fund_analysis

fund_analysis is a skill for Claude Code, Codex from coderzzy/agent-fund-analysis-skill. It costs 39 tokens per session (3,127 once invoked), scanned A, original, MIT.

A Chinese-language workflow for analysing mutual funds using data from Eastmoney, a Chinese financial information website. It produces an HTML report with charts, tables, historical return measures, and written analysis.

In plain words
What is it for?
Use it when given a six-digit Chinese fund code to download raw data, analyse net-value trends and returns, examine support and resistance levels, and create a report.
Why use it?
It gathers and organises fund data so the user does not have to manually compare prices, returns, fees, and changes across different time periods. The report puts these results in one view.

Skill for Claude CodeCodex

Written for no agent in particular: nothing here depends on one.

Needs its repository: it runs a file that does not travel with it, so clone the repository first. The line is mkdir -p ./output_fund/{基金代码}/raw.

Good fit Use it when given a six-digit Chinese fund code to download raw data, analyse net-value trends and returns, examine support and resistance levels, and create a report.

Compare 6 skills from other repositories ↓
Install

Getting it into your agent

It runs from inside its repository, so the clone comes first — what it calls does not travel with the file alone.

Clone the repo
git clone --depth 1 https://github.com/coderzzy/agent-fund-analysis-skill
agentmods
npx agentmods add skills/coderzzy/agent-fund-analysis-skill/fund_analysis

Made for: Claude Code, Codex.

Wrote 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.

agentmods badge for fund_analysis

README.md
[![agentmods](https://agentmods.dev/badge/skills/coderzzy/agent-fund-analysis-skill/fund_analysis/github.svg)](https://agentmods.dev/skills/coderzzy/agent-fund-analysis-skill/fund_analysis)
Your own site
<a href="https://agentmods.dev/skills/coderzzy/agent-fund-analysis-skill/fund_analysis"><img src="https://agentmods.dev/badge/skills/coderzzy/agent-fund-analysis-skill/fund_analysis/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.

agentmods 80×15 button for fund_analysis

Your own site · 80×15
<a href="https://agentmods.dev/skills/coderzzy/agent-fund-analysis-skill/fund_analysis"><img src="https://agentmods.dev/badge/skills/coderzzy/agent-fund-analysis-skill/fund_analysis.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 39 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 3,127 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5.1 $0.00039 $0.03127
Opus 5.5 $0.00016 $0.01251
Sonnet 5.5 $0.00008 $0.00625
Haiku 4.5 $0.00004 $0.00313

Measured 2mo ago against content hash 277538dada99, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

Grade A, and why

fund_analysis 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 2mo ago.

The scan reads SKILL.md. This mod also ships 1 executable file (scripts/fund_analyzer.py), listed below but not scanned — reading those needs a real analyzer, not pattern matching.

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.

fund_analysis/SKILL.md · 257 lines

How it starts

The opening of the file, as written. The whole thing — 257 lines — stays where its author put it; the contents beside it link to each section on GitHub.

基金分析 Skill

功能描述

此 skill 用于从天天基金网获取基金历史数据,通过 Python 脚本进行深度数据分析,最终生成包含可视化图表、数据表格和 Agent 解读的 PPT 风格的 HTML 分析报告。

分析维度:

  • 净值走势可视化
  • 多周期净值统计分析(1个月、半年、1年、3年、成立以来)
  • 压力指标分析(支撑/压力位识别)
  • 不同间隔周期涨跌幅分析(1天、3天、1周、1月、半年、1年)
  • 收益反转周期分析
  • 月度收益分布

触发条件

当用户输入以下或类似表达时触发:

  • "帮我分析基金"
  • "分析基金"
  • "基金分析"
  • 包含基金代码(如 012805)

执行流程

Step 1: 创建输出目录

mkdir -p ./output_fund/{基金代码}/raw
mkdir -p ./output_fund/{基金代码}/analysis
mkdir -p ./output_fund/{基金代码}/report

Step 2: 获取基金数据

  1. 从用户输入中提取基金代码(6位数字)
  2. 构建请求 URL:https://fund.eastmoney.com/pingzhongdata/{基金代码}.js?v={时间戳}
    • 时间戳格式:年月日时分秒,如 20260410022145
  3. 发送 HTTP GET 请求获取数据
  4. 将返回的 JS 数据保存到 ./output_fund/{基金代码}/raw/{基金代码}_raw.js

Step 3: 解析数据

返回的 JS 文件包含以下关键变量:

基金基本信息
变量名 说明 示例值
fS_name 基金名称 "广发恒生科技ETF联接(QDII)C"
fS_code 基金代码 "012805"
fund_sourceRate 原费率 "0.00"
fund_Rate 现费率 "0.00"
fund_minsg 最小申购金额 "10"
收益率数据
变量名 说明 示例值
syl_1n 近一年收益率(%) "-4.23"
syl_6y 近6月收益率(%) "-27.71"
syl_3y 近3月收益率(%) "-16.73"
syl_1y 近1月收益率(%) "-3.08"
净值走势数据
变量名 说明 数据格式
Data_netWorthTrend 单位净值走势 [{"x":时间戳,"y":净值,"equityReturn":回报率,"unitMoney":派送金},...]
Data_acWorthTrend 累计净值走势 [[时间戳,累计净值],...]
Data_grandTotal 累计收益率走势 [[时间戳,收益率],...]

Step 4: 数据分析(Python脚本)

使用 Python 脚本进行深度数据分析:

python scripts/fund_analyzer.py \
  --code {基金代码} \
  --input ./output_fund/{基金代码}/raw/{基金代码}_raw.js \
  --output ./output_fund/{基金代码}/report/report_{基金代码}.html \
  --json-output ./output_fund/{基金代码}/analysis/analysis_{基金代码}.json
分析维度
  1. 净值走势可视化

    • 绘制累计净值总体走势曲线
    • 支持鼠标悬停查看具体日期和数值
    • 支持缩放查看不同时间段
  2. 多周期净值统计分析

    周期 说明
    1个月 最近30天的净值统计
    半年 最近180天的净值统计
    1年 最近365天的净值统计
    3年 最近1095天的净值统计
    成立以来 全部历史净值统计

    每个周期计算:

    • 平均值、中位数
    • 最高值、最低值
    • 标准差(波动程度)
    • 统计区间起止日期

Read the full file on GitHub · 257 lines

Files

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.

Changes

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.

  1. 2mo ago First seen · 257 lines · 39 tokens per session scan A 277538dada99

Subscribe to this mod's changes

fund_analysis is a skill published in the GitHub repository coderzzy/agent-fund-analysis-skill (7 stars, last pushed 6mo ago), licensed MIT. It adds 39 tokens to every session and 3,127 once invoked, about $0.0002 per session on Opus 5.5. 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 2026-08-31.

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