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 FTShare-Lab/FTShare-skill --skill stock-dividends-effectivegit clone --depth 1 https://github.com/FTShare-Lab/FTShare-skillWrote 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/ftshare-lab/ftshare-skill/stock-dividends-effective)<a href="https://agentmods.dev/skills/ftshare-lab/ftshare-skill/stock-dividends-effective"><img src="https://agentmods.dev/badge/skills/ftshare-lab/ftshare-skill/stock-dividends-effective/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/ftshare-lab/ftshare-skill/stock-dividends-effective"><img src="https://agentmods.dev/badge/skills/ftshare-lab/ftshare-skill/stock-dividends-effective.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 | $0.00065 | $0.01040 |
| Opus 5 | $0.00032 | $0.00520 |
| Sonnet 5 | $0.00013 | $0.00208 |
| Haiku 4.5 | $0.00006 | $0.00104 |
Grade A, and why
stock-dividends-effective 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 yesterday.
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 — 68 lines — stays where its author put it; the contents beside it link to each section on GitHub.
股票有效分红记录
1. 接口描述
| 项目 | 说明 |
|---|---|
| 接口名称 | 股票有效分红记录（stock_dividends_effective） |
| 外部接口 | GET /api/v2/market/data/stock-dividends-effective |
| 请求方式 | GET（query 参数） |
| 适用场景 | 查询 A 股已实施分红记录（派息、送股、转增）分页视图，可按标的和公告日期范围筛选 |
2. 请求参数
| 参数名 | 类型 | 是否必填 | 描述 | 取值示例 | 备注 |
|---|---|---|---|---|---|
| symbol | string | 否 | 标的代码 | 600519.XSHG | 支持带交易所后缀；不传返回全市场 |
| since_date | string | 成对 | 开始公告日期 | 2026-05-26 | 格式 YYYY-MM-DD，按 ann_date 筛选 |
| until_date | string | 成对 | 结束公告日期 | 2026-05-26 | 与 since_date 成对且不早于开始日期 |
| page | int | 否 | 页码 | 1 | 从 1 开始，默认 1 |
| page_size | int | 否 | 每页条数 | 50 | 默认 50，最大 200 |
| --all | - | 否 | 自动翻页拉全量 | - | 仅本子 skill 扩展参数 |
3. 响应说明
外层固定为 code / message / data。data 为分页对象：pageNum / pageSize / total / pages / records。
records 元素：
| 字段名 | 类型 | 说明 |
|---|---|---|
| symbol | string | 标的代码（规范化为短后缀，如 600519.SH） |
| ann_date | string | 公告日期 |
| reporting_period | string | 分红所属报告期 |
| cash_dividend_ratio | string | 每股税前现金分红 |
| bonus_issue_ratio | string | 每股送股比例 |
| bonus_issue_from_capital_reserves_ratio | string | 每股转增比例 |
| ex_dividend_date | string / null | 除权除息日 |
| record_date | string / null | 股权登记日 |
| payout_date | string / null | 现金到账日 |
| share_listing_date | string / null | 送转股上市流通日 |
| ann_url | string / null | 公告链接 |
| total_cash_dividend_ratio | string / null | 同一股票同一除权日综合每股税前现金分红 |
| total_bonus_issue_ratio | string / null | 同一股票同一除权日综合每股送股比例 |
| total_bonus_issue_from_capital_reserves_ratio | string / null | 同一股票同一除权日综合每股转增比例 |
4. 调用方式
python <RUN_PY> stock-dividends-effective --symbol 600519.XSHG --page 1 --page-size 1
python <RUN_PY> stock-dividends-effective --symbol 002043.SZ --since-date 2026-05-26 --until-date 2026-05-26
python <RUN_PY> stock-dividends-effective --all
<RUN_PY> 为主 SKILL.md 同级 run.py 的绝对路径。输出 JSON；HTTP 错误输出到 stderr 并以非零状态退出。
5. 注意事项
- 只返回已实施的分红记录；未实施或已取消的不返回。
- 同一股票同一除权日可能返回多条记录；三个
total_*字段为该组合计，组内各条记录取值相同。 - 输入代码会规范化为带交易所后缀的
symbol，例如输入600519.XSHG返回600519.SH。 - 日期按公告日期
ann_date筛选，不限制日期跨度；since_date/until_date必须成对传入（handler 会本地校验并拒绝）。 --all会按pages自动翻页，把所有records合并为一个数组返回。
What ships with it
2 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.
- yesterday First seen · 68 lines · 65 tokens per session scan A dfce3bad5e5a
stock-dividends-effective is a skill published in the GitHub repository FTShare-Lab/FTShare-skill (64 stars, last pushed yesterday), licensed MIT. It adds 65 tokens to every session and 1,040 once invoked, about $0.0003 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 2026-09-11.
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