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China Xlsx Author

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jwangkun
china-xlsx-author

Create professional Excel workbooks for A-share financial analysis. Adapts the original xlsx-author skill for Chinese financial modeling standards, CAS conventions, and A-share formatting. Triggers on "A股Excel模型", "财务模型制作", "create model China", "build model xlsx", "制作模型", or "Excel model [company]".

Overview

Publisherjwangkun
Repositoryclaude-for-financial-services-cn
Skill namechina-xlsx-author
Stars
834
Forks
132
Bundled files
Instructions only
LicenseApache-2.0
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • Self-contained

    Everything the model needs lives in the instructions — no extra files to sync.

  • Open source

    Published by jwangkun on GitHub. Read the source before you install it.

Installation

Install the China Xlsx Author AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
    https://github.com/jwangkun/claude-for-financial-services-cn/tree/main/agent-plugins/china-earnings-reviewer/skills/china-xlsx-author
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/jwangkun/claude-for-financial-services-cn.git /tmp/claude-for-financial-services-cn
mkdir -p .claude/skills
cp -r /tmp/claude-for-financial-services-cn/agent-plugins/china-earnings-reviewer/skills/china-xlsx-author .claude/skills/china-xlsx-author
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable China Xlsx Author in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads China Xlsx Author on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so China Xlsx Author is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

china-xlsx-author

Purpose

Create professional A股财务分析Excel模型 — structured workbooks for Chinese equity analysis.

Data Sources

Primary: iFind MCP (Tier-1 付费) / AkShare MCP (Tier-2 免费备选)

python
get_financials(ticker, "income")     → Income statement data
get_financials(ticker, "balance")    → Balance sheet data
get_financials(ticker, "cashflow")   → Cash flow data
get_quote(ticker)                    → Market data

Secondary Sources

  • 巨潮 — source filings
  • 券商研报 — template references

Workflow

Step 1: Workbook Structure

Standard A-share model structure:

SheetContent
封面 (Cover)Company, date, version, disclaimer
假设 (Assumptions)All model inputs, drivers
利润表 (Income)Historical + forecast P&L
资产负债表 (Balance Sheet)Historical + forecast BS
现金流量表 (Cash Flow)Historical + forecast CF
营运资本 (Working Capital)WC analysis, assumptions
估值 (Valuation)DCF, comps, sensitivity
图表 (Charts)Key visuals
检查 (Checks)Sum checks, balances

Step 2: Formatting Standards

Chinese financial model formatting:

ElementFormat
HeadersBold, background color
InputsBlue font, light blue background
CalculationsBlack font, no background
Hardcodes (to avoid)Red font
Negative numbersRed font or (XXX)
Percentage% format, 1 decimal
Currency¥ or 万元
DatesYYYY-MM-DD or YYYY年MM月

Color coding:

蓝色 = 输入 (Inputs)
黑色 = 公式 (Calculations)
红色 = 警告 (Warnings / hardcodes)
绿色 = 链接 (Links)
灰色 = 标签 (Labels)

Step 3: Income Statement Layout

Standard P&L format (CAS):

ItemFY2021FY2022FY2023FY2024EFY2025E
营业收入
减: 营业成本
= 毛利
毛利率
减: 税金及附加
减: 销售费用
减: 管理费用
减: 研发费用
减: 财务费用
加: 投资收益
加: 公允价值变动
减: 信用减值损失
减: 资产减值损失
加: 资产处置收益
= 营业利润
加: 营业外收入
减: 营业外支出
= 利润总额
减: 所得税费用
= 净利润
其中: 归母净利润
其中: 扣非净利润
EPS (元/股)

Step 4: Balance Sheet Layout

Standard BS format (CAS):

ItemFY2021FY2022FY2023FY2024EFY2025E
资产
货币资金
交易性金融资产
应收票据
应收账款
预付款项
存货
其他流动资产
流动资产合计
长期股权投资
固定资产
在建工程
无形资产
商誉
其他非流动资产
非流动资产合计
资产总计
负债
短期借款
应付票据
应付账款
合同负债
应付职工薪酬
应交税费
其他应付款
流动负债合计
长期借款
应付债券
预计负债
非流动负债合计
负债合计
所有者权益
股本
资本公积
盈余公积
未分配利润
归母股东权益
少数股东权益
所有者权益合计
负债及权益总计

Step 5: Assumptions Sheet

Key assumptions to centralize:

CategoryAssumptionValueSource
Revenue growthFY2024EX%
Revenue growthFY2025EX%
Gross marginFY2024EX%
SG&A % of revenueFY2024EX%
Tax rateEffectiveX%
D&A% of PPEX%
CapEx% of revenueX%
NWC% of revenueX%
Terminal growthX%
WACCX%

Step 6: Valuation Sheet

DCF layout:

ItemValueNotes
Enterprise value¥XX亿
Less: Net debt¥XX亿
Equity value¥XX亿
Shares outstandingXX亿股
Value per share¥XX
Current price¥XX
Upside/(Downside)X%

Football field:

MethodLowMidHigh
P/E
P/B
EV/EBITDA
DCF
Range¥XX¥XX¥XX

Step 7: Checks Sheet

Essential checks:

CheckFormulaTargetResult
BS balancesAssets - L - E0
CF tiesEnding cash - Beg cash - Net CF0
Revenue growth(Rev - Rev_prev) / Rev_prevReasonable
Margin checkGP / RevenueReasonable
Debt scheduleST + LT debt= Total
Retained earningsRE beg + NI - Div= RE end
DepreciationD&A / PPEReasonable

Step 8: Charts & Presentation

Key charts to include:

ChartPurpose
Revenue & profit bridgeHistorical + forecast
Margin trendsGross, operating, net
Valuation multiplesHistorical range
DCF sensitivityTornado chart
Peer comparisonComps scatter plot

China-Specific Excel Conventions

Unit Standards

UnitUsage
元Per-share items
万元Most financial items
亿元Large totals, market cap

Naming Conventions

ItemConvention
Sheet namesShort, Chinese preferred
Cell referencesNamed ranges for key cells
File naming[Ticker][Company][Date]_v[X]

Formula Conventions

ConventionExample
Sheet references'利润表'!B10
Named rangesRevenue, WACC, Shares
Chinese function namesSUM, IF, VLOOKUP

Quality Checks

Before finalizing:

  • All sheets present and linked
  • No hardcodes in calculation cells
  • Historicals cross-checked
  • CAS conventions applied
  • BS balances and CF ties
  • Valuation reasonable
  • Charts update automatically
  • All checks green
  • Documentation complete

Data Source Mode Switch: Set env var IFIND_DATA_SOURCE_MODE to control data source preference.

  • ifind-only (strict): Use iFind only, error if unavailable
  • ifind-fallback (default): iFind preferred, fallback to AkShare
  • akshare-only, wind-only (Wind only), wind-fallback (Wind first, fallback to iFind → AkShare): Skip iFind, use AkShare only

Frequently asked questions

What does the China Xlsx Author AI skill do?

Create professional Excel workbooks for A-share financial analysis. Adapts the original xlsx-author skill for Chinese financial modeling standards, CAS conventions, and A-share formatting. Triggers on "A股Excel模型", "财务模型制作", "create model China", "build model xlsx", "制作模型", or "Excel model [company]".

Why use China Xlsx Author on TypingMind?

Because you install it once and use it with any model. China Xlsx Author is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install China Xlsx Author in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/jwangkun/claude-for-financial-services-cn/tree/main/agent-plugins/china-earnings-reviewer/skills/china-xlsx-author. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use China Xlsx Author?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with China Xlsx Author?

As many as you like. As long as a model supports skills, you can use China Xlsx Author with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the China Xlsx Author AI skill free?

Yes. It is published on GitHub by jwangkun under the Apache-2.0 license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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