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 index-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/index-candlesticks-batch)<a href="https://agentmods.dev/skills/ftshare-lab/ftshare-skill/index-candlesticks-batch"><img src="https://agentmods.dev/badge/skills/ftshare-lab/ftshare-skill/index-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/index-candlesticks-batch"><img src="https://agentmods.dev/badge/skills/ftshare-lab/ftshare-skill/index-candlesticks-batch.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 | $0.01178 |
| Opus 5 | $0.00031 | $0.00589 |
| Sonnet 5 | $0.00012 | $0.00236 |
| Haiku 4.5 | $0.00006 | $0.00118 |
Grade A, and why
index-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.
批量指数K线
1. 接口描述
| 项目 | 说明 |
|---|---|
| 接口名称 | 批量指数K线（index_candlesticks_batch） |
| 外部接口 | GET /api/v2/market/data/index-candlesticks/batch |
| 请求方式 | GET（query 参数，symbols 可重复传入） |
| 适用场景 | 一次批量获取多个指数的历史 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 |
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 | 指数代码列表，逗号分隔传给 CLI | 000300.SH,399001.SZ | 沪市支持 .XSHG/.SH，深市支持 .XSHE/.SZ；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 | 2 | 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 | 指数代码，响应统一使用 .SH、.SZ 短后缀 |
- |
| open / high / low / close | number | 开/高/低/收盘点位 | 指数点 |
| 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（指数成分股合计） | 元 |
| volume | integer | 成交量（指数成分股合计） | - |
| turnover_rate | number | 换手率；指数标的当前为 null |
% |
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> index-candlesticks-batch --symbols 000300.SH,399001.SZ --interval-unit Day --since-ts-millis 1756431000000 --until-ts-millis 1756791000000 --limit 2
python <RUN_PY> index-candlesticks-batch --symbols 000300.XSHG,399001.XSHE --interval-unit Week --adjust-kind Forward --since-ts-millis 1754092800000 --until-ts-millis 1756791000000
<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
symbols、interval_unit、since_ts_millis、until_ts_millis必填；所有symbols使用相同周期。- 接口仅支持 GET；
symbols在查询参数中以重复参数形式发送（symbols=000300.SH&symbols=399001.SZ）。 - 时间跨度最多 12 个日历月；需要更长历史时按窗口分段多次调用。
- 不支持分钟 K 线；分钟数据请使用
index-minutes-batch子 skill。 symbols中每项必须是指数标的：若混入非指数（如 ETF、股票），整个批量请求失败，不静默过滤（当前返回系统错误）。- 输入
.XSHG/.XSHE长后缀时，响应中的 symbol 会规范化为.SH、.SZ短后缀。 - 默认不复权（None）；仅使用历史日 K 数据计算，不含实时行情，实际起始日期以行情数据源覆盖为准。
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 · 62 lines · 62 tokens per session scan A f8bdf4f288d7
index-candlesticks-batch is a skill published in the GitHub repository FTShare-Lab/FTShare-skill (64 stars, last pushed yesterday), licensed MIT. It adds 62 tokens to every session and 1,178 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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