Agent Skills

Tushare Pro 金融数据 API 查询助手。用于帮助用户查询中国股票、基金、期货、债券等金融数据。当用户需要获取股票行情、财务数据、基础信息、宏观经济数据时使用此 skill。

Install

npx skills add https://github.com/daydreammy/tushare-openclaw-skill --skill tushare-api
SKILL.md

Tushare API Skill

简介

Tushare Pro 是中国领先的金融数据平台,提供股票、基金、期货、债券、外汇、数字货币等全品类金融大数据。

官网: https://tushare.pro API 文档: https://tushare.pro/document/2

股票代码规范

所有股票代码都需要带后缀:

交易所 后缀 示例
上海证券交易所 .SH 600000.SH
深圳证券交易所 .SZ 000001.SZ
北京证券交易所 .BJ 835305.BJ
香港证券交易所 .HK 00001.HK

常用 API 接口

基础数据

  • stock_basic - 股票基础信息
  • trade_cal - 交易日历
  • stock_company - 上市公司基本信息
  • new_share - IPO 新股列表

行情数据

  • daily - 日线行情
  • weekly - 周线行情
  • monthly - 月线行情
  • adj_factor - 复权因子
  • daily_basic - 每日指标(PE/PB/市值等)

财务数据

  • income - 利润表
  • balance_sheet - 资产负债表
  • cashflow - 现金流量表
  • forecast - 业绩预告
  • express - 业绩快报
  • dividend - 分红送股
  • fina_indicator - 财务指标

市场数据

  • moneyflow - 个股资金流向
  • limit_list - 每日涨跌停股票
  • top_list - 龙虎榜数据
  • block_trade - 大宗交易

使用方法

Python SDK

import tushare as ts

# 设置 token(需要用户自行申请)
pro = ts.pro_api('your_token_here')

# 获取股票列表
df = pro.stock_basic(exchange='', list_status='L', fields='ts_code,symbol,name,area,industry,list_date')

# 获取日线行情
df = pro.daily(ts_code='000001.SZ', start_date='20240101', end_date='20240201')

# 获取财务数据
df = pro.income(ts_code='600000.SH', start_date='20230101', end_date='20231231')

HTTP API

curl -X POST https://api.tushare.pro \
  -H "Content-Type: application/json" \
  -d '{
    "api_name": "daily",
    "token": "your_token",
    "params": {"ts_code": "000001.SZ", "start_date": "20240101"},
    "fields": "ts_code,trade_date,open,high,low,close,vol"
  }'

积分系统

详细文档

更多接口详情见 references/api-reference.md

注意事项

  1. 需要申请 token 才能使用 API
  2. 注意积分消耗,高频接口消耗更多积分
  3. 数据有更新延迟,日线数据通常在收盘后 1-2 小时更新
  4. 免费用户有调用频次限制

Related skills

researchmattpocock575KInvestigate a question against high-trust primary sources and capture the findings as a Markdown file in the repo. Use when the user wants a topic researched, docs or API facts gathered, or reading legwork delegated to a background agent.paper-context-resolverlllllllama451KRigor Paper Context helper for README-first deep learning repo reproduction. Use only when the README and repository files leave a narrow reproduction-critical gap and the task is to resolve a specific paper detail such as dataset split, preprocessing, evaluation protocol, checkpoint mapping, or runtime assumption from primary paper sources while recording conflicts. Do not use for general paper summary, repo scanning, environment setup, command execution, title-only paper lookup, or replacing Renv-and-assets-bootstraplllllllama450KRigor Setup skill for README-first deep learning repo reproduction. Use when the task is specifically to prepare a conservative conda-first environment, checkpoint and dataset path assumptions, cache location hints, and setup notes before any run on a README-documented repository. Do not use for repo scanning, full orchestration, paper interpretation, final run reporting, or generic environment setup that is not tied to a specific reproduction target.ai-research-explorelllllllama311KRigor Explore compatible skill slug for meaningful and potentially novel deep learning research candidates. Use when the researcher has chosen the task family, dataset, benchmark, evaluation method, provided SOTA references, and wants candidate-only exploration on top of `current_research` with auditable repo understanding, idea gating, fair comparison, and governed experiments written to `explore_outputs/`. Do not use for README-first trusted reproduction, open-ended direction finding, narrow c

Search skills and MCP servers

Fuzzy search across 23,137 skills and servers