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SKILL verified MIT Self-run

Astock Utils

skill-zicxr-a-stock-skills-astock-utils · by ZICXR

A 股通用工具函数库。当 Claude 需要处理股票代码转换 (如 "sh600000" → "600000")、判断市场归属 (沪/深/北)、解析交易日历、计算技术指标 (MA/MACD/KDJ/RSI/BOLL)、格式化数字 (成交量/金额/百分比) 时,应使用此 Skill。这是其他 Skill 的基础工具库。

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Install

$ agentstack add skill-zicxr-a-stock-skills-astock-utils

✓ scanned · ✓ verified — works with Claude Code, Cursor, and more.

Security review

✓ Passed

No issues found. Passed automated security review. · v0.1.0 How review works →

  • ✓ Prompt-injection patterns
  • ✓ Secret / credential exfiltration
  • ✓ Dangerous shell & filesystem operations
  • ✓ Untrusted network calls
  • ✓ Known-malicious package signatures

What it can access

  • ✓ Network access No
  • ✓ Filesystem access No
  • ✓ Shell / process execution No
  • ✓ Environment & secrets No
  • ✓ Dynamic code execution No

From automated source analysis of v0.1.0. “Used” means the capability is present in the source — more access means more to trust, not that it’s unsafe.

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About

A 股通用工具 Skill

何时使用

  • 处理股票代码格式转换
  • 判断股票所属市场
  • 计算技术指标
  • 格式化输出
  • 解析交易日

提供能力

代码处理

  • normalize_code(code) - 规范化代码 (统一 6 位)
  • get_market(code) - 判断市场 (sh/sz/bj)
  • is_cyb(code) - 是否创业板
  • is_kcb(code) - 是否科创板
  • is_bj(code) - 是否北交所
  • is_st(name) - 是否 ST 股

日期工具

  • today_str() - 今天
  • parse_date(s) - 解析日期
  • last_n_trade_days(n) - 最近 N 个交易日
  • date_str(dt) - 日期转字符串

技术指标 (输入: DataFrame, 输出: 增加列后的 DataFrame)

  • add_ma(df, [5,10,20,60]) - 均线
  • add_macd(df) - MACD
  • add_kdj(df) - KDJ
  • add_rsi(df) - RSI
  • add_boll(df) - 布林带
  • add_all_indicators(df) - 一次性添加所有

格式化

  • fmt_volume(v) - 成交量 (1.23亿)
  • fmt_money(v) - 金额
  • fmt_pct(v) - 百分比

使用方式

# 命令行
python main.py normalize-code sh600000
python main.py market 300750
python main.py is-cyb 300750
python main.py trade-days 5

Python API

from skills.01-infra.astock-utils.main import (
    normalize_code, get_market, add_all_indicators,
    fmt_volume, fmt_pct
)

code = normalize_code("sh600000")  # "600000"
market = get_market("300750")  # "sz"
df_with_indicators = add_all_indicators(df)
print(fmt_volume(123456789))  # "1.23亿"

依赖

pandas>=1.5.0
numpy>=1.22.0
akshare>=1.12.0  # 交易日历

Source & license

This open-source skill is cataloged on AgentStack and links to its original source — we do not rehost the code.

Install and usage instructions live in the source repository linked above.

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Versions

  • v0.1.0 Imported from the upstream source.

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