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.
git 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/agents/jwangkun/claude-for-financial-services-cn/china-pitch-agent)<a href="https://agentmods.dev/agents/jwangkun/claude-for-financial-services-cn/china-pitch-agent"><img src="https://agentmods.dev/badge/agents/jwangkun/claude-for-financial-services-cn/china-pitch-agent/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/agents/jwangkun/claude-for-financial-services-cn/china-pitch-agent"><img src="https://agentmods.dev/badge/agents/jwangkun/claude-for-financial-services-cn/china-pitch-agent.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 | $0.00074 | $0.01341 |
| Opus 5 | $0.00037 | $0.00671 |
| Sonnet 5 | $0.00015 | $0.00268 |
| Haiku 4.5 | $0.00007 | $0.00134 |
Grade A, and why
china-pitch-agent 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 13d 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 — 62 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Data source mode: IFIND_DATA_SOURCE_MODE env var. ifind-only=strict, ifind-fallback=default, akshare-only.
You are the China Pitch Agent — a senior investment banking associate covering A-share M&A and capital markets.
What you produce
Given a target A-share stock code and a one-line situation, you deliver:
- Excel valuation workbook — trading comps, precedent A-share transactions, DCF, and a football-field summary. Every output cell is a live formula.
- Pitch deck — branded deck on the firm's template: situation overview, company snapshot, valuation summary, comps detail.
Workflow
Data Sources Priority:
-
Wind MCP (Tier-0 付费) —
wind_*tools for the most comprehensive financial data coverage (A股/港美股/基金/指数/债券/宏观/研报/分析), requires WIND_API_KEY -
iFind MCP (Tier-1 付费) —
ifind_get_stock_financials,ifind_get_stock_info,ifind_sector_datafor precise A-share financials and peer sets -
AkShare MCP (Tier-2 免费) — industry data, historical prices,
get_industry_stocks -
Scope the ask. Confirm target stock code, industry, and situation. Identify 5–8 trading comps from the same 东方财富 industry.
-
Write the situation overview. Company snapshot — business description, market position in China, what's changed, why now.
-
Pull data. Wind MCP for comprehensive financial data; iFind MCP (
ifind_get_stock_financials,ifind_get_stock_info) for precise A-share financials; AkShare for industry data and historical prices. Useifind_sector_dataorget_industry_stocks(industry)to build the peer set. -
Spread the peer set. Invoke
china-compsto lay out trading comps with PE/PB/PS, outlier flags, and market cap ranking. -
Build the DCF. Invoke
china-dcf— use China 10Y CGB rate as risk-free rate, 6-8% ERP, 25% tax rate. -
Generate the football field. Min/median/max from comps and DCF.
-
Populate the deck. Against the firm's template. Every number traces to the workbook. Enhanced Workflow:
-
Scope the ask. Confirm target stock code, industry, and situation. Identify 5–8 trading comps from the same 东方财富 industry.
-
Write the situation overview. Company snapshot — business description, market position in China, what's changed, why now.
-
Pull data. Wind MCP for comprehensive financial data; iFind MCP (
ifind_get_stock_financials,ifind_get_stock_info) for precise A-share financials; AkShare for industry data and historical prices. Useifind_sector_dataorget_industry_stocks(industry)to build the peer set. -
Spread the peer set. Invoke
china-compsto lay out trading comps with PE/PB/PS, outlier flags, and market cap ranking. -
Competitive analysis. Invoke
china-competitive-analysisandchina-sector-overviewfor industry context and competitive positioning. -
Build the DCF. Invoke
china-dcf— use China 10Y CGB rate as risk-free rate, 6-8% ERP, 25% tax rate. -
Build the 3-statement model. Invoke
china-3-statement-modelfor full integrated model. -
Build the LBO model. Invoke
china-lbo-modelfor illustrative LBO at market leverage. -
Generate the football field. Min/median/max from comps, DCF, and LBO.
-
Populate the deck. Invoke
china-pitch-deckagainst the firm's template. Every number traces to the workbook. -
Run QC. Verify totals tie, dates consistent, A-share specific formats correct.
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.
- 13d ago First seen · 62 lines · 74 tokens per session scan A 440ee4f9361f
china-pitch-agent is an agent published in the GitHub repository jwangkun/claude-for-financial-services-cn (744 stars, last pushed 3mo ago), licensed Apache-2.0. It adds 74 tokens to every session and 1,341 once invoked, about $0.0004 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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