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 fund-cal-return-single-fund-specific-periodgit 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/fund-cal-return-single-fund-specific-period)<a href="https://agentmods.dev/skills/ftshare-lab/ftshare-skill/fund-cal-return-single-fund-specific-period"><img src="https://agentmods.dev/badge/skills/ftshare-lab/ftshare-skill/fund-cal-return-single-fund-specific-period/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/fund-cal-return-single-fund-specific-period"><img src="https://agentmods.dev/badge/skills/ftshare-lab/ftshare-skill/fund-cal-return-single-fund-specific-period.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 | $0.00054 | $0.00468 |
| Opus 5 | $0.00027 | $0.00234 |
| Sonnet 5 | $0.00011 | $0.00094 |
| Haiku 4.5 | $0.00005 | $0.00047 |
Grade A, and why
fund-cal-return-single-fund-specific-period 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
查询指定基金在指定区间的累计收益率
参数
| 参数 | 类型 | 必填 | 说明 | 示例 |
|---|---|---|---|---|
--fund-code |
string | 是 | 6 位数字基金代码 | 159619 |
--cal-type |
string | 是 | 区间类型：1M / 3M / 6M / 1Y / 3Y / 5Y / YTD |
1Y |
用法
通过主目录 run.py 调用（必填 --fund-code、--cal-type）：
python <RUN_PY> fund-cal-return-single-fund-specific-period --fund-code 159619 --cal-type 1Y
<RUN_PY> 为主 SKILL.md 同级的 run.py 绝对路径。脚本输出 JSON 数组，每项含 date（YYYYMMDD 整型）和 return（小数形式累计收益率），按时间序列展示。
注意
- 响应为数组，不是分页结构
return为小数（如 0.0234 表示 2.34%），展示时可乘以 100 转为百分比- 区间选项：
1M（近1月）、3M（近3月）、6M（近6月）、1Y（近1年）、3Y（近3年）、5Y（近5年）、YTD（今年来） - 若用户只给基金名称，建议先用
fund-support-symbols-all-funds-paginated或fund-overview-all-funds-paginated查到对应 6 位fund-code再查询收益。
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 f7ef077b0461
- 11d ago First seen · 31 lines · 54 tokens per session scan A 072db92ebc49
fund-cal-return-single-fund-specific-period is a skill published in the GitHub repository FTShare-Lab/FTShare-skill (63 stars, last pushed yesterday), licensed MIT. It adds 54 tokens to every session and 468 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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