Skill flagged — suspicious patterns detected

ClawHub Security flagged this skill as suspicious. Review the scan results before using.

Capital Market Report

v2.3.1

Generate high-signal, impact-driven capital market anomaly and rumor reports. Focuses on actionable business signals, expectation-breaking news, and deep log...

1· 611·6 current·7 all-time
byZhe (Phil) Yang@yangzhe1991
Security Scan
VirusTotalVirusTotal
Suspicious
View report →
OpenClawOpenClaw
Suspicious
medium confidence
!
Purpose & Capability
The description and SKILL.md claim a news-scanning + delta-report pipeline, which matches the included scripts. However the runtime instructions and code call other skills' scripts (e.g., stock-analysis hot_scanner.py and tencent-finance-stock-price query_stock.py, cryptoprice script) that are not declared in metadata. That external-skill dependency is not listed in requirements and is disproportionate to the provided manifest.
!
Instruction Scope
SKILL.md instructs the agent to run local scripts and to read the prior report at ~/.openclaw/workspace-group/memory/last_capital_market_report.md and then overwrite that file. The scripts also create and prune a cache under ~/.openclaw/workspace-group/market-monitor and perform broad network fetches. Reading and overwriting a workspace memory file is within the reported function (delta extraction) but is a direct file-write operation to user home and should be noted.
Install Mechanism
There is no install spec (instruction-only), which minimizes installer risk. However the Python scripts include inline dependency declarations (e.g., 'requests', 'google-genai', 'pytz') but no automated install or metadata listing. That mismatch means the runtime may fail or require manual dependency installation.
!
Credentials
The manifest requests no environment variables, but scripts declare a dependency on 'google-genai' (news-processor.py) which typically requires cloud credentials (API key) to be useful. The skill also calls many external web endpoints and other skill scripts. The absence of declared API keys or required credentials is a proportionality/information gap.
Persistence & Privilege
always:false (normal). The skill writes cache files and overwrites its own last report file under ~/.openclaw/workspace-group — it does not request system-wide privileges or modify other skills' configs, but it will maintain state in the user's workspace directory.
What to consider before installing
This skill is a coherent news-scraper + report generator but has several red flags: (1) It invokes other skills' scripts (stock-analysis, tencent-finance-stock-price, cryptoprice) that are not declared—ensure those skills exist and are trusted. (2) news-processor.py lists 'google-genai' as a dependency but the skill does not declare any API key requirement; if you provide Google/other API credentials, be sure you trust the code. (3) The runtime reads and overwrites ~/.openclaw/workspace-group/memory/last_capital_market_report.md and writes cache files—expect persisted state in your home. (4) Several subprocess calls use shell=True and invoke files under ~/.openclaw — if those paths can be modified by other users or packages, this could be abused. Before installing: inspect the full scripts locally, run them in a sandboxed account/environment, verify/fulfill the undeclared dependencies if you intend to use them, and avoid supplying API credentials unless you confirm which keys are needed and why. If you need higher assurance, ask the skill author for a clear dependency list and required environment variables or run the scrapers in a restricted network environment.

Like a lobster shell, security has layers — review code before you run it.

latestvk97er5pmtjj0556w0x06ra3zkx8308d3
611downloads
1stars
12versions
Updated 9h ago
v2.3.1
MIT-0

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**: ...

Comments

Loading comments...