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 cxOrz · Agent Tool · ★ 71
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
🔒 Is smart-codebase safe to install? View the security audit →
Smart-Codebase English | 简体中文 Turn your OpenCode into a senior project expert that learns and grows with every task. 🔥 The Pain Point Every time you start a new session, AI starts from scratch. It doesn't remember: Why you chose that architecture? What gotchas exist in your codebase? What patterns your team follows? What you learned from debugging that nasty bug? You explain the same things over and over. ✨ The Solution Smart-Codebase gives your AI permanent memory through SKILL files. It uses an AI agent to autonomously capture knowledge from your conversations and project files. 📖 Table of Contents ⚙️ How It Works 📦 Installation [⚡ Commands](#-comman
| Stars | 71 |
| Forks | 9 |
| Language | TypeScript |
| Category | Agent Tool |
| License | Apache-2.0 |
| Quality Score | 70.1226070571885/100 |
| Last Updated | 2026-03-13 |
| Created | 2026-01-28 |
| Platforms | claude-code, gemini, node |
| Est. Tokens | ~12k |
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smart-codebase is A plugin for OpenCode. Make your coding agent learn and grow with every task.. It is categorized as a Agent Tool with 71 GitHub stars.
smart-codebase is primarily written in TypeScript. It covers topics such as anthropic, chatgpt, claude.
You can find installation instructions and usage details in the smart-codebase GitHub repository at github.com/cxOrz/smart-codebase. The project has 71 stars and 9 forks, indicating an active community.
smart-codebase is released under the Apache-2.0 license, making it free to use and modify according to the license terms.
The top alternatives to smart-codebase on Agent Skills Hub include antigravity-workflows, c4-genai-suite, notion-mcp-server. 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: