data)
python "$SCRIPTS/cn_stock_data.py" quote --code [CODE]

# K线(看连板股历史走势)
python "$SCRIPTS/cn_stock_data.py" kline --code [CODE] --freq daily --start [日期]

补充:通过 web 搜索确认涨停原因/题材概念。

Workflow

Step 1: 确定分析范围

根据用户意图分类:

  • 当日涨跌停全景:今日涨停/跌停家数、连板梯队、炸板率
  • 特定连板梯队:几板股有哪些、最高连板股是谁
  • 个股涨停原因:某只股票为何涨停/跌停
Step 2: 数据获取

获取涨停池 + 跌停池 + 炸板池数据。如分析个股,额外获取该股 K 线和行情报价。日期参数用 YYYYMMDD 格式,默认为最近交易日。

注意:非交易日或盘中时段数据可能不完整,需注明数据状态。

Step 3: 涨跌停分析
  • 涨跌停对比:涨停家数 vs 跌停家数,判断市场情绪(涨多跌少=偏强)
  • 连板梯队:按连板天数分层统计(首板/二板/三板/四板及以上)
  • 板块归类:涨停股按所属概念/行业分组,找出最强主线
  • 炸板率:炸板数 /(涨停数 + 炸板数),炸板率高=封板意愿弱、市场分歧大
  • 涨停时间:早盘集合竞价/开盘涨停 vs 尾盘涨停,时间越早封板越强

详见 references/board-analysis-guide.md 中的涨跌停制度和连板术语。

Step 4: 连板龙头追踪
  • 识别当日最高连板股("最高标")
  • 获取该股近期 K 线,分析连板启动原因和走势
  • 对比同期次高标和跟风股
  • 连板断板后的走势预警(高位断板常伴随大幅回调)
Step 5: 输出

根据风格生成报告:

维度formalbrief
输出格式完整涨跌停复盘报告快速要点
连板梯队逐层详列+个股点评仅列最高板和关键股
板块归类分行业/概念详细归类仅标注最强主线
炸板分析炸板股逐只分析仅炸板率数字
结论客观陈述市场情绪可加简要判断

默认风格:brief。用户要求"详细分析"/"出报告"/"复盘"时用 formal。

关键规则

  1. 涨跌停制度因板块而异:主板10%、科创板/创业板20%、北交所30%、ST股5%,分析时必须区分
  2. 连板≠安全:高连板股随时可能断板,绝不暗示"还能继续涨停"
  3. 注明数据日期:始终标注分析的是哪一天的数据,避免误导
  4. 不做涨停预测:不说"明天会涨停"、"可以打板"等预测性建议
  5. 炸板风险:炸板股风险极大(冲高回落),需特别提示
  6. 数据时效:涨停池数据盘中实时更新,收盘后为最终数据,需说明取数时点

使用示例

示例 1: 基本使用
python
# 调用 skill
result = run_skill({
    "param1": "value1",
    "param2": "value2"
})
示例 2: 命令行使用
bash
python scripts/run_skill.py --input data.json

© aifinlab, 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 1 other file (references) in skills/a-share-board-analysis of aifinlab/FinClaw.

  • SKILL.md
  • references/board-analysis-guide.md

Open the folder on GitHubat commit 9e62862

Compare with similar skills

A Share Board Analysis 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.

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Questions about A Share Board Analysis

What does A Share Board Analysis do?

A股涨跌停板分析/连板追踪/涨停板统计。当用户说"涨停"、"跌停"、"涨停板"、"连板"、"打板"、"炸板"、"涨停分析"、"今天多少家涨停"、"连板股"、"首板"、"二板"、"三板"、"涨停原因"、"XX涨停了"、"涨停板分析"时触发。MUST USE when user asks about limit-up/limit-down board analysis, consecutive…. A Share Board Analysis is an agent skill from aifinlab/FinClaw. A股涨跌停板分析/连板追踪/涨停板统计。当用户说"涨停"、"跌停"、"涨停板"、"连板"、"打板"、"炸板"、"涨停分析"、"今天多少家涨停"、"连板股"、"首板"、"二板"、"三板"、"涨停原因"、"XX涨停了"、"涨停板分析"时触发。MUST USE when user asks about limit-up/limit-down board analysis, consecutive board tracking, or daily limit statistics for A-shares.

When should I use A Share Board Analysis?

A Share Board Analysis fits situations like: user asks about limit-up/limit-down board analysis; consecutive board tracking; daily limit statistics for A-shares.

How do I install A Share Board Analysis in Claude Code?

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

How do I install A Share Board Analysis in Codex?

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

Can I use A Share Board Analysis 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 aifinlab/FinClaw --skill a-share-board-analysis -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-board-analysis, .gemini/skills/a-share-board-analysis, .github/skills/a-share-board-analysis and .opencode/skills/a-share-board-analysis in your project.

What does A Share Board Analysis need to run?

Going by SKILL.md and its folder, A Share Board Analysis needs the command-line tools its instructions call (python). Our summary lists: Python 3.

Does A Share Board Analysis 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 Board Analysis 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 A Share Board Analysis use?

A Share Board Analysis 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 A Share Board Analysis use?

About 665 tokens (SKILL.md is roughly 2.7k 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 1.6k tokens, read only when the agent opens those files.

What are the alternatives to A Share Board Analysis?

Skills that share tags, products or a category with A Share Board Analysis: Sandbox Bench (vercel/next.js, 143k stars), Statistical Analysis (spacering-net/codeg, 3.9k stars), Statsmodels (zLanqing/codex-claude-academic-skills, 4.7k stars) and AI Daily Digest (vigorX777/ai-daily-digest, 1.6k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains A Share Board Analysis?

aifinlab (a GitHub user) maintains it in aifinlab/FinClaw, which has 255 GitHub stars. The repository holds 74 skills in this directory. The repository was last updated on May 13, 2026.

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