guardvibe vs SkillSpector

Security scanning for AI-generated code and agent skills

guardvibe checks AI-generated code and repositories using local rules, dependency intelligence, and MCP or CLI workflows. SkillSpector scans AI agent skills before installation, combining static analysis with optional LLM review; the main difference is codebase security versus skill security.

guardvibeSkillSpector
LanguageTypeScriptPython
LicenseApache-2.0Apache-2.0
Stars620.6k
Forks01.8k
Last analyzedOct 30, 2026Oct 20, 2026

Key differences

  • guardvibe is written in TypeScript and focuses on generated code, whole repositories, prompts, and host configuration; SkillSpector is written in Python and focuses on agent skills before installation.
  • guardvibe uses deterministic local rules and daily CVE intelligence; SkillSpector combines static checks with optional LLM semantic review and OSV.dev dependency lookups.
  • SkillSpector accepts skills from files, directories, Git repositories, URLs, and zip archives, while guardvibe offers repository checks and integrations for coding agents and development workflows.
  • guardvibe supports Claude Code, Cursor, Gemini CLI, Codex, VS Code, and Windsurf; SkillSpector targets Claude Code, Codex, Gemini CLI, and MCP skills.
  • Both use Apache-2.0 and provide MCP support, but SkillSpector has 20.6k stars and 1.8k forks, while guardvibe has 6 stars and 0 forks.
  • guardvibe’s contribution is concentrated heavily in one of its two contributors; SkillSpector has a broader contributor base and ongoing issue and pull-request handling.

Choose guardvibe if you…

  • need checks for AI-generated code, repositories, dependencies, or host configuration.
  • want prompt analysis, cross-file repository checks, or workflows integrated with coding agents such as Cursor or Windsurf.
  • prefer deterministic local rules for supported web stacks and development workflows.
Read the guardvibe analysis →

Choose SkillSpector if you…

  • need to assess third-party agent skills before installing or approving them.
  • want to scan skills from repositories, URLs, zip archives, directories, or individual files.
  • need optional LLM review, risk recommendations, or finding baselines for skill scans.
Read the SkillSpector analysis →

Compare the numbers side by side, or add more projects

This comparison is generated with AI from the OSRepos analyses of both projects. Always check each project's repository and documentation before choosing.