Flagged: spawns subprocesses. Scanned against the SlowMist agent-security taxonomy, refreshed every 8 hours. Full audit →
by tam159 · MCP Server · ★ 56
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
🔒 Is next-role safe to install? View the security audit →
NextRole 🚀 ✨ GenAI-Accelerated Career Advancement ✨ Upload your CV + a job description. Get a tailored resume PDF, a researched interview-prep doc, and a day-of battlecard cheat sheet — built by a multi-agent system with long-term memory. What is NextRole? Preparing for an in
| Stars | 56 |
| Forks | 12 |
| Language | Python |
| Category | MCP Server |
| License | MIT |
| Quality Score | 63.7330020480288/100 |
| Open Issues | 7 |
| Last Updated | 2026-09-15 |
| Created | 2026-04-28 |
| Platforms | mcp, python |
| Est. Tokens | ~17k |
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next-role is 🚀 Level up your career with GenAI. 📄 Tailor your CV to any JD, 🔍 automate company research, and 🗓️ generate custom interview prep plans for your next role or internal promotion.. It is categorized as a MCP Server with 56 GitHub stars.
next-role is primarily written in Python. It covers topics such as a2a, ai-agents, ai-long-term-memory.
You can find installation instructions and usage details in the next-role GitHub repository at github.com/tam159/next-role. The project has 56 stars and 12 forks, indicating an active community.
next-role is released under the MIT license, making it free to use and modify according to the license terms.
The top alternatives to next-role on Agent Skills Hub include orchestkit, omnicoreagent, langchain_data_agent. 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: