full-stack-ai-agent-template: Full-stack AI app generator — FastAPI + Next.js with agents, RAG, streaming, auth, and 20+ integrations out

by vstorm-co · Codex Skill · ★ 1.9k

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

Security audit verdict: SAFE · quality 70/100

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. Full audit →

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.

ai-agentsceleryclawdbotdockerfastapifull-stacklangchainlanggraphllmlogfire

Quick Facts

Stars1,903
Forks375
LanguagePython
CategoryCodex Skill
LicenseMIT
Quality Score70/100
Open Issues15
Last Updated2026-09-16
Created2025-12-19
Platformsdocker, python
Est. Tokens~2306k

About full-stack-ai-agent-template

Full-Stack AI Agent Template Production-ready FastAPI + Next.js project generator with AI agents, RAG, and 20+ enterprise integrations. Quick Start • Features • Demo • Documentation • Configurator • PyPI <img src="https://img.shields.io/badge/c

Compatible Skills

These tools work well together with full-stack-ai-agent-template for enhanced workflows:

  • mengram — semantic(0.16)+complementary+shared_fw(crewai,langchain)+same_lang+similar_pop+shared_platform (72%)
  • AgentChat — semantic(0.17)+complementary+shared_fw(fastapi,langchain)+rare_topics+same_lang+similar_pop+shared_platform (71%)
  • langchain-mcp-adapters — semantic(0.24)+complementary+shared_fw(langchain)+same_lang+similar_pop+shared_platform (61%)

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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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