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-idea-generationgit 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-idea-generation)<a href="https://agentmods.dev/skills/jwangkun/claude-for-financial-services-cn/china-idea-generation"><img src="https://agentmods.dev/badge/skills/jwangkun/claude-for-financial-services-cn/china-idea-generation/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-idea-generation"><img src="https://agentmods.dev/badge/skills/jwangkun/claude-for-financial-services-cn/china-idea-generation.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 | $0.00096 | $0.02448 |
| Opus 5.5 | $0.00038 | $0.00979 |
| Sonnet 5.5 | $0.00019 | $0.00490 |
| Haiku 4.5 | $0.00010 | $0.00245 |
Grade A, and why
china-idea-generation 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 — 278 lines — stays where its author put it; the contents beside it link to each section on GitHub.
china-idea-generation
Purpose
Systematically surface new A股投资机会 through quantitative screens, thematic analysis, and pattern recognition.
Data Sources
Primary: iFind MCP (Tier-1 付费) / AkShare MCP (Tier-2 免费备选)
get_market_overview() → Top gainers, losers, most active
get_quote(ticker) → Price, PE, PB, market cap
get_historical_data(ticker) → Price trends, momentum
get_financials(ticker, "income") → Financial metrics
get_financials(ticker, "balance") → Balance sheet health
get_industry_stocks(industry="...") → Peer comparison
Secondary Screening Data
| Data | Source | Use |
|---|---|---|
| 龙虎榜 (Dragon-Tiger list) | 东方财富 | Unusual activity, institutional interest |
| 北向资金 (Northbound flows) | 沪深港通 | Foreign investor sentiment |
| 融资融券 (Margin trading) | 交易所 | Leverage and sentiment |
| 股东人数变化 | 巨潮 | Institutional accumulation/distribution |
| 机构持仓 | 季报/F10 | Fund ownership trends |
| 大宗交易 (Block trades) | 交易所 | Smart money signals |
Workflow
Step 1: Define Screen Criteria
Investment philosophy alignment:
- Value vs Growth vs GARP vs Momentum
- Market cap preference (large / mid / small)
- Sector focus or sector-agnostic
- Liquidity requirements (turnover threshold)
- Risk tolerance (volatility, leverage, earnings stability)
Screen parameters (A-share specific):
| Parameter | Typical Range | Notes |
|---|---|---|
| PE (TTM) | 5-50x | Avoid negative PE |
| PB | 0.5-5x | <1x may indicate distress |
| PS | 0.5-5x | For high-growth unprofitable |
| Market cap | >50亿 | Liquidity threshold |
| Daily turnover | >5000万 | Tradability |
| ROE | >10% | Quality filter |
| Debt/Equity | <100% | Financial health |
| Revenue growth | >10% | Growth filter |
| EPS growth | >15% | Earnings momentum |
Step 2: Quantitative Screens
Screen 1: Deep Value (深度价值)
Filters:
- PE (TTM) < 15x AND PB < 1.5x
- ROE > 10% (past 3 years average)
- Debt/Equity < 80%
- Revenue growth > 0% (not declining)
- Market cap > 30亿
Output: Value candidates with potential mispricing
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 · 278 lines · 96 tokens per session scan A 782af8ce8bac
china-idea-generation 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 96 tokens to every session and 2,448 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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