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 huifer · Claude Skill · ★ 920
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
🔒 Is WellAlly-health safe to install? View the security audit →
Claude-Ally-Health - Personal Health Information System A file-based personal health data management system using Claude Code CLI tools for data management. GitHub: https://github.com/huifer/Claude-Ally-Health ⚠️ Disclaimer: This project is NOT affiliated with, endorsed by, or associated with Anthropic or Claude.ai. This is an independent open-source project developed by WellAlly Tech. 📝 Note: This project uses GLM's for image recognition. Project Developer This project is developed and maintained by WellAlly Tech. System Features 📁 Pure file-based storage, no database required
| Stars | 920 |
| Forks | 121 |
| Language | Shell |
| Category | Claude Skill |
| License | MIT |
| Quality Score | 66.8905941328349/100 |
| Open Issues | 7 |
| Last Updated | 2026-07-16 |
| Created | 2025-12-31 |
| Platforms | claude-code, cli |
| Est. Tokens | ~13k |
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WellAlly-health is Ally-Health is an intelligent healthcare assistant that combines Claude AI technology with medical expertise. Through natural language interaction, it helps users record symptoms, manage medications, . It is categorized as a Claude Skill with 920 GitHub stars.
WellAlly-health is primarily written in Shell. It covers topics such as claude, claude-code, health.
You can find installation instructions and usage details in the WellAlly-health GitHub repository at github.com/huifer/WellAlly-health. The project has 920 stars and 121 forks, indicating an active community.
WellAlly-health is released under the MIT license, making it free to use and modify according to the license terms.
The top alternatives to WellAlly-health on Agent Skills Hub include Unity-MCP, linkedin-mcp-server, buildwithclaude. 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: