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 jomeswang · Codex Skill · ★ 57
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
🔒 Is agnes-ai-skill safe to install? View the security audit →
Agnes AI Free Text, Image & Video Generation Skill Agnes AI Skill is a free multimodal Agent Skill for Codex, Claude Code, OpenClaw, Claude Desktop, Hermes, WorkBuddy, Cherry Studio, Opencode, and similar AI agent tools. It helps agents use Agnes 2.0 APIs for text generation, image generation, image editing, text-to-video, image-to-video, and API integration through a single root . Use this Agnes skill when you want an Agnes AI skill, image generation skill, video generation skill, text to image workflow, image to video workflow, free AI API workflow, or free AI model workflow that fits Codex skills, Claude Code skills, and OpenClaw skills. 中文：Agnes AI 免费文本 / 生图 / 图片编辑 / 生视频 Agent Skill，支持 Codex、 Claude Code、OpenClaw、Claude Desktop、Hermes、WorkBuddy、Cherry Studio、 Opencode 等工具。 Quick Start Install the skill with a repository-aware skills installer: Or copy this sentence to your agent: text Please read and install Agnes AI S
| Stars | 57 |
| Forks | 2 |
| Category | Codex Skill |
| License | MIT |
| Quality Score | 66.9390129515997/100 |
| Last Updated | 2026-06-13 |
| Created | 2026-06-01 |
| Platforms | claude-code, codex |
| Est. Tokens | ~19k |
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agnes-ai-skill is Agnes AI skill for text, image, and video APIs with persistent auth and OpenAI-style workflows. It is categorized as a Codex Skill with 57 GitHub stars.
You can find installation instructions and usage details in the agnes-ai-skill GitHub repository at github.com/jomeswang/agnes-ai-skill. The project has 57 stars and 2 forks, indicating an active community.
agnes-ai-skill is released under the MIT license, making it free to use and modify according to the license terms.
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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: