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 adambbhe/TDX-finance-mcp-plugin-v3 --skill tdx-event-driven-short-term-catalystgit clone --depth 1 https://github.com/adambbhe/TDX-finance-mcp-plugin-v3Wrote 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/adambbhe/tdx-finance-mcp-plugin-v3/tdx-event-driven-short-term-catalyst)<a href="https://agentmods.dev/skills/adambbhe/tdx-finance-mcp-plugin-v3/tdx-event-driven-short-term-catalyst"><img src="https://agentmods.dev/badge/skills/adambbhe/tdx-finance-mcp-plugin-v3/tdx-event-driven-short-term-catalyst/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/adambbhe/tdx-finance-mcp-plugin-v3/tdx-event-driven-short-term-catalyst"><img src="https://agentmods.dev/badge/skills/adambbhe/tdx-finance-mcp-plugin-v3/tdx-event-driven-short-term-catalyst.svg" alt="Reviewed on agentmods" width="80" 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 | $0.00162 | $0.01649 |
| Opus 5 | $0.00081 | $0.00825 |
| Sonnet 5 | $0.00032 | $0.00330 |
| Haiku 4.5 | $0.00016 | $0.00165 |
Grade A, and why
事件驱动与短线催化分析 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 12d 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.
How it starts
The opening of the file, as written. The whole thing — 131 lines — stays where its author put it; the contents beside it link to each section on GitHub.
事件驱动短线催化
Skill 分类 事件驱动 / 短线交易 / 预期差博弈
适用人群 短线交易者、题材交易者、波段投资者
适用场景 用户关心某只股票未来几天是否有交易机会，核心催化是什么，市场会如何演绎，以及应该如何跟踪。
输出结构
- 核心催化
- 催化强度与级别
- 市场预期差
- 资金与板块联动
- 可能路径推演
- 风险提示
- 操作建议
必查数据
个股行情（必查）
tdx_quotes(code=股票代码, setcode=市场代码, hasHQInfo="1", hasExtInfo="1", hasProInfo="1", bspNum="5")tdx_kline(code=股票代码, setcode=市场代码, period="4", wantNum="5", tqFlag="11")
板块联动（必查）
- 结合所属行业、概念题材、同题材个股表现判断联动强弱
- 必要时配合
tdx_screener观察涨停分布与梯队高度
资金博弈（必查）
- 看成交量、换手率、盘口强弱、量比、封单与回封能力
- 若存在明显游资博弈特征，要明确说明其持续性风险
事件验证（必查）
tdx_api_data(entry="tdxf10_gg_rdtc", fixedTag="sjcd") name="事件/股票"tdx_api_data：查询公司公告、事件标签、业务相关信息，验证事件与公司关联度
分析框架
第一步：判断催化类型
常见催化包括：
- 政策催化
- 产业催化
- 业绩催化
- 公告催化
- 海外映射
- 情绪催化
不同类型的事件，持续性完全不同。必须先判断是“基本面催化”还是“交易型催化”。
第二步：判断催化强度
可分为四档：
- 强催化：级别高、影响范围广、持续性较强
- 中催化：有逻辑，但需要板块或资金配合
- 弱催化：消息存在，但持续性一般
- 噪音：消息不构成有效交易逻辑
第三步：判断预期差
真正的短线机会来自预期差，而不是消息本身。 重点判断：
- 市场是否已经知道这条消息
- 当前股价和板块是否提前交易过
- 龙头还是后排，谁更容易承接预期差
- 如果超预期，谁会先受益
第四步：看资金和板块是否支持
至少要回答：
- 个股是否处于强势位置
- 所属板块是否有扩散能力
- 龙头、中军、跟风之间是否形成梯队
- 资金是接力、低吸还是兑现
第五步：做路径推演
至少给出三种情景：
- 最强情景：催化继续发酵，资金强化，板块扩散
- 中性情景：冲高震荡，只有局部机会
- 弱势情景：消息兑现、承接不足、快速回落
第六步：给出跟踪点与操作建议
重点告诉用户：
- 明天应该看什么
- 哪个信号代表强化
- 哪个信号代表降温
- 是否适合追涨、低吸、观察或回避
输出要求
- 必须把“催化、预期、博弈、路径”讲清楚
- 必须说明该事件和公司是强关联还是弱关联
- 必须明确催化级别和持续性判断
- 不要把所有消息都当成重大利好
- 如果事件强度不足，要明确建议降低预期
⚠️ 数据准确性规范
金融分析常见数据错误，必须规避：
| # | 常见错误 | 正确做法 |
| 8 | 成交额/市值必须逐位读数 | 看到大数字必须用计算器核实，不能凭印象估算。示例：21385988100/1亿=213.86亿（不是21.39亿）。凡是金额类数字，输出前必须用计算器验证一次。 |
|---|---------|---------| | 1 | 成交额单位混淆 | tdx_quotes 的 Amount 单位是"元"，除以1亿得"亿元"（如 5615563780/1亿=56.16亿）。禁止把原始值当成亿元直接使用。 | | 2 | 成交量单位混淆 | Volume 单位是"手"（如 8283895手=828.39万手），Inside/Outside 同理。 | | 3 | 涨幅凭印象描述 | Lead 字段已是 %，直接使用；K线涨幅=(今收-昨收)/昨收×100%。禁止写"大概涨了多少"。 | | 4 | 把T+1数据当当日数据 | tdx_api_data 资金流向(zjlx)最新日期为上一交易日，不可描述为"今日主力净流入"。 | | 5 | 高开/涨幅模糊描述 | 必须写明：如"高开3%（开盘6.87元，昨收6.54元）"，禁止写"高开明显"。 | | 6 | 市值/股本单位错 | ZSZ 单位是"元"（/1亿）；ZGB/LTGB 单位是万股（如 357258.969万股=35.73亿股）。 | | 7 | 金融数据估算 | 禁止"大概"、"差不多"。所有数字必须计算后写出等于多少，不凭印象。必须逐位核实。 |
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.
- 12d ago First seen · 131 lines · 162 tokens per session scan A 05e224573b10
事件驱动与短线催化分析 is a skill published in the GitHub repository adambbhe/TDX-finance-mcp-plugin-v3 (35 stars, last pushed 2mo ago), licensed MIT. It adds 162 tokens to every session and 1,649 once invoked, about $0.0008 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.
Other skills, from other repositories
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hithink-finance-data
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hithink-finance-market
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hithink-finance-special-data
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hithink-finance-futures
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