china-idea-generation

china-idea-generation is a skill for Claude Code from jwangkun/claude-for-financial-services-cn. It costs 96 tokens per session (2,448 once invoked), scanned A, original, Apache-2.0.

A research workflow for finding investment ideas among mainland Chinese stocks, also called A-shares. It combines market data, financial figures, themes, and price patterns to identify possible long or short positions.

In plain words
What is it for?
Use it to screen A-shares by factors such as valuation, company size, growth, momentum, industry, investor activity, and financial health. It can support research for both stocks expected to rise and stocks expected to fall.
Why use it?
It reduces the work of searching a large stock market for companies that match chosen investment rules. It also brings several types of evidence together for comparing potential ideas.

Skill for Claude Code

Written for Claude Code: shipped in a Claude Code plugin.

Part of the china-earnings-reviewer plugin — 31 skills, 1 agent shipped together

Good fit Use it to screen A-shares by factors such as valuation, company size, growth, momentum, industry, investor activity, and financial health. It can support research for both stocks expected to rise and stocks expected to fall.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/jwangkun/claude-for-financial-services-cn/china-idea-generation
Install

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.

Any agent
npx skills add jwangkun/claude-for-financial-services-cn --skill china-idea-generation
Clone the repo
git clone --depth 1 https://github.com/jwangkun/claude-for-financial-services-cn

Made for: Claude Code.

Or install china-earnings-reviewer, the plugin that ships this one along with the rest of its 31 skills, 1 agent.

Wrote 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.

agentmods badge for china-idea-generation

README.md
[![agentmods](https://agentmods.dev/badge/skills/jwangkun/claude-for-financial-services-cn/china-idea-generation/github.svg)](https://agentmods.dev/skills/jwangkun/claude-for-financial-services-cn/china-idea-generation)
Your own site
<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.

agentmods 80×15 button for china-idea-generation

Your own site · 80×15
<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>
Per session 96 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 2,448 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe. Third-party audits
  • NVIDIA SkillSpector pass 7 Sept 2026
How audits are shown
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5.1 $0.00096 $0.02448
Opus 5 $0.00048 $0.01224
Sonnet 5 $0.00019 $0.00490
Haiku 4.5 $0.00010 $0.00245

Measured 13d ago against content hash 782af8ce8bac, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-12, from the pricing page.

Security

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 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.

agent-plugins/china-earnings-reviewer/skills/china-idea-generation/SKILL.md · 278 lines

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

Read the full file on GitHub · 278 lines

Changes

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.

  1. 13d ago First seen · 278 lines · 96 tokens per session scan A 782af8ce8bac

Subscribe to this mod's changes

china-idea-generation 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 96 tokens to every session and 2,448 once invoked, about $0.0005 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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