Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add wentorai/research-plugins --skill akshare-finance-datagit clone --depth 1 https://github.com/wentorai/research-pluginsWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/wentorai/research-plugins/akshare-finance-data)<a href="https://agentmods.dev/skills/wentorai/research-plugins/akshare-finance-data"><img src="https://agentmods.dev/badge/skills/wentorai/research-plugins/akshare-finance-data/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/wentorai/research-plugins/akshare-finance-data"><img src="https://agentmods.dev/badge/skills/wentorai/research-plugins/akshare-finance-data.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00018 | $0.01727 |
| Opus 5 | $0.00009 | $0.00864 |
| Sonnet 5 | $0.00004 | $0.00345 |
| Haiku 4.5 | $0.00002 | $0.00173 |
Grade A, and why
akshare-finance-data scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 7d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 208 lines — stays where its author put it; the contents beside it link to each section on GitHub.
AkShare Financial Data Guide
Overview
AkShare is an open-source Python library providing free access to Chinese and global financial market data. It aggregates data from 50+ sources including Sina Finance, East Money, Tushare, Yahoo Finance, and central bank websites. No API key required for most functions. Essential for financial research, quantitative analysis, and economic studies involving Chinese market data.
Installation
pip install akshare --upgrade
# Verify
python -c "import akshare as ak; print(ak.__version__)"
Core Data Categories
Stock Market Data (A-Shares)
import akshare as ak
import pandas as pd
# Real-time quotes for all A-shares
df = ak.stock_zh_a_spot_em()
print(df.head())
# Columns: 代码, 名称, 最新价, 涨跌幅, 成交量, 成交额, ...
# Historical daily data for a specific stock
df = ak.stock_zh_a_hist(symbol="000001", period="daily",
start_date="20200101", end_date="20261231")
print(df.columns)
# 日期, 开盘, 收盘, 最高, 最低, 成交量, 成交额, 振幅, 涨跌幅, 换手率
# Minute-level data
df = ak.stock_zh_a_hist_min_em(symbol="000001", period="5",
start_date="2026-01-01 09:30:00",
end_date="2026-03-10 15:00:00")
Fund Data
# ETF list
df = ak.fund_etf_spot_em()
# Open-end fund NAV history
df = ak.fund_open_fund_info_em(symbol="000001", indicator="单位净值走势")
# Fund manager information
df = ak.fund_manager_em(symbol="000001")
Bond Market
# China government bond yields
df = ak.bond_china_yield(start_date="20200101", end_date="20261231")
# Corporate bond issuance
df = ak.bond_cb_jsl() # Convertible bonds from jisilu.cn
Macroeconomic Indicators
# GDP quarterly data
df = ak.macro_china_gdp()
# CPI monthly data
df = ak.macro_china_cpi()
# PMI (Purchasing Managers' Index)
df = ak.macro_china_pmi()
# Money supply (M0, M1, M2)
df = ak.macro_china_money_supply()
# US economic data
df = ak.macro_usa_gdp() # US GDP
df = ak.macro_usa_cpi() # US CPI
df = ak.macro_usa_unemployment_rate() # US unemployment
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 7d ago First seen · 208 lines · 18 tokens per session scan A 02ca1e86b9ad
akshare-finance-data is a skill published in the GitHub repository wentorai/research-plugins (291 stars, last pushed 2mo ago), licensed MIT. It adds 18 tokens to every session and 1,727 once invoked, about $0.0001 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-09-03.
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