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 economic-china-retail-sales-monthlygit 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/economic-china-retail-sales-monthly)<a href="https://agentmods.dev/skills/ftshare-lab/ftshare-skill/economic-china-retail-sales-monthly"><img src="https://agentmods.dev/badge/skills/ftshare-lab/ftshare-skill/economic-china-retail-sales-monthly/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/economic-china-retail-sales-monthly"><img src="https://agentmods.dev/badge/skills/ftshare-lab/ftshare-skill/economic-china-retail-sales-monthly.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 | $0.00064 | $0.00647 |
| Opus 5 | $0.00032 | $0.00324 |
| Sonnet 5 | $0.00013 | $0.00129 |
| Haiku 4.5 | $0.00006 | $0.00065 |
Grade A, and why
economic-china-retail-sales-monthly 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
中国经济 - 社会消费品零售总额（月度）
1. 接口描述
| 项目 | 说明 |
|---|---|
| 接口名称 | 社会消费品零售总额（月度汇总计算结果） |
| 外部接口 | GET /api/v1/market/data/economic/china-retail-sales |
| 请求方式 | GET |
| 适用场景 | 获取中国社会消费品零售总额月度数据，含当月值、同比、累计及累计同比等 |
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. 用法
直接执行：
python script/handler.py
脚本输出 JSON 数组，按时间倒序，每项含 month（如 2025年03月份）、current（当月值）、yoy（同比 %）、cumulative（累计值）、cumulative_yoy（累计同比 %）、unit（亿元）、currency（CNY），以表格展示给用户。
4. 响应说明
返回值为社会消费品零售总额月度计算结果列表，按时间倒序。
RetailSalesComputed 结构
| 字段名 | 类型 | 是否可为空 | 说明 | 单位 |
|---|---|---|---|---|
| month | String | 否 | 月份，格式如 2025年03月份 | - |
| current | float | 是 | 当月值 | 见 unit |
| yoy | float | 是 | 同比增长 | % |
| cumulative | float | 是 | 累计值 | 见 unit |
| cumulative_yoy | float | 是 | 累计同比增长 | % |
| unit | String | 否 | 货币单位 | - |
| currency | String | 否 | 货币种类 | - |
5. 请求示例
GET /api/v1/market/data/economic/china-retail-sales
6. 注意事项
- 返回按月份汇总，格式如「2025年03月份」，列表已按时间倒序，最新月份在前。
- 金额单位见
unit（通常为亿元），同比单位为 %，各数值字段可为 null。
调用示例
python <RUN_PY> economic-china-retail-sales-monthly
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 Changed · +6 lines a925c46c991a
- 12d ago First seen · 61 lines · 64 tokens per session scan A e51995cb4d1a
economic-china-retail-sales-monthly is a skill published in the GitHub repository FTShare-Lab/FTShare-skill (64 stars, last pushed yesterday), licensed MIT. It adds 64 tokens to every session and 647 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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