a65adcc2e5
Sources: extracted from two upstream archives (skill-repo, skills-main),
merged with the following policy:
- 15 broken symlinks (pointing to /Users/jameslee/.cc-switch/skills or
../../.agents/skills on a foreign machine) discarded
- 3 real name collisions with identical content (ai-pair, ifind-http-api,
zhipu-websearch) kept as one copy
- Functional overlaps deduped keeping the strongest variant:
- docx family: kept docx (official, full toolchain) + docx-cn
(GB/T 9704 Chinese official-document constants),
dropped docx_writer (no scripts, name collided with docx)
- humanizer family: kept humanizer-zh (6 zh reference docs),
dropped humanizer (en, redundant for CN workflow)
- Skills that only ran in a foreign environment removed:
ablemind-ops, app-publish, hlb-design-system, openclaw-adj-skill,
claude-driver
- alphapai excluded from this public repo because its SKILL.md hard-coded
live credentials
Result: 25 skills, 572 files, ~7.5 MB.
Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
62 lines
2.1 KiB
Markdown
62 lines
2.1 KiB
Markdown
## 大盘指数每日指标
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----
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接口：index_dailybasic，可以通过[**数据工具**](https://tushare.pro/webclient/)调试和查看数据。
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描述：目前只提供上证综指，深证成指，上证50，中证500，中小板指，创业板指的每日指标数据
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数据来源：Tushare社区统计计算
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数据历史：从2004年1月开始提供
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数据权限：用户需要至少400积分才可以调取，具体请参阅[积分获取办法](https://tushare.pro/document/1?doc_id=13)
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**输入参数**
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名称 | 类型 | 必选 | 描述
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---- | ----- | ---- | ----
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trade_date | str | N | 交易日期 （格式：YYYYMMDD，比如20181018，下同）
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ts_code | str | N | TS代码
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start_date | str | N | 开始日期
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end_date | str | N | 结束日期
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注：trade_date，ts_code 至少要输入一个参数，单次限量3000条（即，单一指数单次可提取超过12年历史），总量不限制。
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**输出参数**
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名称 | 类型 | 默认显示 | 描述
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--- | ---- | ---- | ----
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ts_code | str | Y | TS代码
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trade_date | str | Y | 交易日期
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total_mv | float | Y | 当日总市值（元）
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float_mv | float | Y | 当日流通市值（元）
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total_share | float | Y | 当日总股本（股）
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float_share | float | Y | 当日流通股本（股）
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free_share | float | Y | 当日自由流通股本（股）
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turnover_rate | float | Y | 换手率
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turnover_rate_f | float | Y | 换手率(基于自由流通股本)
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pe | float | Y | 市盈率
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pe_ttm | float | Y | 市盈率TTM
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pb | float | Y | 市净率
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**接口示例**
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```python
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pro = ts.pro_api()
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df = pro.index_dailybasic(trade_date='20181018', fields='ts_code,trade_date,turnover_rate,pe')
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```
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**数据示例**
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ts_code trade_date turnover_rate pe
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0 000001.SH 20181018 0.38 11.92
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1 000300.SH 20181018 0.27 11.17
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2 000905.SH 20181018 0.82 18.03
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3 399001.SZ 20181018 0.88 17.48
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4 399005.SZ 20181018 0.85 21.43
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5 399006.SZ 20181018 1.50 29.56
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6 399016.SZ 20181018 1.06 18.86
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7 399300.SZ 20181018 0.27 11.17 |