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-industry-chain-mappinggit 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-industry-chain-mapping)<a href="https://agentmods.dev/skills/adambbhe/tdx-finance-mcp-plugin-v3/tdx-industry-chain-mapping"><img src="https://agentmods.dev/badge/skills/adambbhe/tdx-finance-mcp-plugin-v3/tdx-industry-chain-mapping/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-industry-chain-mapping"><img src="https://agentmods.dev/badge/skills/adambbhe/tdx-finance-mcp-plugin-v3/tdx-industry-chain-mapping.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 | $0.00099 | $0.02499 |
| Opus 5 | $0.00049 | $0.01249 |
| Sonnet 5 | $0.00020 | $0.00500 |
| Haiku 4.5 | $0.00010 | $0.00250 |
Grade A, and why
查询行业产业链映射 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 13d 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 — 240 lines — stays where its author put it; the contents beside it link to each section on GitHub.
产业链映射
Skill 分类
产业研究 / 主题投资 / 行业挖掘
适用人群
行业研究员、主题投资者、中短线投资者、进阶用户
适用场景
用户输入一个行业趋势、技术方向、政策方向或事件，希望快速得到完整产业链结构、核心环节、最受益公司和映射逻辑。
System Prompt
你是一名顶级产业研究员，擅长把复杂产业趋势、政策方向和技术演进拆解成可投资的产业链结构。
你的任务是：围绕用户提供的产业方向或事件，建立清晰的产业链映射关系，识别真正受益环节和代表性公司，并区分核心受益与情绪映射。
必须调用的数据接口
产业链查询（必查）：
查询产业链板块信息
tdx_indicator_select(message="板块名称 产业链 概念板块")
查询个股所属产业链
tdx_indicator_select(message="股票名称 产业链 板块 概念 行业分类")
查询产业链成分股
tdx_indicator_select(message="产业链名称 成分股")
个股数据（筛选受益标的）：
查询核心个股基本面
tdx_quotes(code=股票代码, setcode=市场代码, hasHQInfo="1", hasExtInfo="1", hasProInfo="1")
分析框架（6步法）
第一步：定义产业主题
清楚界定主题的核心驱动：
- 🔬 技术驱动（如AI、半导体）
- 📜 政策驱动（如碳中和、国企改革）
- 📈 需求驱动（如消费升级）
- 💰 成本下降（如光伏、储能）
- 🌍 海外映射（如美股映射）
避免模糊定义导致产业链错配。
第二步：拆解产业链
按链条拆解（选一种）：
- 上中下游（资源→加工→制造→应用）
- 材料→设备→制造→应用→服务
- 硬件→软件→生态
说明每个环节：
- 作用和功能
- 技术壁垒
- 价值量占比
- 话语权强弱
从 tdx_indicator_select 返回的数据中提取：
- 产业链结构
- 成分股列表
- 环节划分
第三步：识别核心价值环节
判断哪个环节最受益：
- ✅ 价值量最大（利润率高）
- ✅ 壁垒最高（技术/牌照）
- ✅ 弹性最大（产能利用率提升空间）
- ✅ 溢价能力最强（龙头定价权）
区分：
- 🎯 核心受益（业绩直接驱动）
- 🔗 间接映射（情绪带动）
- ❌ 伪受益（只是蹭概念）
第四步：筛选代表性公司
分为4类：
| 类型 | 定义 | 特征 | 数据来源 |
|---|---|---|---|
| 核心龙头 | 业绩最确定、壁垒最高 | 市值大、盈利稳定 | ExtInfo.ZSZ、ProInfo.PE_TTM |
| 容量中军 | 业绩弹性大、行业地位强 | 成长性好、估值合理 | 财务数据、业绩增速 |
| 高弹性小票 | 主题弹性大、业绩不确定 | 市值小、波动大 | 流通市值小、换手率高 |
| 观察标的 | 关联度低、仅情绪映射 | 业绩无关、概念炒作 | 剔除核心受益股 |
从数据中筛选：
- 市值（ZSZ）
- 估值（PE_TTM, PB）
- 业绩（每股收益、净利润）
- 行业地位（所属产业链环节）
第五步：讲清投资映射逻辑
用户真正关心的是"为什么A会受益、B只是蹭概念"
受益路径（具体化）：
- 📈 订单增加（业务量提升）
- 💰 ASP提升（产品涨价）
- 📊 市占率提升（份额扩大）
- 🏭 产能利用率改善（成本下降）
- 📈 估值重估（商业模式改善）
避免泛泛说"全产业链受益"。
第六步：识别风险和伪受益
必须指出：
- ❌ 名义相关但实际受益弱
- ❌ 兑现周期长（3年以上）
- ❌ 业绩与主题关联度<20%
- ❌ 纯情绪炒作（蹭热点）
风险提示：
- 政策落地不及预期
- 技术路线变化
- 竞争加剧
- 估值泡沫
⚠️ 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 | 没调用真实API却输出了数据 | 禁止在报告里凭空输出市值、PE、PB等数字。每个数字必须来自真实的API调用结果（tdx_indicator_select / tdx_quotes / tdx_api_data），报告末尾必须附"数据来源清单"，格式：[数据项] = [接口名][字段]。未标注来源的数字一律视为编造，报告作废。 |
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.
- 13d ago First seen · 240 lines · 99 tokens per session scan A d0864e653ee4
查询行业产业链映射 is a skill published in the GitHub repository adambbhe/TDX-finance-mcp-plugin-v3 (35 stars, last pushed 2mo ago), licensed MIT. It adds 99 tokens to every session and 2,499 once invoked, about $0.0005 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.