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 CloudAI-X · Claude Skill · ★ 1.4k
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
🔒 Is claude-workflow-v2 safe to install? View the security audit →
project-starter A universal Claude Code workflow plugin with specialized agents, skills, hooks, and output styles for any software project. Compatible with skills.sh — works with Claude Code, Cursor, Codex, and 35+ AI agents. Quick Start Option 1: skills.sh (Recommended — Any Agent) Installs skills to Claude Code, Cursor, Codex, Windsurf, Cline, and 35+ other AI agents automatically. Option 2: npx (Claude Code — Full Plugin) Installs the complete plugin: agents, commands, skills, and hooks. Option 3: CLI (Per-Session) Option 4: Agent SDK
| Stars | 1,407 |
| Forks | 189 |
| Language | Python |
| Category | Claude Skill |
| License | MIT |
| Quality Score | 76.2698011939252/100 |
| Open Issues | 12 |
| Last Updated | 2026-08-25 |
| Created | 2026-01-01 |
| Platforms | claude-code, codex, python |
| Est. Tokens | ~18k |
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claude-workflow-v2 is Universal Claude Code workflow plugin with agents, skills, hooks, and commands. It is categorized as a Claude Skill with 1.4k GitHub stars.
claude-workflow-v2 is primarily written in Python. It covers topics such as agent-skills, ai, ai-agents.
You can find installation instructions and usage details in the claude-workflow-v2 GitHub repository at github.com/CloudAI-X/claude-workflow-v2. The project has 1.4k stars and 189 forks, indicating an active community.
claude-workflow-v2 is released under the MIT license, making it free to use and modify according to the license terms.
The top alternatives to claude-workflow-v2 on Agent Skills Hub include ai-workflow, agentsys, cursor-talk-to-figma-mcp. 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: