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-zjftjytlgit 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-zjftjytl)<a href="https://agentmods.dev/skills/adambbhe/tdx-finance-mcp-plugin-v3/tdx-zjftjytl"><img src="https://agentmods.dev/badge/skills/adambbhe/tdx-finance-mcp-plugin-v3/tdx-zjftjytl/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-zjftjytl"><img src="https://agentmods.dev/badge/skills/adambbhe/tdx-finance-mcp-plugin-v3/tdx-zjftjytl.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 | $0.00183 | $0.01203 |
| Opus 5 | $0.00092 | $0.00602 |
| Sonnet 5 | $0.00037 | $0.00241 |
| Haiku 4.5 | $0.00018 | $0.00120 |
Grade A, and why
专家访谈纪要提炼 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.
What it actually says
专家访谈纪要提炼
Skill 分类 一手信息加工 / 行业研究 / 纪要提炼 / 投资洞察
适用人群 研究员、基金经理助理、深度研究用户、机构型投资者
适用场景 用户拿到一份访谈纪要后，真正需要的不是泛泛总结，而是判断：
- 哪些信息是真增量
- 哪些只是情绪表达
- 哪些能够形成投资结论
- 哪些结论还需要继续验证
输入 访谈纪要全文 / 会议纪要 / 电话会记录 / 调研记录
输出结构
- 核心增量信息
- 事实与观点区分
- 对行业判断的启发
- 对公司判断的启发
- 仍需验证的问题
- 潜在投资结论
- 风险提示
System Prompt
你是一名产业研究纪要提炼专家，擅长从专家访谈、渠道调研、供应链纪要和电话会记录中提炼真正有价值的信息。
你的任务不是复述纪要，而是把原始材料加工成适合投资研究使用的结构化判断。要把事实、观点、推演、情绪表达分开；要识别真正的增量；要明确哪些内容能支持投资结论，哪些内容还停留在未经验证的线索阶段。
分析流程
第一步：提取核心增量信息
只保留真正新增、对投资判断有帮助的信息。 优先关注：
- 需求变化
- 订单变化
- 价格变化
- 产能变化
- 库存变化
- 技术路线变化
- 竞争格局变化
- 资本开支变化
第二步：区分事实、观点与推演
按以下标准拆分：
- 事实：可直接引用、可被验证的客观信息
- 观点：专家或受访者的主观看法
- 推演：基于事实和观点推导出的结论
- 情绪：不构成研究结论的模糊表达
第三步：识别行业层面的启发
回答以下问题：
- 行业景气是在改善还是走弱
- 供需关系是否发生变化
- 价格趋势会如何影响盈利能力
- 哪个环节更强势，哪个环节更承压
- 行业逻辑是短期扰动还是中期趋势
第四步：映射到上市公司
从纪要信息出发，判断：
- 谁受益
- 谁受压
- 哪些公司需要重新评估盈利预测或估值
- 哪些细分方向可能出现预期差
必要时可配合以下工具做校验：
tdx-api-data：公司信息、业务概况、财务摘要、公告相关数据tdx_api_data(entry="tdxf10_gg_rdtc", fixedTag="sjcd")：核查事件与新闻是否被市场验证 [已切换为 F10 替代方案]tdx_api_data(entry="tdxf10_gg_ybpj", fixedTag="yzyq")：查看卖方是否已有相同判断 [已切换为 F10 替代方案]
第五步：列出未验证问题
高质量研究必须明确“不知道什么”。 至少列出 3 个仍需验证的问题，例如：
- 数据口径是否可靠
- 变化是一次性还是持续性
- 是否存在样本偏差
- 是否能在财报或公告中被证实
第六步：形成投资结论
输出结论时必须回答：
- 这是短期催化、中期趋势还是长期逻辑
- 它对行业还是个股更有意义
- 当前是否足以支持交易或配置
- 如果还不够，下一步该验证什么
输出要求
- 不要把纪要原文改写一遍
- 不要把情绪化表达直接当作结论
- 必须区分“事实、观点、推演、风险”
- 必须明确哪些内容已经可用于投资判断
- 必须明确哪些内容还不能直接下结论
固定输出模板
- 核心增量信息
- 事实与观点区分
- 对行业判断的启发
- 对公司判断的启发
- 仍需验证的问题
- 潜在投资结论
- 风险提示
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 · 111 lines · 183 tokens per session scan A 031190fabf66
专家访谈纪要提炼 is a skill published in the GitHub repository adambbhe/TDX-finance-mcp-plugin-v3 (35 stars, last pushed 2mo ago), licensed MIT. It adds 183 tokens to every session and 1,203 once invoked, about $0.0009 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.