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 SkeneTechnologies · MCP Server · ★ 121
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
🔒 Is skene safe to install? View the security audit →
Skene reads your codebase and produces a user journey for your product: the lifecycle stages a user moves through, the milestones inside each stage, and the code or database evidence that proves each milestone is real. Quick Start Install and launch the interactive terminal UI: The wizard walks you through provider selection, authentication, and analysis — no configuration needed upfront. <img src="https://github.com/user-attachments/
| Stars | 121 |
| Forks | 13 |
| Language | Go |
| Category | MCP Server |
| License | MIT |
| Quality Score | 71.0181597801091/100 |
| Open Issues | 10 |
| Last Updated | 2026-08-26 |
| Created | 2026-01-07 |
| Platforms | cli, gemini, go, mcp |
| Est. Tokens | ~16k |
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skene is Product-Led Growth (PLG) analysis toolkit that detects tech stacks, plans growth loops and builds the loop iteratively.. It is categorized as a MCP Server with 121 GitHub stars.
skene is primarily written in Go. It covers topics such as ai-tools, anthropic, automation.
You can find installation instructions and usage details in the skene GitHub repository at github.com/SkeneTechnologies/skene. The project has 121 stars and 13 forks, indicating an active community.
skene is released under the MIT license, making it free to use and modify according to the license terms.
The top alternatives to skene on Agent Skills Hub include agentsilex, SimplerLLM, mcp-fusion. 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: