Capital Market Report (High-Signal Anomaly Edition)

Generates forward-looking business deduction reports based on an "Absolute Impact Threshold." This skill abandons traditional macroeconomic index reading (e.g., "Nasdaq down 1%"), shifting instead to deep scraping of domestic and international forums, news, and social media to lock in supply-chain anomalies and earnings explosion points with extreme expectation gaps.

Core Philosophy (Absolute Impact Threshold)

1. Zero Routine Data: No longer reports routine market data like index points or daily percentage changes. Focuses entirely on nuclear-level anomalies in the business world.
2. Dynamic Capacity: Abolishes mechanical rules like "must have 3-5 items." If only 2 events meet the threshold today, report 2; if 8 major global supply-chain-shaking news break, report all 8.
3. Core on Selected Assets, Inclusive of Global Leaders: While deeply scanning specific target assets (e.g., Chinese ADRs, A/HK tech stocks, AI/consumer/EV supply chains), it absolutely must not miss strategic turning points from global tech giants (e.g., the "Magnificent Seven" or core global AI leaders).

Execution Pipeline & Toolchain

Step 1: Launch Underlying Scanners

You must run the following information scraping tools:

1. Chinese Financial Core News Scraper (Scraping domestic sources like Cailianshe, Wall Street CN, Sina Finance):

cd ~/.openclaw/skills/capital-market-report; uv run scripts/news-processor.py --delta --delta

2. Overseas Anomaly & Rumor Radar (Monitoring Reddit WSB, CoinGecko, Yahoo Finance movers, Google News rumors): (Note: Requires the stock-analysis skill to be installed)

uv run ~/.openclaw/skills/stock-analysis/scripts/hot_scanner.py
uv run ~/.openclaw/skills/stock-analysis/scripts/rumor_scanner.py

Step 2: Comprehensive Inclusion of Major Market Events

From the scraped results, retain news based on the following rules:

• Include All High-Attention Events: Any news heavily discussed by the market (e.g., major AI model releases like Claude/GPT updates, big tech earnings, macro data, geopolitical shifts) MUST be included, even if they perfectly meet market expectations. Do not filter out highly focused topics.
• Retain Anomalies: Keep extremely strong earnings reversals, supply-chain-level product delays, or major rumors.
• Red Line: Do not aggressively filter out major news just because it lacks a "shock" factor. If the market cares, it goes in the report.

Step 3: Mandatory Source Tracking (Real URL Verification)

Red Line: Every piece of news reported must include a real source URL [Read Original](URL).

• The URL is natively extracted and provided by the underlying news-processor.py script from the original RSS or HTML feeds.
• Do not invent URLs or use generic domain homepages. Rely on the exact link returned by the scripts.

Step 4: Isolated Deduction & Localization

Perform strict logical deduction on the selected events:

• Market Isolation Red Line: Rigorously distinguish the "country/market" where the anomaly occurred. For example, a surge in US domestic airfares can only be deduced as bullish for US airlines and US OTAs; it absolutely cannot be forcefully applied to Chinese companies like Trip.com.
• If the event is a shock to an overseas giant (e.g., Honda taking a massive loss), the deduction must clarify whether the logical link to its global competitors genuinely holds up.
• Language Localization: Although this skill description is in English, the final report generated MUST be written in the user's primary conversational language (e.g., if the user communicates in Chinese, the report must be in Chinese).

Step 5: Rolling Updates & Delta Extraction (Temporal Event Tracking)

For multi-source concurrency or rolling reports on the same market event, DO NOT simply discard duplicate news items. Instead, apply strict "Delta Extraction" tracking based on time:

• Definition of Delta: "Delta" means new information added since the last generated report (temporal delta), NOT whether the news broke market expectations.
• Baseline Comparison: You MUST read the previous report from ~/.openclaw/workspace-group/memory/last_capital_market_report.md before generating the new report. Use it to compare newly scraped news against the previous report's coverage of the same event.
• Extract Delta (New Information): Specifically pull out any new data, new official statements, or new market reactions that weren't in the previous report.
• Visual Labeling: Use tiered labeling for event tracking updates. For example:
  • 🔴 [增量更新 - 关键细节/市场反应] for news containing substantial new facts since the last report.
  • ⚪ [跟进报道 - 与上次相比无新增] for news that merely repeats facts already covered in the previous report.
• Save State: After generating the new report, you MUST overwrite ~/.openclaw/workspace-group/memory/last_capital_market_report.md with the exact text of the new report so it is available for the next run.

Report Output Format

The output must be minimalist, sharp, and deduction-driven:

📊 **Capital Market Absolute Impact Report | YYYY-MM-DD HH:MM**

⚠️ **Core Anomaly Alerts (Potential Expectation Gaps & Strategic Inflection Points)**

- **[Category/Theme] Core Event Title (Marked with Country/Market)**
  **Source & Link**: News Source Name ([Read Original](Real_Article_URL))
  **Core**: A single sentence highlighting the crux of the anomaly.
  **Rigorous Deduction**: 1-2 sentences pointing out the bullish/bearish impact and specific stock tickers or supply chains. The logic must be airtight.

- **[Category/Theme] Core Event Title (Marked with Country/Market)**
  **Source & Link**: News Source Name ([Read Original](Real_Article_URL))
  **Core**: ...
  **Rigorous Deduction**: ...