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 agentmods add skills/ftshare-lab/ftshare-skill/etf-ohlcsnpx skills add FTShare-Lab/FTShare-skill --skill etf-ohlcsgit 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/etf-ohlcs)<a href="https://agentmods.dev/skills/ftshare-lab/ftshare-skill/etf-ohlcs"><img src="https://agentmods.dev/badge/skills/ftshare-lab/ftshare-skill/etf-ohlcs.svg" alt="Measured on agentmods" 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 | $0.00050 | $0.01335 |
| Opus 5 | $0.00025 | $0.00668 |
| Sonnet 5 | $0.00010 | $0.00267 |
| Haiku 4.5 | $0.00005 | $0.00134 |
Grade A, and why
etf-ohlcs 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 6d 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 — 77 lines — stays where its author put it; the contents beside it link to each section on GitHub.
ETF K 线 - 查询单只 ETF OHLC K 线（daec，日期区间）
1. 接口描述
| 项目 | 说明 |
|---|---|
| 接口名称 | 查询单只 ETF OHLC K 线 |
| 外部接口 | GET /api/v1/market/data/daec/history/ohlcs |
| 请求方式 | GET |
| 适用场景 | 获取 A 股指定 ETF 在指定日期区间、周期的 K 线（开高低收、成交量、成交额），支持日/周/月线与前/后复权 |
已从 v2（
/app/api/v2/etfs/:etf/ohlcs）迁移至 daec 统一标的接口（daec/history/ohlcs?symbol=）。对外参数契约有变：由 v2 的--span/--limit/--until_ts_ms改为--since/--until（YYYYMMDD 日期区间）+--interval+--adjust。注意：daec 不支持年线（YEAR1），响应不再含 MA5/MA10/MA20 与 prev_close。
2. 请求参数
说明：etf 为路径参数（必填），since 必填，until/interval/adjust 可选。
| 参数名 | 类型 | 是否必填 | 描述 | 取值示例 | 备注 |
|---|---|---|---|---|---|
| etf | string | 是 | ETF 标的键（路径参数，带市场后缀） | 510050.XSHG、159915.XSHE、920036.BJ | 沪 .XSHG、深 .XSHE、北交所 .BJ |
| since | string | 是 | 起始日期 YYYYMMDD | 20240101 | - |
| until | string | 否 | 结束日期 YYYYMMDD | 20240131 | 不传则默认今天 |
| interval | string | 否 | K 线周期 | Day | Day（日线，默认）、Week（周线）、Month（月线）；无年线 |
| adjust | string | 否 | 复权类型 | Forward | Forward（前复权，默认）、Backward（后复权）、None（不复权） |
3. 响应说明
返回指定 ETF 的 K 线列表，包装为 {"ohlcs": [...]}（daec 返回裸数组，脚本统一包装）：
{
"ohlcs": [
{ "open": "2.85", "high": "2.865", "low": "2.84", "close": "2.862", "volume": 125000000, "turnover": "358000000.0", "open_ts_ms": "2022-04-06T09:30:00", "close_ts_ms": "2022-04-06T15:00:00" }
]
}
Ohlc 单条（ohlcs 元素）
| 字段名 | 类型 | 是否可为空 | 说明 | 单位 |
|---|---|---|---|---|
| open | string | 否 | 开盘价 | 元 |
| high | string | 否 | 最高价 | 元 |
| low | string | 否 | 最低价 | 元 |
| close | string | 否 | 收盘价 | 元 |
| volume | long | 否 | 成交量 | 份 |
| turnover | string | 否 | 成交额 | 元 |
| open_ts_ms | string | 否 | 该根 K 线开始时间（北京时间 ISO） | - |
| close_ts_ms | string | 否 | 该根 K 线结束时间（北京时间 ISO） | - |
注：daec 接口不再返回
prev_close、MA5/MA10/MA20、has_last_empty；价格字段为字符串类型（避免浮点精度丢失）。
4. 用法
通过主目录 run.py 调用（必填 --etf、--since）：
python <RUN_PY> etf-ohlcs --etf 510050.XSHG --since 20240101 --until 20240131
python <RUN_PY> etf-ohlcs --etf 159915.XSHE --since 20240101 --until 20260628 --interval Week
python <RUN_PY> etf-ohlcs --etf 510050.XSHG --since 20230101 --interval Month --adjust Forward
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.
- 6d ago First seen · 77 lines · 50 tokens per session scan A 0d923d97a800
etf-ohlcs is a skill published in the GitHub repository FTShare-Lab/FTShare-skill (62 stars, last pushed yesterday), licensed MIT. It adds 50 tokens to every session and 1,335 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 2026-08-30.
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