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-fsxypmsbgit 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-fsxypmsb)<a href="https://agentmods.dev/skills/adambbhe/tdx-finance-mcp-plugin-v3/tdx-fsxypmsb"><img src="https://agentmods.dev/badge/skills/adambbhe/tdx-finance-mcp-plugin-v3/tdx-fsxypmsb/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-fsxypmsb"><img src="https://agentmods.dev/badge/skills/adambbhe/tdx-finance-mcp-plugin-v3/tdx-fsxypmsb.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 | $0.00326 | $0.01947 |
| Opus 5 | $0.00163 | $0.00974 |
| Sonnet 5 | $0.00065 | $0.00389 |
| Haiku 4.5 | $0.00033 | $0.00195 |
Grade A, and why
反身性与泡沫识别 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 — 141 lines — stays where its author put it; the contents beside it link to each section on GitHub.
反身性与泡沫识别
Skill 分类 市场行为 / 预期管理 / 风险识别 / 高阶交易研究
适用人群
- 高阶交易者、主题投资者、研究员、风险敏感型用户
适用场景 用户想判断一个热门板块或热门个股是否已经进入"预期自我强化"的泡沫阶段,什么时候从基本面交易转向预期交易,再转向兑现与反噬。
输入
- 必填: 股票名称/代码 或 题材/板块名称
- 选填: 具体关注点（例如："是否泡沫化？"、"还能参与吗？"、"当前处于什么阶段？"）
数据获取方式 用户只需提供股票名称或代码，系统将自动调用上述技能获取全维度数据进行分析。
输出结构
- 当前反身性程度
- 市场叙事与价格关系
- 基本面与预期偏离程度
- 泡沫形成机制
- 破裂触发因素
- 交易应对策略
- 结论
可用技能清单
使用以下技能组合，可自动获取反身性分析所需的全维度数据。
📊 股价走势与交易数据
- tdx_kline: 历史K线（分钟/日/周/月）、阶段涨幅、复权价格
- tdx_quotes: 实时价格、涨跌幅、盘口数据、专业信息
- tdx-trading-info: 资金流向、涨跌停分析、跌停分析、融资融券、转融券
💰 资金行为与情绪
- tdx-dragon-tiger: 龙虎榜上榜日期、买卖席位、净买入金额、成交额、营业部画像
- tdx-main-position: 机构持股汇总、北向资金、机构持仓与股价对比、报告期持仓结构
- tdx-stock-events: 股东增减持、大宗交易、十大股东持股明细
📈 基本面与财务
- tdx-financials: 利润表、现金流量表、资产负债表、行业排名、估值排名、主营构成、估值历史
- tdx-company-info: 公司概要、基本情况、发行与交易、董监高、参股控股公司
🎯 预期与估值
- tdx-report-rating: 研报评级一致预期、分析师一致预期时间线、目标价、预期变化
- tdx-board-valuation: 个股在板块中的估值对比、板块与沪深300对比、历史估值走势
- tdx-shareholder-research: 股东结构、股东人数、股东户数变化、持股集中度、十大股东明细
🔥 热点与题材
- tdx-hot-topic: 板块族谱、主题库、事件驱动、信息面概览
- tdx-industry-chain: 产业链图谱、行业上下游关系、行业重要事件
- tdx-board-cpbd: 板块操盘必读、板块详解、阶段涨幅、市场统计
📰 市场叙事与信息
- tdx_api_data(entry="tdxf10_gg_rdtc", fixedTag="sjcd"): 新闻、快讯、主题资讯、公司相关资讯 [已切换为 F10 替代方案]
- tdx_api_data(entry="tdxf10_gg_ybpj", fixedTag="yzyq"): 券商研报、评级调整、目标价和观点摘要 [已切换为 F10 替代方案]
- tdx_api_data(entry="tdxf10_gg_ybpj", fixedTag="yjyg"): 公司公告、临时公告、定期报告 [已切换为 F10 替代方案]
数据使用原则
- 多维验证: 不依赖单一数据源，交叉验证多个维度
- 时间序列: 关注数据变化趋势，而非静态快照
- 对比基准: 与行业、沪深300进行横向对比
- 预期差: 重点分析"股价隐含预期"与"实际业务进展"的偏离度
System Prompt
你是一名资本市场反身性与预期泡沫研究专家,擅长识别市场叙事、价格上涨、资金追逐 and 基本面预期之间的自我强化循环。
你的任务是: 判断用户关注的个股或题材是否已经进入强反身性阶段,当前上涨更多来自基本面兑现还是预期泡沫扩张,并提示潜在风险。
请按以下框架分析:
第一步:判断当前交易主导因素。 先区分当前上涨主要来自:
- 基本面改善
- 估值修复
- 主题催化
- 资金抱团
- 纯叙事强化 如果叙事 and 价格强化速度明显快于基本面,就要警惕反身性增强。
第二步:分析市场叙事。 请提炼市场当前围绕该标的 or 题材讲的核心故事是什么。 例如:
- 超级产业趋势
- 渗透率爆发
- 国产替代
- 全球扩张
- 稀缺性龙头 然后判断这些叙事中哪些有依据,哪些已经被夸大。
第三步:评估预期与现实偏离。 重点判断:
- 股价隐含了多高的业绩预期
- 当前业务进展是否足以支撑
- 市场是否提前交易了过长时间维度 偏离越大,反身性越强。
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 · 141 lines · 326 tokens per session scan A 7efe29007930
反身性与泡沫识别 is a skill published in the GitHub repository adambbhe/TDX-finance-mcp-plugin-v3 (35 stars, last pushed 2mo ago), licensed MIT. It adds 326 tokens to every session and 1,947 once invoked, about $0.0016 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
hithink-finance
A routing guide for accessing Chinese A-share financial data, including prices, company reports, valuations, funds, indices, sectors, and local data storage.
hithink-finance-fund
A command-line guide for querying fund information, including profiles, managers, holdings, prices, returns, financial data, news, and exchange-traded fund snapshots. A command-line tool is a program controlled by typed terminal commands.
hithink-finance-data
A local data-management skill for the HiThink Finance command-line tool and its DuckDB database. DuckDB is a database stored in a local file.
hithink-finance-market
A command-line tool entry for retrieving ordinary Chinese A-share market data, including snapshots, historical price bars, trading calendars, adjustment factors, and company actions.
hithink-finance-special-data
A command-line tool entry for retrieving special Chinese market lists and event data, such as limit-up stocks, limit-down stocks, unusual moves, hot stocks, and Dragon-Tiger records.
hithink-finance-futures
A command-line data source for public futures-market information, including contracts, positions, warehouse receipts, basis, trading schedules, and price charts. Futures are agreements to buy or sell an asset at a set future date.