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 10jqk-board-listgit 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/10jqk-board-list)<a href="https://agentmods.dev/skills/ftshare-lab/ftshare-skill/10jqk-board-list"><img src="https://agentmods.dev/badge/skills/ftshare-lab/ftshare-skill/10jqk-board-list/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/10jqk-board-list"><img src="https://agentmods.dev/badge/skills/ftshare-lab/ftshare-skill/10jqk-board-list.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 | $0.00055 | $0.00576 |
| Opus 5 | $0.00028 | $0.00288 |
| Sonnet 5 | $0.00011 | $0.00115 |
| Haiku 4.5 | $0.00006 | $0.00058 |
Grade A, and why
10jqk-board-list 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 8d 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
同花顺板块列表
1. 接口描述
| 项目 | 说明 |
|---|---|
| 接口名称 | 查询同花顺板块列表 |
| 外部接口 | GET /api/v1/market/data/ths-board-list |
| 请求方式 | GET |
| 适用场景 | 查询同花顺全部板块（概念/证监会/行业/地域）的代码与名称列表 |
2. 请求参数
| 参数名 | 类型 | 是否必填 | 描述 | 取值示例 | 备注 |
|---|---|---|---|---|---|
| 无 | - | - | - | - | 接口返回全量板块列表 |
3. 响应说明
成功响应外层为 code、message、data，板块列表位于 data 数组中。
|--------|------|------|
| module | string | 板块类型：concept（概念）/ csrc（证监会）/ industry（行业）/ region（地域） |
| code | string | 板块代码 |
| name | string | 板块名称 |
示例响应：
{
"code": 200,
"message": "success",
"data": [
{ "module": "concept", "code": "885311", "name": "5G概念" },
{ "module": "industry", "code": "881001", "name": "银行" },
{ "module": "region", "code": "883001", "name": "北京" }
]
}
4. 用法
python <RUN_PY> 10jqk-board-list
python <RUN_PY> 10jqk-board-list --module concept
python <RUN_PY> 10jqk-board-list --module industry
python <RUN_PY> 10jqk-board-list --search 人工智能
5. 请求示例
GET /api/v1/market/data/ths-board-list
6. 注意事项
- 返回四类板块（concept/csrc/industry/region），客户端按
module字段过滤 - 板块代码用于后续查询 K 线等数据
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.
- 8d ago Changed · +4 lines f14858fa620c
- 12d ago First seen · 59 lines · 55 tokens per session scan A bd55337ec148
10jqk-board-list is a skill published in the GitHub repository FTShare-Lab/FTShare-skill (64 stars, last pushed today), licensed MIT. It adds 55 tokens to every session and 576 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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