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-performance-express-all-stocks-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/stock-performance-express-all-stocks-specific-period)<a href="https://agentmods.dev/skills/ftshare-lab/ftshare-skill/stock-performance-express-all-stocks-specific-period"><img src="https://agentmods.dev/badge/skills/ftshare-lab/ftshare-skill/stock-performance-express-all-stocks-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/stock-performance-express-all-stocks-specific-period"><img src="https://agentmods.dev/badge/skills/ftshare-lab/ftshare-skill/stock-performance-express-all-stocks-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 | $0.00060 | $0.00424 |
| Opus 5 | $0.00030 | $0.00212 |
| Sonnet 5 | $0.00012 | $0.00085 |
| Haiku 4.5 | $0.00006 | $0.00042 |
Grade A, and why
stock-performance-express-all-stocks-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 9d 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
查询指定报告期全市场业绩快报（分页）
参数
| 参数 | 类型 | 必填 | 说明 | 示例 |
|---|---|---|---|---|
--year |
int | 是 | 报告所属年度 | 2024 |
--report-type |
string | 是 | 报告期类型：q1/q2/q3/annual |
annual |
--page |
int | 否 | 页码，从 1 开始（默认 1） | 1 |
--page-size |
int | 否 | 每页记录数（默认 20） | 20 |
用法
从用户问题中提取年度和报告期类型，执行：
python scripts/handler.py --year 2024 --report-type annual --page 1 --page-size 20
脚本输出带分页信息的 JSON，每项含 stock_code、stock_name、eps、total_revenue、net_profit、roe 等字段，以表格展示给用户。
注意
report-type取值：q1（一季报）、q2（半年报）、q3（三季报）、annual（年报）- 需要全量数据时，循环请求直到
page > total_pages
调用示例
python <RUN_PY> stock-performance-express-all-stocks-specific-period --year 2025 --report-type annual --page 1 --page-size 5
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.
- 9d ago First seen · 37 lines · 60 tokens per session scan A 7057e6499ec4
stock-performance-express-all-stocks-specific-period is a skill published in the GitHub repository FTShare-Lab/FTShare-skill (64 stars, last pushed yesterday), licensed MIT. It adds 60 tokens to every session and 424 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 2026-09-03.
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