vexjoy-agent: VexJoy AI Agent with Jev Intelligent Routing - /do routes plain-English requests to the right specialist agent

by notque · Claude Skill · ★ 448

Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h

Featured in: TypeSafe Jev

How to install vexjoy-agent

git clone https://github.com/notque/vexjoy-agent.git ~/vexjoy-agent

Taken from the project's README on GitHub.

Security audit verdict: SAFE · quality 68/100

None of the 42 rules matched — no credential harvesting, no data exfiltration, no curl-pipe-shell installer. Scanned against 42 published rules built on the SlowMist agent-security taxonomy, refreshed every 8 hours.

The quality score combines nine heuristic checks of the repo and its README: completeness, clarity, specificity, examples, structure, agent readiness, step-by-step content, instruction quality and security notes. It rates how well the project explains itself to an agent, not the code.

aiai-agentsai-pipelinesai-skillsai-workflowsclaudeclaude-aiclaude-codeclaude-code-skillclaude-skills

Quick Facts

Stars448
Forks51
LanguagePython
CategoryClaude Skill
LicenseMIT
Quality Score68/100
Last Updated2026-11-06
Created2026-03-18
Platformsclaude-code, codex, python
Est. Tokens~17k

About vexjoy-agent

VexJoy Agent VexJoy Agent is a complete agent-driven workflow system for Claude Code, Codex, Gemini CLI, and Factory. It gives all four CLIs domain-specific expertise, step-by-step workflows, and automated quality gates. The result is your coding agent working like a team of Go, Python, Kubernetes, review, and content specialists instead of one generalist.

Compatible Skills

These tools work well together with vexjoy-agent for enhanced workflows:

  • devops-claude-skills — semantic(0.26)+complementary+same_lang+similar_pop+shared_platform (59%)
  • claude-skills — semantic(0.40)+complementary+same_lang+similar_pop+shared_platform (59%)
  • bria-skill — semantic(0.25)+complementary+same_lang+similar_pop+shared_platform (59%)
  • openclaw-config — semantic(0.25)+complementary+rare_topics+same_lang+similar_pop+shared_platform (58%)
  • fieldflow — semantic(0.22)+complementary+same_lang+similar_pop+shared_platform (58%)

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How this security grade is produced

Grades come from a rule-based scan built on the SlowMist agent-security taxonomy: 42 published rules, covering credential harvesting, data exfiltration, curl | sh installers and more. 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:

View on GitHub → Browse Claude Skill tools