According to AlphaMoat, as of 2026-09, Fund Advisor has 2,634 downloads and 3 stars — ranked #3,993 of 5,078 AI skills overall, and #335 of 465 in Professional.
| Platform | Installs | Downloads | Stars | Comments |
|---|---|---|---|---|
| ClawHub ↗ | 59 | 2.0K | 2 | - |
| SkillHub ↗ | 262 | 2.6K | 3 | — |
Platforms count differently and update at different times.
Capabilities: (1) holdings management — import off-exchange fund holdings exported via the fund E-account from Alipay, JD Finance, Tencent Wealth, Xueqiu, Qieman and all other platforms (Excel converted to CSV); imported data overwrites and saves to the local database (default $HOME/.fund-advisor, file fund_portfolio_v1.db, customizable via FUND_ADVISOR_DATA_PATH); (2) five qieman-mcp modules — financial data (NAV history/holdings detail/risk metrics), research services (screening/diagnosis/backtest/correlation/risk assessment), advisory services (asset allocation/planning/risk matching), advisory content (news interpretation/hot topics/manager views/financial news), and general services (trading days/chart rendering/PDF generation); (3) fund-cli.sh commands (init, import-csv/import-excel, sync --all, group by investment type/account/manager/distributor, query by condition, detail); (4) investment consulting via mcporter call to qieman-mcp directly (batch fund lookup, holdings look-through, correlation, backtesting, asset allocation plans, Monte Carlo simulation, fund search and performance comparison, diagnosis, market thermometer, hot topics, financial news). Key constraints: all analysis and conclusions must be based on the user's imported holdings data and the latest real-time data from qieman-mcp; other data sources can introduce investment risk, so never provide subjective data or analytical conclusions. Notes: MCP queries at most 10 funds per call; NAV and holdings data are delayed — check the NAV date; CSV supports utf-8/utf-8-sig/gbk/gb18030 encodings.
Profile published 2026-10-27
Generated from the skill’s documentation as examples; not results of actual runs.
The counting method changed in 2026-09: skills with the same name are now counted separately by author, and the full catalog is covered. Dashed lines show months before the change; they are not compared with later months, and no growth is computed across the change.
| Month | Downloads | MoM | Stars |
|---|---|---|---|
| 2026-09 | 2.6K | — | 3 |
| 2026-08 | 2.2K | +7.0% | 3 |
| 2026-07 | 2.1K | +14.4% | 3 |
| 2026-06 | 1.8K | +11.1% | 3 |
| 2026-05 | 1.6K | — | 3 |
| 2026-03 | 1.2K | — | 2 |
The author’s original file, shown as plain text without edits or review by AlphaMoat. Links are not clickable; check commands before running them. Fetched 2026-10-23.
---
name: fund-advisor
description: 基金投资顾问技能。提供个人基金持仓统一管理功能,支持所有平台持仓导入、分析、查询;提供基金基础数据、持仓明细、持仓穿透等基于数据查询;提供投资组合分析、投资规划、组合回测服务;提供财经资讯、热点新闻、财经新闻查询;提供基金搜索、公告查询等服务。当用户咨询技能已经覆盖的问题时,优先激活此技能。
metadata: {"clawdbot":{"emoji":"💰","requires":{"bins":["bash","mcporter","python","pip"],"env":["QIEMAN_API_KEY","FUND_ADVISOR_DATA_PATH"]}}}
compatibility: 依赖 mcporter CLI 和 qieman-mcp MCP 服务
---
# 基金顾投 Skill (fund-advisor)
提供个人基金持仓统一管理功能,支持所有平台持仓导入、分析、查询;提供基金基础数据、持仓明细、持仓穿透等基于数据查询;提供投资组合分析、投资规划、组合回测服务;提供财经资讯、热点新闻、财经新闻查询;提供基金搜索、公告查询等服务。
‼️重要:你所有的分析过程和结论必须基于用户导入的持仓数据和qieman-mcp服务器工具获取最新的实时数据。
‼️重要:你引用的其他来源数据可能会给用户带来投资风险,请一定要使用可靠的、准确的、即时的数据,不要提供任何主观的数据和分析结论。
## 能力范围
1. 管理用户的基金持仓数据,用户可以通过基金E账户导出所有持仓数据(包括:支付宝、京东金融、腾讯理财、雪球基金、且慢等所有平台的场外基金持仓数据),导入数据时会创建数据库文件存储用户导入的数据,后续可以配合qieman-mcp的数据查询能力进行持仓数据的综合分析。数据目录可通过 `FUND_ADVISOR_DATA_PATH` 环境变量配置,默认为 `$HOME/.fund-advisor`,数据库文件名为 `fund_portfolio_v1.db`。
2. 本技能整合qieman-mcp的五大核心能力模块:
| 模块 | 能力说明 |
| ------ | ---------- |
| 金融数据 | 基金基础信息、净值历史、持仓明细、风险指标、业绩表现等 |
| 投研服务 | 基金筛选、基金诊断、回测分析、相关性分析、风险评估等 |
| 投顾服务 | 资产配置方案、投资规划、风险匹配、财务分析等 |
| 投顾内容 | 实时资讯解读、热点话题、基金经理观点、财经新闻等 |
| 通用服务 | 交易日查询、图表渲染、PDF生成、时间查询等 |
完整工具清单见 [references/mcp-tools-full.md](references/mcp-tools-full.md)
## 核心功能
### 1. 持仓管理
导入用户的持仓数据,后续进行数据分析使用。
数据获取和导入方法:通过基金E账户导出Excel,转换成csv文件后发生给你的Agent。
```bash
# 初始化环境(检查 mcporter 和 qieman-mcp 配置)
bash scripts/fund-cli.sh init
# 导入 CSV 持仓文件,导入的数据会覆盖保存到本地数据库
bash scripts/fund-cli.sh import-csv tools/data/holdings.csv
# 导入 Excel 持仓文件,导入的数据会覆盖保存到本地数据库
bash scripts/fund-cli.sh import-excel tools/data/holdings.xlsx
# 同步所有数据到本地(基础信息 + 持仓详情)
bash scripts/fund-cli.sh sync --all
```
### 2. 持仓分析
```bash
# 按列分组统计
bash scripts/fund-cli.sh group -c invest_type # 按投资类型分组
bash scripts/fund-cli.sh group -c fund_account # 按基金账户分组
bash scripts/fund-cli.sh group -c trade_account # 按交易账户分组
bash scripts/fund-cli.sh group -c fund_manager # 按基金管理人分组
bash scripts/fund-cli.sh group -c sales_agency # 按销售机构分组
# 按条件查询持仓明细
bash scripts/fund-cli.sh query -c fund_manager -v "易方达" # 查询易方达管理的基金
bash scripts/fund-cli.sh query -c invest_type -v "股票型" # 查询股票型基金
bash scripts/fund-cli.sh query -c fund_name -v "红利" # 查询名称包含红利的基金
# 查看基金详情
bash scripts/fund-cli.sh detail 004137
```
### 3. 基金投资咨询
直接通过 MCP 服务查询任意基金信息,无需本地数据库:
```bash
# 批量查询多只基金
mcporter call qieman-mcp.BatchGetFundsDetail --args '{"fundCodes":["004137","000001","110022"]}' --output json
# 查询基金持仓明细
mcporter call qieman-mcp.BatchGetFundsHolding --args '{"fundCodes":["004137"]}' --output json
```
详细工具参考文档 [references/mcp-tools-full.md](references/mcp-tools-full.md)
## 数据模型
- FundHolding - 用户持仓
- FundInfo - 基金信息
详见 [references/reference.md](references/reference.md)
## 导入格式
csv示例文件见 [assets/sample.csv](assets/sample.csv)
- Excel格式和csv格式相同,只是文件扩展名不同
详细规范见 [references/csv-format.md](references/csv-format.md)
## 使用示例
### 示例1:查询基金信息
用户:"帮我查一下易方达蓝筹精选的信息"
执行:
```bash
mcporter call qieman-mcp.BatchGetFundsDetail --args '{"fundCodes":["005827"]}' --output json
```
### 示例2:导入新持仓
用户:"我有个CSV文件要导入"
执行:
```bash
bash scripts/fund-cli.sh import-csv /path/to/holdings.csv
```
### 示例3:同步最新数据
用户:"更新一下基金数据"
执行:
```bash
bash scripts/fund-cli.sh sync --all
```
## 注意事项
1. **环境要求**:需要先运行 `init` 命令确保 mcporter 和 qieman-mcp 配置正确
2. **批量限制**:MCP 服务单次最多查询 10 只基金
3. **数据时效**:基金净值和持仓数据有延迟,注意查看净值日期
4. **CSV 编码**:支持 utf-8, utf-8-sig, gbk, gb18030 编码
5. **目录结构**:工程代码位于 `tools/` 目录下
## 高级功能场景
### 场景1:投资组合诊断分析
用户持有基金组合,需要诊断分析:
```bash
# 1. 查询基金信息
mcporter call qieman-mcp.BatchGetFundsDetail \
--args '{"fundCodes":["005094","320007","001003","040046"]}' \
--output json
# 2. 基金相关性分析
mcporter call qieman-mcp.GetFundsCorrelation \
--args '{"fundCodes":["005094","320007","001003","040046"]}' \
--output json
# 3. 组合回测分析
mcporter call qieman-mcp.GetFundsBackTest \
--args '{"fundCodes":["005094","320007","001003","040046"],"weights":[0.47,0.23,0.17,0.13]}' \
--output json
```
### 场景2:资产配置方案规划
用户希望制定投资方案:
```bash
# 1. 获取资产配置方案
mcporter call qieman-mcp.GetAssetAllocationPlan \
--args '{"expectedAnnualReturn":0.08}' \
--output json
# 2. 蒙特卡洛模拟
mcporter call qieman-mcp.MonteCarloSimulate \
--args '{"weights":[0.3,0.3,0.2,0.2],"years":3}' \
--output json
```
### 场景3:基金筛选与对比
用户希望筛选符合特定条件的基金:
```bash
# 1. 基金搜索
mcporter call qieman-mcp.SearchFunds \
--args '{"keyword":"红利","sortBy":"oneYearReturn","limit":10}' \
--output json
# 2. 基金业绩对比
mcporter call qieman-mcp.GetBatchFundPerformance \
--args '{"fundCodes":["005827","000001","110022"]}' \
--output json
# 3. 基金诊断
mcporter call qieman-mcp.GetFundDiagnosis \
--args '{"fundCode":"005827"}' \
--output json
```
### 场景4:市场分析
用户希望了解市场情况:
```bash
# 1. 市场温度计
mcporter call qieman-mcp.GetLatestQuotations \
--args '{"date":"2025-03-01"}' \
--output json
# 2. 热点话题
mcporter call qieman-mcp.SearchHotTopic \
--args '{"limit":10}' \
--output json
# 3. 基金经理观点
mcporter call qieman-mcp.SearchManagerViewpoint \
--args '{"industry":"科技","limit":5}' \
--output json
# 4. 搜索财经资讯
mcporter call qieman-mcp.SearchFinancialNews \
--args '{"keyword":"降息","startDate":"2025-01-01","limit":10}' \
--output json
```
## 环境配置
### 1. 配置环境变量
设置 `QIEMAN_API_KEY` 环境变量:
```bash
# 临时设置(当前终端会话)
export QIEMAN_API_KEY="your-api-key-here"
# 永久设置(添加到 shell 配置文件)
echo 'export QIEMAN_API_KEY="your-api-key-here"' >> ~/.zshrc
source ~/.zshrc
```
获取 API Key:访问 [且慢MCP官网](https://qieman.com/mcp/account) 申请免费 API Key。
可选:设置 `FUND_ADVISOR_DATA_PATH` 环境变量自定义数据目录:
```bash
# 自定义数据目录(默认为 $HOME/.fund-advisor)
export FUND_ADVISOR_DATA_PATH="/path/to/your/data"
```
### 2. 安装 mcporter
```bash
# NPM
npm install -g mcporter
# 或 Homebrew
brew tap steipete/tap
brew install mcporter
```
### 3. 初始化环境
```bash
# 检查并初始化环境(会自动使用环境变量中的 API Key 配置 qieman-mcp)
bash scripts/fund-cli.sh init
```
初始化脚本会:
1. 检查 mcporter 是否已安装
2. 检查 `QIEMAN_API_KEY` 环境变量是否已配置
3. 自动生成 `~/.mcporter/mcporter.json` 配置文件
4. 测试 MCP 服务连接
## 参考文档
- [MCP工具完整清单](references/mcp-tools-full.md)
- [CSV导入格式规范](references/csv-format.md)
- [项目架构说明](references/REFERENCE.md)
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Data month: 2026-09 · Downloads, stars and installs are aggregated monthly from public skill registries (ClawHub, SkillHub). See methodology.