No red flags found in any of the 11 categories — no credential harvesting, no data exfiltration, no curl-pipe-shell installer. Scanned against the SlowMist agent-security taxonomy, refreshed every 8 hours. Full audit →
by joreilly · MCP Server · ★ 602
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
🔒 Is FantasyPremierLeague safe to install? View the security audit →
Fantasy Premier League Compose Multiplatform project running on following Android iOS Desktop Also includes Kotlin Notebook MCP Server It also currently makes use of the following Jetpack libraries ViewModel Navigation 3 Room DataStore Related posts: Using Realm persistence library in a Kotlin Multiplatform project Using new Swift Async Algorithms package to close the gap on Combine Displaying Charts on iOS, Android, and Desktop using Compose Multiplatform Using Jetpack Room in Kotlin Multiplatform shared code Using Navigation 3 with Compose Multiplatform Screenshots Android iOS Desktop <img width="912" height="888" alt="Screenshot 2025-11-01 at 20 38 24" src="https://github.com/user-attachments/assets/d9cbc228-7d1c-4b2
| Stars | 602 |
| Forks | 63 |
| Language | Jupyter Notebook |
| Category | MCP Server |
| License | Apache-2.0 |
| Quality Score | 56.5206328524135/100 |
| Open Issues | 4 |
| Last Updated | 2026-09-19 |
| Created | 2021-01-23 |
| Platforms | mcp |
| Est. Tokens | ~16k |
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FantasyPremierLeague is Fantasy Premier League Kotlin/Compose Multiplatform sample. It is categorized as a MCP Server with 602 GitHub stars.
FantasyPremierLeague is primarily written in Jupyter Notebook. It covers topics such as android, compose-multiplatform, datastore.
You can find installation instructions and usage details in the FantasyPremierLeague GitHub repository at github.com/joreilly/FantasyPremierLeague. The project has 602 stars and 63 forks, indicating an active community.
FantasyPremierLeague is released under the Apache-2.0 license, making it free to use and modify according to the license terms.
The top alternatives to FantasyPremierLeague on Agent Skills Hub include compose-skill, sceneview, compose-skill. Each offers a different approach to the same problem space — compare them side-by-side by stars, quality score, and community activity.
Grades come from a rule-based scan built on the SlowMist agent-security taxonomy, covering 11 red-flag categories including credential harvesting, data exfiltration, and curl | sh installers. It is a first-layer scan, not a manual audit — we say so rather than overstate it.
The scale of the problem is documented independently: Liu et al. (2026), in a study of 31,132 agent skills, report that 26.1% contain security vulnerabilities. Our own full-catalog census is published as a citable open dataset.
Sources & who's responsible: