A comprehensive, real-time financial earnings analysis skill covering global markets. When invoked, performs large-scale web search across multiple markets and compiles a structured 10-module deep-dive report.
This skill transforms raw search results into professional-grade financial analysis. It systematically collects earnings data from A-shares, Hong Kong stocks, US equities, and European markets, then organizes findings into consistent reporting formats with rankings, peer comparisons, and industry trend analysis.
The user explicitly requests any of the following:
Execute parallel WebSearch queries across these axes. Search breadth must be wide enough to capture major earnings releases from the past 3-5 days.
China Markets:
2026年财报 A股 季度报告 最新2026年港股 财报 最新业绩2026年 中概股 财报新能源 财报 消费 财报 科技 财报 医药 财报 金融 财报US Markets:
latest earnings season 2026 resultsS&P 500 earnings reportsMagnificent 7 earnings Q1AAPL MSFT GOOGL AMZN META NVDA TSLA earningsEurope & Other:
European earnings 2026 results日本 欧州 決算 2026For each company found, extract these fields into a structured record:
| Category | Fields |
|---|---|
| ---------- | -------- |
| Identity | Company name (bilingual), ticker, reporting quarter |
| Revenue | Total revenue, YoY%, QoQ%, organic vs M&A breakdown |
| Profitability | Gross profit & margin, Operating profit & margin, Net income & margin, Adj. EPS, EBITDA |
| Segment | Revenue by business line, revenue by geography, segment margin |
| Cash Flow | Operating CF, Free CF, Capex, cash position |
| Guidance | Next quarter revenue guide, full-year guide changes, vs consensus |
| Market Reaction | After-hours / next-day price change, analyst rating changes |
If a field cannot be found, mark as N/A — never fabricate numbers.
Output a structured report organized into the following modules. Use consistent formatting, tables, and clear visual hierarchy.
═══════════════════════════════════════════════════════
DAILY FINANCIAL EARNINGS DEEP-DIVE REPORT
{date} | Coverage: Global Markets
═══════════════════════════════════════════════════════
Per company, structured format:
## {Company} ({Ticker})
├─ Revenue: {X}B CNY (YoY +X%, QoQ +X%)
├─ Net Income: {X}B CNY (YoY +X%)
├─ Gross Margin: X% (YoY +/-Xpp)
├─ EPS: {X} CNY (YoY +X%)
├─ R&D: {X}B CNY (X% of revenue)
├─ Op Cash Flow: {X}B CNY (YoY +X%)
├─ Segment Detail:
│ ├─ {Segment A}: {X}B (+X%)
│ ├─ {Segment B}: {X}B (+X%)
├─ Guidance: {details}
├─ Market Reaction: {price change}
└─ Quick Take: {1-sentence analyst-level assessment}
Cover: A-share tech/semi, consumer, EV, financial, healthcare sector leaders.
Same per-company structure as above. Cover: Tencent, Alibaba, Meituan, JD, NetEase, Xiaomi, etc.
Same per-company structure, with USD/B notation. Cover all Mag-7 plus notable S&P 500 reporters.
Cover: SAP, LVMH, ASML, Roche, Novartis, Shell, etc., with EUR notation.
Build at least 4 of these tables from collected data:
Top 5 by Revenue
Top 5 by Revenue Growth (YoY%)
Top 5 by Net Income
Top 5 by Net Profit Margin
Top 5 by Gross Margin
Top 5 by R&D Spend
Use markdown tables with: | Rank | Company | Metric | Value | YoY |
Categorize every company into three tiers:
🟢 BEAT (Exceeded expectations)
| Company | EPS Surprise | Revenue Surprise | Price Impact |
|---------|-------------|-----------------|-------------|
| ... | +X% | +X% | +X% |
🟡 IN-LINE (Met expectations)
🔴 MISS (Below expectations)
Write 2-3 sentence qualitative analysis per sector represented in the data:
Tech / AI: Capex trends, AI monetization divergence, cloud growth rates
EV / Auto: Price war impact, export growth, margin pressure
Consumer: Premium vs mass divergence, China recovery signals
Financial: NIM trends, wealth management, capital market activity
Healthcare / Biotech: R&D pipeline, policy impact
Industrial: AI infrastructure buildout, backlog growth
Select the most significant companies. For each, produce:
### Deep Dive: {Company}
| Metric | Current Q | Prior Q | YoY Q | QoQ Chg | YoY Chg |
|--------|-----------|---------|-------|---------|---------|
**Strengths:**
- {bullet points}
**Risks:**
- {bullet points}
**Analyst Consensus:**
- Buy/Hold/Sell distribution
- Price target range
- Key ratings changes
📅 Upcoming Earnings (Next 7 Days)
| Date | Company | Market | Key Focus |
|------|---------|--------|-----------|
📅 Key Economic Data
| Date | Indicator | Region | Expected |
|------|-----------|--------|----------|
N/A for unfound data. Never hallucinate financial figures.See examples/report-example.md for a sample output.
See references/markets.md for market-specific conventions.
For publishing to SkillHub (skillhub publish), create registry/skills/daily-financial-report.md:
---
name: daily-financial-report
description: Daily multi-market financial earnings deep-dive report with global coverage, rankings, surprises analysis, and industry trends. Covers A-shares, HK stocks, US Mag-7, and European markets.
version: 2.0.0
author: your-github-username
license: MIT
trigger: /每日财报
platforms:
- claude
- cursor
- windsurf
- codex
- aider
- claw
- gemini
category: finance
tags:
- finance
- earnings
- stocks
- investment
- financial-analysis
- quarterly-earnings
---
# Install via SkillHub CLI
pip install skillhub
skillhub install daily-financial-report
# Or via npx
npx @skill-hub/cli install daily-financial-report
# Or manual: copy daily-financial-report/ to ~/.claude/skills/
npx @openclaw/clawhub install daily-financial-report
Use skill-publisher to publish to all major registries at once:
npx skill-publisher publish ./daily-financial-report \
--clawhub \
--skillhub \
--github
daily-financial-report-skillhub.zipunzip daily-financial-report-skillhub.zip~/.claude/skills/daily-financial-report/共 1 个版本