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 etf-description-allgit 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-description-all)<a href="https://agentmods.dev/skills/ftshare-lab/ftshare-skill/etf-description-all"><img src="https://agentmods.dev/badge/skills/ftshare-lab/ftshare-skill/etf-description-all.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 | $0.00043 | $0.00755 |
| Opus 5 | $0.00022 | $0.00378 |
| Sonnet 5 | $0.00009 | $0.00151 |
| Haiku 4.5 | $0.00004 | $0.00076 |
Grade A, and why
etf-description-all 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 3d 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.
What it actually says
ETF-查询全部ETF基础信息
1. 接口描述
| 项目 | 说明 |
|---|---|
| 接口名称 | 查询全部ETF基础信息 |
| 外部接口 | /api/v2/market/data/etf-description-all |
| 请求方式 | GET |
| 适用场景 | 获取 ETF 列表（代码与名称）及部分基础属性信息，用于列表展示、筛选与检索 |
2. 请求参数
说明：该接口无需请求参数
| 参数名 | 类型 | 是否必填 | 描述 | 取值示例 | 备注 |
|---|---|---|---|---|---|
| - | - | - | 无需参数 | - | - |
3. 响应说明
返回值为 ETF 基础信息数组，数据模型如下：
[
EtfDescriptionItem
]
EtfDescriptionItem 结构
| 字段名 | 类型 | 是否可为空 | 说明 | 单位 |
|---|---|---|---|---|
| asset_class | String | 否 | 基金类型，当前外部返回小写字符串（如 stock、bond、commodity、currency） |
- |
| custodian | String | 否 | 基金托管人（通常为托管银行） | - |
| float_shares | int | 是 | 流通份额，无数据时为 null | 份 |
| inception_date | String | 否 | 成立日期，格式 YYYY-MM-DD |
- |
| management_company | String | 否 | 基金管理人 | - |
| name | String | 否 | ETF 名称 | - |
| symbol | String | 否 | ETF 标的代码，带交易所后缀 | - |
4. 用法
通过主目录 run.py 调用（无需参数）：
python <RUN_PY> etf-description-all
<RUN_PY> 为主 SKILL.md 同级的 run.py 绝对路径。脚本输出 JSON 数组，可直接用于“名称 -> symbol”映射。
5. 请求示例
GET /api/v1/market/data/etf-description-all
6. 响应示例
[
{
"asset_class": "currency",
"custodian": "交通银行",
"float_shares": 3955933,
"inception_date": "2013-03-29",
"management_company": "易方达基金",
"name": "货币ETF易方达",
"symbol": "159001.XSHE"
}
]
7. 数据更新时间与注意事项
- 数据更新时间以接口/数据源为准。
- 当用户只给 ETF 名称或简称时，建议先调用本接口做名称匹配，拿到唯一
symbol后再调用etf-detail、etf-ohlcs、etf-prices、etf-components-all、etf-pre-single。 - 若名称匹配到多个
symbol，先让用户确认目标标的，再继续查询指标。
What ships with it
1 file 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.
- 3d ago Changed 1f5765a1b105
- 7d ago First seen · 84 lines · 43 tokens per session scan A 6da32d726181
etf-description-all is a skill published in the GitHub repository FTShare-Lab/FTShare-skill (62 stars, last pushed 2d ago), licensed MIT. It adds 43 tokens to every session and 755 once invoked, about $0.0002 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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