flyreq-image-studio: AI生图工作台、视频工作台。支持 Agent 与工作台模式、无限画布、素材管理、提示词反推/广场及 PWA，支持外链式配置

by doudou770 · Agent Tool · ★ 152

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

How to install flyreq-image-studio

git clone https://github.com/doudou770/flyreq-image-studio.git

Taken from the project's README on GitHub. Check the security audit before running it.

Security audit verdict: SAFE · quality 61/100

Flagged: sudo usage. 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.

agentaiai-agentsflyreqgpt-image-2grokgrok-imagineimage-generationimage-generation-aiinfinite-canvas

Quick Facts

Stars152
Forks30
LanguageTypeScript
CategoryAgent Tool
LicenseAGPL-3.0
Quality Score61/100
Open Issues2
Last Updated2026-09-25
Created2026-06-30
Platformsnode
Est. Tokens~20k

About flyreq-image-studio

FlyReq Image Studio 简体中文 | English 自托管的 AI 生图工作台 · 视频工作台 · 多模型协议 · 无限画布 · 素材库 · PWA 📖 简介 FlyReq Image Studio（简称 FlyReq Image）是一个面向个人与团队的 AI 图片和视频创作工作台。前端使用 Next.js 16 + React 19 静态导出（PWA），后端是轻量 Node.js 服务（ + SQLite + WebSocket），统一调度任务并代理图片与视频生成 API。 核心亮点： 多模型接入：图片、视频、文本模型独立配置，兼容 Google、OpenAI、xAI 和 New API 能力自适应：按模型能力显示分辨率、参考素材、时长、画幅和高级参数 图像视频一体化：支持文生图、图生图、GIF、视频生成和无限画布创作...

Compatible Skills

These tools work well together with flyreq-image-studio for enhanced workflows:

  • gpt-image-2-skill — semantic(0.44)+complementary+shared_fw(openai,react)+rare_topics+same_lang+similar_pop+shared_platform (86%)
  • mcp-image — semantic(0.50)+complementary+shared_fw(openai)+rare_topics+same_lang+similar_pop+shared_platform (80%)
  • opencode-gpt-imagegen — semantic(0.43)+complementary+shared_fw(openai)+rare_topics+same_lang+similar_pop+shared_platform (78%)

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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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