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-wxd-jjgit 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-wxd-jj)<a href="https://agentmods.dev/skills/adambbhe/tdx-finance-mcp-plugin-v3/tdx-wxd-jj"><img src="https://agentmods.dev/badge/skills/adambbhe/tdx-finance-mcp-plugin-v3/tdx-wxd-jj/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-wxd-jj"><img src="https://agentmods.dev/badge/skills/adambbhe/tdx-finance-mcp-plugin-v3/tdx-wxd-jj.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 | $0.00070 | $0.02499 |
| Opus 5 | $0.00035 | $0.01249 |
| Sonnet 5 | $0.00014 | $0.00500 |
| Haiku 4.5 | $0.00007 | $0.00250 |
Grade A, and why
问小达选基金 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 — 254 lines — stays where its author put it; the contents beside it link to each section on GitHub.
问小达选基金 使用指南
技能概述
本技能提供公募基金智能筛选能力，帮助用户快速找到符合特定条件的基金。通过自然语言查询，支持多种筛选维度的组合。
核心功能
支持的筛选维度
| 维度 | 说明 | 示例 |
|---|---|---|
| 基金类型 | 按股票型、债券型、混合型、货币型等筛选 | 股票型基金、债券型基金、QDII |
| 业绩筛选 | 按收益率、回撤、夏普比率等筛选 | 近一年收益率前10、最大回撤小于5% |
| 基金经理 | 按基金经理查询 | 某某经理管理的基金 |
| 风险指标 | 按波动率、最大回撤等筛选 | 低波动率基金、风险控制能力强的基金 |
| 持仓分析 | 按重仓股、行业配置等筛选 | 重仓白酒的基金、科技配置比例高的基金 |
| 资产配置 | 按股票仓位、债券仓位等筛选 | 股票仓位高于80%、均衡配置 |
| 多条件组合 | 多个条件组合筛选 | 股票型且近一年收益前10 |
数据来源
- 主要数据源: 通达信问小达 (tdx_screener)
- 辅助数据源: 通达信行情数据、资讯数据
使用流程
步骤 1: 接收用户查询
接收用户的自然语言基金筛选请求，分析用户意图和筛选条件。
用户输入示例:
- "近一年收益率前10的股票型基金"
- "某经理管理的基金"
- "低风险且收益稳定的债券基金"
步骤 2: Query 改写与标准化
将用户的口语化表达改写为标准的金融查询语句。
改写规则:
- 保留核心意图（基金类型、收益率、基金经理等）
- 将口语转为标准术语（"给我选一个基金" → "基金有哪些"）
- 适当简化复杂条件
- 保持原意不变
标准化示例:
| 用户输入 | 标准化 Query |
|---|---|
| 帮我选个收益好的股票型基金 | 近一年收益率前10的股票型基金 |
| 某经理管的基金 | 某某经理管理的基金 |
| 不想亏太多的债券基金 | 低风险的债券基金 |
步骤 3: 调用数据接口
使用 tdx_screener 工具查询基金数据：
tdx_screener message="<标准化的Query>" rang="JJ"
参数说明:
message: 标准化后的查询语句rang: 市场范围，基金查询使用 "JJ"
步骤 4: 数据扩展决策（可选）
根据数据完整性决定是否需要补充信息：
数据完整: 直接格式化返回结果
需要扩展背景信息:
- 调用
tdx_api_data(entry="tdxf10_gg_rdtc", fixedTag="sjcd")获取基金相关资讯 - 调用
tdx_api_data(entry="tdxf10_gg_ybpj", fixedTag="yzyq")获取基金研报观点 - 调用
tdx_quotes获取实时行情数据
步骤 5: 格式化输出
组织语言回答用户，确保结果清晰易懂。
输出格式要求:
- 使用表格展示基金列表（代码、名称、收益率、规模等）
- 说明数据来源
- 如果改写了问句，需说明最终使用的查询条件
数据返回格式
基础表格字段
| 字段 | 说明 |
|---|---|
| 基金代码 | 基金的唯一标识代码 |
| 基金名称 | 基金的全称 |
| 基金类型 | 股票型、债券型、混合型等 |
| 单位净值 | 基金的单位净值 |
| 累计净值 | 基金的累计净值 |
| 近一年收益 | 近一年的收益率 |
| 基金经理 | 基金经理姓名 |
| 基金规模 | 基金的管理规模 |
| 成立日期 | 基金成立时间 |
输出示例
近一年收益率前10的股票型基金（数据来源于通达信问小达）：
| 排名 | 基金代码 | 基金名称 | 基金类型 | 近一年收益 | 基金规模 |
|------|----------|----------|----------|-----------|----------|
| 1 | 110011 | 易方达中小盘混合 | 混合型 | 35.62% | 150.3亿 |
| 2 | 000001 | 华夏成长混合 | 混合型 | 34.28% | 128.7亿 |
| 3 | ...
注意事项
重要提示
- 数据来源标注: 所有引用通达信数据的地方，必须强调数据来源于通达信问小达
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 · 254 lines · 70 tokens per session scan A 433164f1201d
问小达选基金 is a skill published in the GitHub repository adambbhe/TDX-finance-mcp-plugin-v3 (35 stars, last pushed 2mo ago), licensed MIT. It adds 70 tokens to every session and 2,499 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.
Other skills, from other repositories
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hithink-finance-fund
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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.