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-client-reportgit 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-client-report)<a href="https://agentmods.dev/skills/jwangkun/claude-for-financial-services-cn/china-client-report"><img src="https://agentmods.dev/badge/skills/jwangkun/claude-for-financial-services-cn/china-client-report/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-client-report"><img src="https://agentmods.dev/badge/skills/jwangkun/claude-for-financial-services-cn/china-client-report.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 | $0.00078 | $0.01451 |
| Opus 5.5 | $0.00031 | $0.00580 |
| Sonnet 5.5 | $0.00016 | $0.00290 |
| Haiku 4.5 | $0.00008 | $0.00145 |
Grade A, and why
china-client-report 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.
This is a copy
89% identical to bilibili-helper — 247 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
How it starts
The opening of the file, as written. The whole thing — 206 lines — stays where its author put it; the contents beside it link to each section on GitHub.
china-client-report
Purpose
Create professional A股财富管理客户报告 — performance reports for Chinese wealth management clients.
Data Sources
Primary: iFind MCP (Tier-1 付费) / AkShare MCP (Tier-2 免费备选)
get_index_data("000001") → 上证指数 benchmark
get_index_data("399006") → 创业板指 benchmark
get_index_data("000300") → 沪深300 benchmark
get_quote(ticker) → Individual security performance
get_fund_data(fund_code) → Fund performance
Secondary Sources
- 基金公司 — fund data
- Wind / Choice — comprehensive market data
- 晨星中国 — fund ratings
Workflow
Step 1: Portfolio Snapshot
Client portfolio summary:
| Metric | Value | Change |
|---|---|---|
| Total AUM (总资产) | ¥XX.X万 | ±X% |
| Market value | ¥XX.X万 | ±X% |
| Cash position | ¥XX.X万 | |
| YTD return | X.XX% | |
| Since inception | X.XX% (annualized) | |
| Benchmark (沪深300) | X.XX% |
Step 2: Performance Attribution
Performance by asset class:
| Asset Class | Allocation | Market Value | Period Return | Contribution |
|---|---|---|---|---|
| A股股票 | XX% | ¥XX | X.XX% | X.XX% |
| 基金 | XX% | ¥XX | X.XX% | X.XX% |
| 债券 | XX% | ¥XX | X.XX% | X.XX% |
| 现金/理财 | XX% | ¥XX | X.XX% | X.XX% |
| Total | 100% | X.XX% |
Performance by sector:
| Sector | Allocation | Return | Contribution |
|---|---|---|---|
| 消费 | XX% | X.XX% | X.XX% |
| 科技 | XX% | X.XX% | X.XX% |
| 医药 | XX% | X.XX% | X.XX% |
| 金融 | XX% | X.XX% | X.XX% |
| 新能源 | XX% | X.XX% | X.XX% |
| 其他 | XX% | X.XX% | X.XX% |
Step 3: Holdings Review
Top positions:
| Security | Ticker | Allocation | Market Value | Period Return | vs Benchmark |
|---|---|---|---|---|---|
Positions with significant changes:
- New positions added
- Positions sold
- Significant gainers (>20%)
- Significant losers (>15%)
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 · 206 lines · 78 tokens per session scan A 5243d9f84631
china-client-report is a skill published in the GitHub repository jwangkun/claude-for-financial-services-cn (848 stars, last pushed 1mo ago), licensed Apache-2.0. It adds 78 tokens to every session and 1,451 once invoked, about $0.0003 per session on Opus 5.5. A static security scan graded it A with 0 findings. It is 89% identical to bilibili-helper, differing in 247 lines, and is treated as a copy.
Other skills, from other repositories
dcf-model
Build discounted cash flow valuation workbooks in Excel.
comps-analysis
Build comparable-company valuation workbooks in Excel.
tear-sheet
Generate professional company tear sheets using S&P Capital IQ data via the Kensho LLM-ready API MCP server. Use this skill whenever the user asks for a tear sheet, company one-pager, company profile, fact sheet, company snapshot, or company overview document — especially when they mention a specific company name or…
investor-materials
Create and update pitch decks, one-pagers, investor memos, accelerator applications, financial models, and fundraising materials. Use when the user needs investor-facing documents, projections, use-of-funds tables, milestone plans, or materials that must stay internally consistent across multiple fundraising assets.
lbo-model
This skill should be used when completing LBO (Leveraged Buyout) model templates in Excel for private equity transactions, deal materials, or investment committee presentations. The skill fills in formulas, validates calculations, and ensures professional formatting standards that adapt to any template structure.
pitch-deck
Populates investment banking pitch deck templates with data from source files. Use when: user provides a PowerPoint template to fill in, user has source data (Excel/CSV) to populate into slides, user mentions populating or filling a pitch deck template, or user needs to transfer data into existing slide layouts. Not…