Soccer Predict

Football match betting prediction system. Auto-scrapes data from titan007.com (Asian handicap, over/under, European odds, fundamentals, lineups, corners, hal...

This skill is coherent with its description, but exercise caution before enabling it. Key points to consider: - The skill instructs the agent to open titan007 pages and run JavaScript in the page context to extract tables. That can access page cookies/localStorage or other site-local data — only run this if you trust the skill source and understand the site’s data sensitivity and terms of service. - The SKILL.md tells the agent to persist learned models and match history to files under ~/.claude/projects/*/memory/..., but the registry metadata does not declare these config paths. Confirm where data will be written, review those files, and ensure you are comfortable with persistent storage of scraped data. - Scraping titan007 may violate that site’s terms or local laws; check legal/ToS implications and betting regulations in your jurisdiction. - Because the skill can store and reuse historical predictions, review stored content for sensitive or personally identifying data and consider running the skill in a sandboxed environment (isolated user account or container) if you want to limit exposure. - Avoid providing any unrelated credentials; this skill does not declare needed secrets. If additional env vars or tokens are requested later, treat that as a red flag. If you decide to proceed: start with a short test in concise mode, monitor network activity and created files, and inspect saved memory files before allowing continued autonomous use.

Type: OpenClaw Skill Name: soccer-predict Version: 1.1.0 The 'soccer-predict' skill is a comprehensive sports analytics tool designed to scrape football match data from titan007.com and provide betting recommendations. It utilizes standard OpenClaw capabilities such as 'browser navigate' and 'browser console exec' for data extraction and implements a persistent 'learning' mechanism by saving model weights and match history to local markdown files (e.g., in references/review-framework.md). All identified behaviors, including web scraping and file persistence, are explicitly documented and strictly aligned with the stated purpose of quantitative sports prediction, with no evidence of data exfiltration, malicious execution, or harmful prompt injection.