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-initiating-coveragegit 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-initiating-coverage)<a href="https://agentmods.dev/skills/jwangkun/claude-for-financial-services-cn/china-initiating-coverage"><img src="https://agentmods.dev/badge/skills/jwangkun/claude-for-financial-services-cn/china-initiating-coverage/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-initiating-coverage"><img src="https://agentmods.dev/badge/skills/jwangkun/claude-for-financial-services-cn/china-initiating-coverage.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 | $0.00100 | $0.02113 |
| Opus 5.5 | $0.00040 | $0.00845 |
| Sonnet 5.5 | $0.00020 | $0.00423 |
| Haiku 4.5 | $0.00010 | $0.00211 |
Grade A, and why
china-initiating-coverage 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 1mo 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 — 272 lines — stays where its author put it; the contents beside it link to each section on GitHub.
china-initiating-coverage
Purpose
Create institutional-quality A股首次覆盖研究报告, following Chinese sell-side research standards.
Data Sources
Primary: iFind MCP (Tier-1 付费) / AkShare MCP (Tier-2 免费备选)
get_stock_info(ticker) → Company profile
get_quote(ticker) → Current valuation
get_historical_data(ticker) → Trading history
get_financials(ticker, "income") → Historical P&L
get_financials(ticker, "balance") → Historical BS
get_financials(ticker, "cashflow") → Historical CF
get_industry_stocks(industry="...") → Peer companies
Secondary Sources
- 巨潮资讯 — official filings (annual reports, prospectus)
- 上交所 / 深交所 — listing documents, announcements
- 公司官网 — investor relations, presentations
- 慧博 / Wind / Choice — consensus estimates
- 券商研报 — existing analyst coverage (if any)
- 行业协会 — industry data
Workflow
Task 1: Company Research
Company overview:
- Business description (主营业务)
- History and development (发展历程)
- Ownership structure (股权结构)
- Management team (管理层)
- Shareholder composition (股东构成)
Business segments:
| Segment | Revenue % | Margin | Growth Driver |
|---|---|---|---|
Key questions to answer:
- What does the company do? How does it make money?
- What is its competitive advantage? (护城河)
- What are the key growth drivers?
- What are the main risks?
- Who are the comparable companies?
Task 2: Financial Modeling
Build a financial model (refer to china-3-statement-model skill):
Historical analysis (3-5 years):
| Metric | 2020 | 2021 | 2022 | 2023 | 2024E | 2025E | 2026E |
|---|---|---|---|---|---|---|---|
| Revenue (亿) | |||||||
| YoY Growth | |||||||
| Gross Margin | |||||||
| Operating Margin | |||||||
| Net Margin | |||||||
| ROE | |||||||
| Net Debt/EBITDA |
Key modeling considerations (see china-3-statement-model):
- CAS accounting standards
- 25% tax rate (or 15% for 高新技术企业)
- 千元 vs 元 unit normalization
- 增值税 treatment
- 商誉 flagging
- R&D expense treatment
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.
- 1mo ago First seen · 272 lines · 100 tokens per session scan A 99aad7cc18e2
china-initiating-coverage is a skill published in the GitHub repository jwangkun/claude-for-financial-services-cn (844 stars, last pushed 1mo ago), licensed Apache-2.0. It adds 100 tokens to every session and 2,113 once invoked, about $0.0004 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 2026-08-30.
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