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 410417122/ashare-ai --skill asharegit clone --depth 1 https://github.com/410417122/ashare-aiWrote 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/410417122/ashare-ai/ashare)<a href="https://agentmods.dev/skills/410417122/ashare-ai/ashare"><img src="https://agentmods.dev/badge/skills/410417122/ashare-ai/ashare/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/410417122/ashare-ai/ashare"><img src="https://agentmods.dev/badge/skills/410417122/ashare-ai/ashare.svg" alt="Reviewed on agentmods" width="80" height="20"></a>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 | $0.00062 | $0.02856 |
| Opus 5.5 | $0.00025 | $0.01142 |
| Sonnet 5.5 | $0.00012 | $0.00571 |
| Haiku 4.5 | $0.00006 | $0.00286 |
Grade A, and why
ashare 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 2mo 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 — 331 lines — stays where its author put it; the contents beside it link to each section on GitHub.
A股量化交易 Skill (Tushare Pro + Backtrader)
执行哲学
你是执行者,不是教程生成器。
当用户要求回测时,他们想看到结果,不是让他们自己复制代码运行。当用户要求图表时,他们想看到图表,不是一个文件路径。
核心原则
| 用户请求 | ❌ 错误做法 | ✅ 正确做法 |
|---|---|---|
| "回测这个策略" | "这是代码,你自己运行" | 执行代码,展示回测结果 |
| "获取平安银行数据" | "用 pro.daily() 接口" | 执行代码,展示数据 |
| "画个K线图" | "保存到 chart.png" | 执行并打开图片 |
关键行为准则
- 写了代码就要运行 - 用 Bash 执行 Python,不要只给代码块
- 生成文件就要打开 - 图表/报告生成后,执行
start <filepath>(Windows) - 遇到错误就要修复 - 不要只报告错误,要调试解决
- 不确定就要查文档 - 用 context7 查询,不要凭记忆猜测
Tushare Token 配置(重要)
在首次使用或需要获取数据时,必须先询问用户使用哪种 Token 类型。
Token 类型选择
Tushare 支持两种连接方式:
方式一:官方 Token(推荐)
适用于直接从 Tushare Pro 官网注册获取的 token。
import tushare as ts
# 方法1:使用 set_token(推荐)
ts.set_token('your_official_token')
pro = ts.pro_api()
# 方法2:直接传入 token
pro = ts.pro_api('your_official_token')
方式二:中转 Token
适用于使用中转服务的 token(如 tushare.xiximiao.com)。
import tushare as ts
pro = ts.pro_api('占位符')
pro._DataApi__token = '你的中转Token'
pro._DataApi__http_url = 'http://tushare.xiximiao.com/dataapi'
使用流程
-
首次使用时询问:
请问您使用的是: 1. Tushare 官方 Token(从 tushare.pro 注册获取) 2. 中转 Token(如 tushare.xiximiao.com) 请告诉我您使用的是哪种 Token,以及您的 Token 值。 -
根据用户选择使用对应的初始化代码
-
后续使用时:
- 如果用户已经配置过,直接使用对应的方式
- 如果不确定,再次询问用户
注意事项
- 不要假设用户使用哪种方式,必须明确询问
- 官方 Token 和中转 Token 的初始化代码不同,不可混用
- 中转 Token 需要额外设置
http_url
核心原则:不确定就查文档
这是最重要的原则:遇到任何不确定的接口、参数、字段,必须用 context7 查询官方文档。
Tushare 接口查询
Library ID: /websites/tushare_pro_document
查询示例:
- "daily 日线行情 返回字段 open high low close"
- "fina_indicator 财务指标 roe eps 参数"
- "stock_basic 股票列表 industry market"
- "stk_factor_pro pe pb 市盈率 市净率"
- "moneyflow 资金流向 buy_sm buy_md"
Backtrader 功能查询
Library ID: /websites/backtrader_docu
查询示例:
- "cerebro adddata PandasData dataframe"
- "strategy buy sell order next"
- "indicator SMA EMA RSI MACD period"
- "analyzer SharpeRatio Returns DrawDown"
- "broker setcommission commission"
What ships with it
11 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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.
- 2mo ago First seen · 331 lines · 62 tokens per session scan A fc2435ad0733
ashare is a skill published in the GitHub repository 410417122/ashare-ai (21 stars, last pushed 9mo ago), licensed MIT. It adds 62 tokens to every session and 2,856 once invoked, about $0.0002 per session on Opus 5.5. 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 2026-08-30.
ashare compared with skills from other repositories
| Mod | Type | Stars | Last push | Licence | Scan | Tokens | Works with |
|---|---|---|---|---|---|---|---|
| ashare410417122/ashare-ai | Skill | 21 | 9mo ago | MIT | A | 62 | Claude Code |
| sector-rotationHKUDS/Vibe-Trading | Skill | 38k | yesterday | MIT | A | 39 | Claude Code, Codex |
| twitter-readerhimself65/finance-skills | Skill | 3.5k | 2d ago | MIT | A | 110 | Claude Code |
| strategy-pivot-designertradermonty/claude-trading-skills | Skill | 3.7k | 2d ago | MIT | A | 28 | Claude Code, Codex |
| energy-procurementhashgraph-online/awesome-codex-plugins | Skill | 1.5k | yesterday | Apache-2.0 | A | 93 | Claude Code, Codex |
| airdrop-hunting-guidenirholas/three.ws | Skill | 269 | yesterday | Apache-2.0 | A | 54 | Claude Code, Codex |
| multi-expert-analyzerdigoal/blog | Skill | 8.6k | 2d ago | GPL-2.0 | A | 292 | Codex |