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-candlesticks-batchgit 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-candlesticks-batch)<a href="https://agentmods.dev/skills/ftshare-lab/ftshare-skill/stock-candlesticks-batch"><img src="https://agentmods.dev/badge/skills/ftshare-lab/ftshare-skill/stock-candlesticks-batch/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-candlesticks-batch"><img src="https://agentmods.dev/badge/skills/ftshare-lab/ftshare-skill/stock-candlesticks-batch.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 | $0.00107 | $0.01270 |
| Opus 5 | $0.00053 | $0.00635 |
| Sonnet 5 | $0.00021 | $0.00254 |
| Haiku 4.5 | $0.00011 | $0.00127 |
Grade A, and why
stock-candlesticks-batch 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 — 62 lines — stays where its author put it; the contents beside it link to each section on GitHub.
批量股票K线
1. 接口描述
| 项目 | 说明 |
|---|---|
| 接口名称 | 批量股票K线（stock_candlesticks_batch） |
| 外部接口 | GET /api/v2/market/data/stock-candlesticks/batch |
| 请求方式 | GET（query 参数，symbols 可重复传入） |
| 适用场景 | 一次批量查询股票 / ETF / 可转债 / 指数等多只标的的历史 K 线（开高低收、成交量、成交额、换手率），支持日/周/月/年周期与前复权/后复权。通用语义，允许不同证券类别混合查询，不做类别校验 |
2. 请求参数
| 参数名 | 类型 | 是否必填 | 描述 | 取值示例 | 备注 |
|---|---|---|---|---|---|
| symbols | string[] | 是 | 标的代码列表，逗号分隔传给 CLI | 600519.SH,510300.SH,113027.SH,000300.SH | 可混合股票/ETF/可转债/指数；沪市 .XSHG/.SH、深市 .XSHE/.SZ、北交所 .BJSE/.BJ；接口侧以重复 query 参数发送 |
| interval_unit | string | 是 | 周期单位 | Day | Day/Week/Month/Year，大小写不敏感；不支持 Minute |
| adjust_kind | string | 否 | 复权类型 | Forward | None（默认）/Forward（前复权）/Backward（后复权） |
| since_ts_millis | int | 是 | 开始时间戳（毫秒） | 1756431000000 | 与 until 的跨度不得超过 12 个日历月；不得晚于 until |
| until_ts_millis | int | 是 | 结束时间戳（毫秒） | 1756791000000 | - |
| limit | int | 否 | 每个标的返回条数上限 | 3 | 不传时返回请求时间范围内的全部数据 |
3. 响应说明
外层固定为 code（成功 200）/ message（成功 success）/ data（失败时为 null）。data 为非分页嵌套数组，外层每项为 [symbol, K线数组]，每根 K 线字段：
| 字段名 | 类型 | 说明 | 单位 |
|---|---|---|---|
| symbol | string | 标的代码，响应统一使用 .SH、.SZ、.BJ 短后缀 |
- |
| open / high / low / close | number | 开/高/低/收盘价 | 元 |
| ts_millis | string | 收盘时间戳 | 毫秒 |
| ts_millis_open | string | 开盘时间戳 | 毫秒 |
| turnover | number | 成交额 | 元 |
| volume | integer | 成交量 | - |
| turnover_rate | number | 换手率 | % |
注：open/high/low/close、turnover 在 JSON 中实际以字符串返回（避免精度丢失）；ts_millis 为数字。
4. 调用方式
python <RUN_PY> stock-candlesticks-batch --symbols 600519.SH,000001.SZ --interval-unit Day --since-ts-millis 1756431000000 --until-ts-millis 1756791000000 --limit 2
python <RUN_PY> stock-candlesticks-batch --symbols 600519.SH,510300.SH,113027.SH --interval-unit Week --adjust-kind Forward --since-ts-millis 1756431000000 --until-ts-millis 1756791000000 --limit 3
<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。
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 Changed · +2 lines · -4 tokens per session 8b490d2bef26
- 8d ago First seen · 60 lines · 111 tokens per session scan A 7c72e0629187
stock-candlesticks-batch is a skill published in the GitHub repository FTShare-Lab/FTShare-skill (64 stars, last pushed yesterday), licensed MIT. It adds 107 tokens to every session and 1,270 once invoked, about $0.0005 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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