codeguide-starter-fullstack: Boilerplate built for AI coding agents, tools, CLI

by CodeGuide-dev · Claude Skill · ★ 150

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

Security audit verdict: SAFE · quality 77/100

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.

better-authboilerplateclaude-codecursordrizzle-ormnextjsqwen-codeshadcn-uistarter-kit

Quick Facts

Stars150
Forks44
LanguageTypeScript
CategoryClaude Skill
Quality Score77/100
Open Issues11
Last Updated2025-10-20
Created2025-08-26
Platformsclaude-code, cli, node
Est. Tokens~29k

About codeguide-starter-fullstack

Codeguide Starter Fullstack A modern web application starter template built with Next.js 15, featuring authentication, database integration, and dark mode support. Tech Stack Framework: Next.js 15 (App Router with Turbopack) Language: TypeScript Authentication: Better Auth Database: Drizzle ORM with PostgreSQL Styling: Tailwind CSS v4 UI Components: shadcn/ui (New York style) Theme System:...

Compatible Skills

These tools work well together with codeguide-starter-fullstack for enhanced workflows:

  • plate-playground-template — semantic(0.21)+complementary+rare_topics+same_lang+similar_pop+shared_platform (57%)
  • autosteer — semantic(0.19)+complementary+rare_topics+same_lang+similar_pop+shared_platform (56%)
  • gemini-cli-desktop — semantic(0.17)+complementary+rare_topics+same_lang+similar_pop+shared_platform (56%)
  • boilerplate-mcp-server — semantic(0.16)+complementary+rare_topics+same_lang+similar_pop+shared_platform (55%)

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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:

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