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>
80 lines
3.0 KiB
Markdown
80 lines
3.0 KiB
Markdown
## A股日线行情
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----
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接口：daily，可以通过[**数据工具**](https://tushare.pro/webclient/)调试和查看数据
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数据说明：交易日每天15点～16点之间入库。本接口是未复权行情，停牌期间不提供数据
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调取说明：基础积分每分钟内可调取500次，每次6000条数据，一次请求相当于提取一个股票23年历史
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描述：获取股票行情数据，或通过[**通用行情接口**]( https://tushare.pro/document/2?doc_id=109)获取数据，包含了前后复权数据
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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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ts_code | str | N | 股票代码（支持多个股票同时提取，逗号分隔）
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trade_date | str | N | 交易日期（YYYYMMDD）
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start_date | str | N | 开始日期(YYYYMMDD)
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end_date | str | N | 结束日期(YYYYMMDD)
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**注：日期都填YYYYMMDD格式，比如20181010**
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**输出参数**
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名称 | 类型 | 描述
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--- | ---- | ----
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ts_code | str | 股票代码
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trade_date | str | 交易日期
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open | float | 开盘价
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high | float | 最高价
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low | float | 最低价
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close | float | 收盘价
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pre_close | float | 昨收价【除权价】
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change | float | 涨跌额
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pct_chg | float | 涨跌幅 【基于除权后的昨收计算的涨跌幅：（今收-除权昨收）/除权昨收 】
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vol | float | 成交量 （手）
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amount | float | 成交额 （千元）
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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.daily(ts_code='000001.SZ', start_date='20180701', end_date='20180718')
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#多个股票
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df = pro.daily(ts_code='000001.SZ,600000.SH', start_date='20180701', end_date='20180718')
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```
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或者
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```python
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df = pro.query('daily', ts_code='000001.SZ', start_date='20180701', end_date='20180718')
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```
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也可以通过日期取历史某一天的全部历史
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```python
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df = pro.daily(trade_date='20180810')
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```
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**数据样例**
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ts_code trade_date open high low close pre_close change pct_chg vol amount
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0 000001.SZ 20180718 8.75 8.85 8.69 8.70 8.72 -0.02 -0.23 525152.77 460697.377
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1 000001.SZ 20180717 8.74 8.75 8.66 8.72 8.73 -0.01 -0.11 375356.33 326396.994
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2 000001.SZ 20180716 8.85 8.90 8.69 8.73 8.88 -0.15 -1.69 689845.58 603427.713
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3 000001.SZ 20180713 8.92 8.94 8.82 8.88 8.88 0.00 0.00 603378.21 535401.175
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4 000001.SZ 20180712 8.60 8.97 8.58 8.88 8.64 0.24 2.78 1140492.31 1008658.828
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5 000001.SZ 20180711 8.76 8.83 8.68 8.78 8.98 -0.20 -2.23 851296.70 744765.824
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6 000001.SZ 20180710 9.02 9.02 8.89 8.98 9.03 -0.05 -0.55 896862.02 803038.965
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7 000001.SZ 20180709 8.69 9.03 8.68 9.03 8.66 0.37 4.27 1409954.60 1255007.609
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8 000001.SZ 20180706 8.61 8.78 8.45 8.66 8.60 0.06 0.70 988282.69 852071.526
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9 000001.SZ 20180705 8.62 8.73 8.55 8.60 8.61 -0.01 -0.12 835768.77 722169.579
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