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 Yuuhann1999 · MCP Server · ★ 348
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
🔒 Is agent-storyboard safe to install? View the security audit →
Agent 分镜台 · Agent Storyboard 让 Codex、Claude Code 帮你把视频从想法做到分镜、素材和配音。 一个本地优先的分镜工作台：Agent 负责写和生成，你在一张表里检查、调整、验收。 快速开始 · 工作方式 · 功能 · 环境 · MCP 工具 · 开发 为什么做它 做一条短视频，脚本在文档里，分镜在表格里，图片在生图网页里，配音在另一个工具里，素材散落在文件夹里。每换一个窗口，上下文就丢一次。 Agent 分镜台把这些收进同一张本地分镜表： Agent 直接写入：一句话让 Agent 建好完整项目，不需要控制浏览器。 结果自动回填：Agent 生成的图片、视频和配音，落进对应镜头，不用手动对文件名。 你只做验收：所有自动化结果都在表格里，能一眼看到、直接改。 数据都在本机：项目、脚本和素材保存在你的电脑上。 Agent 生成素材，结果自动回填到对应镜头 🚀 快速开始 需要 Node.js 18 或更高版本，以及 Codex 或 Claude Code 之一。 1. 安装插件
| Stars | 348 |
| Forks | 49 |
| Language | JavaScript |
| Category | MCP Server |
| License | MIT |
| Quality Score | 66.8550750017929/100 |
| Open Issues | 4 |
| Last Updated | 2026-09-30 |
| Created | 2026-06-23 |
| Platforms | claude-code, codex, mcp, node |
| Est. Tokens | ~15k |
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agent-storyboard is 本地优先的 Agent 视频分镜工作台：让 Codex、Claude Code 通过 MCP 写分镜、生成图片/视频素材和配音，并自动回填。Local-first storyboard workbench for AI agents (Codex, Claude Code).. It is categorized as a MCP Server with 348 GitHub stars.
agent-storyboard is primarily written in JavaScript. It covers topics such as agent, ai-video, claude-code.
You can find installation instructions and usage details in the agent-storyboard GitHub repository at github.com/Yuuhann1999/agent-storyboard. The project has 348 stars and 49 forks, indicating an active community.
agent-storyboard is released under the MIT license, making it free to use and modify according to the license terms.
The top alternatives to agent-storyboard on Agent Skills Hub include codexia, vllm-mlx, paperdebugger. 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: