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 jwangkun/claude-for-financial-services-cn --skill china-dcfgit clone --depth 1 https://github.com/jwangkun/claude-for-financial-services-cnWrote 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/jwangkun/claude-for-financial-services-cn/china-dcf)<a href="https://agentmods.dev/skills/jwangkun/claude-for-financial-services-cn/china-dcf"><img src="https://agentmods.dev/badge/skills/jwangkun/claude-for-financial-services-cn/china-dcf/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/jwangkun/claude-for-financial-services-cn/china-dcf"><img src="https://agentmods.dev/badge/skills/jwangkun/claude-for-financial-services-cn/china-dcf.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00054 | $0.00975 |
| Opus 5 | $0.00027 | $0.00487 |
| Sonnet 5 | $0.00011 | $0.00195 |
| Haiku 4.5 | $0.00005 | $0.00097 |
Grade A, and why
china-dcf 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 — 98 lines — stays where its author put it; the contents beside it link to each section on GitHub.
china-dcf
Data Sources (Multi-Tier)
Tier 0 — 万得 Wind（最全面付费数据）
- 覆盖：A股/港美股/基金/指数/债券/宏观/研报/分析（44个工具）
- MCP 服务：
wind-mcp（需WIND_API_KEY密钥，以ak_开头） - 优势：全市场覆盖面最广、数据最全面、包含研报和量化分析
- 密钥申请：https://aifinmarket.wind.com.cn/#/home
Tier 1 — 同花顺 iFind（付费精确数据）
ifind_get_stock_financials(ticker, ...) -> Historical financials
ifind_get_stock_info(ticker) -> Market data, shares outstanding
ifind_get_risk_indicators(ticker) -> Beta, volatility for WACC
Tier 2 - AkShare (free, open-source, fallback)
get_financials(ticker, "income", "annual") -> Historical P and L
get_financials(ticker, "balance", "annual") -> Historical BS
get_quote(ticker) -> Market cap, price
Data source mode switch: When env var
IFIND_DATA_SOURCE_MODE=ifind-only, use iFind exclusively.
wind-only: Wind only, error if unavailablewind-fallback: Wind first, fallback to iFind → AkShare
Key differences from US-market DCF
| Parameter | US DCF Convention | China DCF Convention |
|---|---|---|
| Risk-free rate | US 10Y Treasury | China 10Y CGB (国债收益率, ~2.5-3.5%) |
| Equity risk premium | ~5-6% (historical US) | ~6-8% (China A-share ERP) |
| Tax rate | US corporate 21% | China corporate 25% (高新技术企业 15%) |
| Terminal growth | US GDP growth (~2%) | China GDP growth (~4-5%) |
| Currency | USD | CNY |
| Reporting standard | US GAAP / IFRS | CAS (中国会计准则) |
Workflow
Step 1: Pull financials
get_financials(ticker, "income", "annual") → last 5 years
get_financials(ticker, "balance", "annual")
get_financials(ticker, "cashflow", "annual")
Step 2: Get market data
get_quote(ticker) → price, market cap, PE, PB
get_index_data("000001") → benchmark return for beta estimation
Step 3: Build projections
- Project revenue using historical growth rates adjusted for China macro outlook
- Assume 65-75% operating margin for 白酒 / high-margin sectors
- Assume 15-25% operating margin for manufacturing
- CapEx as % of revenue: check historical from cashflow statement
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 · 98 lines · 54 tokens per session scan A f8a02ba65fa0
china-dcf is a skill published in the GitHub repository jwangkun/claude-for-financial-services-cn (744 stars, last pushed 3mo ago), licensed Apache-2.0. It adds 54 tokens to every session and 975 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.
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