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-earnings-previewgit 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-earnings-preview)<a href="https://agentmods.dev/skills/jwangkun/claude-for-financial-services-cn/china-earnings-preview"><img src="https://agentmods.dev/badge/skills/jwangkun/claude-for-financial-services-cn/china-earnings-preview/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-earnings-preview"><img src="https://agentmods.dev/badge/skills/jwangkun/claude-for-financial-services-cn/china-earnings-preview.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 | $0.00108 | $0.02099 |
| Opus 5 | $0.00054 | $0.01050 |
| Sonnet 5 | $0.00022 | $0.00420 |
| Haiku 4.5 | $0.00011 | $0.00210 |
Grade A, and why
china-earnings-preview 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 — 242 lines — stays where its author put it; the contents beside it link to each section on GitHub.
china-earnings-preview
Purpose
Build A股季报/年报前瞻分析, preparing for company earnings releases with scenario frameworks and key metrics to watch.
Data Sources
Primary: iFind MCP (Tier-1 付费) / AkShare MCP (Tier-2 免费备选)
get_quote(ticker) → Current valuation, PE/PB
get_historical_data(ticker) → Trading context, 52-wk range
get_financials(ticker, "income", "annual") → Historical revenue/EPS trends
# News (china-news MCP — separate server)
get_stock_news(ticker="{{TICKER}}") → Pre-earnings context
get_industry_stocks(industry="...") → Peer trading multiples
Consensus Estimates Sources
| Source | Access | Notes |
|---|---|---|
| Wind 一致预期 | Institutional | Most comprehensive |
| Choice 一致预期 | Institutional | Alternative |
| 慧博投研 | Web / API | Good coverage |
| 同花顺 iFinD | Web / API | Retail-friendly UI |
| 东方财富 | Web | Free, some coverage |
| 巨潮 业绩预告 | Regulatory | Mandatory disclosures |
If consensus unavailable, derive from:
- Historical growth rates
- Management guidance from prior calls
- Industry benchmarks
Secondary Sources
- 公司公告 (earnings preview notices 业绩预告)
- 行业研究报告 (sector reports)
- 卖方研报 (broker research summaries)
Workflow
Step 1: Establish Baseline
Historical performance (last 4-8 quarters):
| Quarter | Revenue (亿) | YoY | Net Income (亿) | YoY | EPS (元) | Net Margin |
|---|---|---|---|---|---|---|
| Q1 2024 | ||||||
| Q2 2024 | ||||||
| Q3 2024 | ||||||
| Q4 2023 |
Identify trends:
- Accelerating or decelerating growth?
- Margin expansion or compression?
- Seasonal patterns?
- One-time items to normalize?
Step 2: Gather Consensus Estimates
Consensus table:
| Metric | Q1 2024 Estimate | Range (Low-High) | # Analysts |
|---|---|---|---|
| Revenue (亿) | |||
| YoY Growth | |||
| Net Income (亿) | |||
| EPS (元) | |||
| Gross Margin | |||
| Net Margin |
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 · 242 lines · 108 tokens per session scan A 8e6bc84844fe
china-earnings-preview 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 108 tokens to every session and 2,099 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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