Generate \"ideal promise vs cruel reality\" visual comparisons by analyzing image content across any domain.
Works with
Automatically detects image domain (architecture, portrait, product, food, travel, gaming, fitness, home, tech) and current state (deteriorated, ideal, or normal)
Outputs three modes: idealized rendering, realistic everyday appearance, or side-by-side comparison with automatic layout (left-right or top-bottom based on aspect ratio)
Applies five universal contrast dimensions ac
AI-first code editor with Composer
Before installing skills in Cursor, ensure your development environment meets these requirements:
node --versionanti-renderExecute the skills CLI command in your project's root directory to begin installation:
Fetches anti-render from lionad-morotar/anti-render-skill and configures it for Cursor.
The CLI shows a list of agents. Use arrow keys and space to select Cursor:
Confirm successful installation by checking the skill directory location:
Restart Cursor to activate anti-render. Access via /anti-render in your agent's command palette.
We perform automated surface-level scans (Gen AI Scanner, Socket, Snyk) during installation. These checks detect common vulnerabilities but do not guarantee complete security. Always review skill source code and verify the publisher's reputation before production use.
Skills execute code in your environment. Always review source, verify the publisher, and test in isolation before production.
Submit your Claude Code skill and start earning
Create detailed user stories, acceptance criteria, and feature specs
Example
Generate user stories for 'password reset feature' with acceptance criteria, edge cases, and test scenarios
Reduce spec writing time by 50%, ensure comprehensive coverage
Research competitors, compare features, identify gaps
Example
Analyze 5 competitor products, create feature comparison matrix, suggest differentiation opportunities
Complete competitive research in 2 hours instead of 2 days
Evaluate features using frameworks (RICE, ICE, Kano) and create prioritized backlogs
Example
Score 20 feature ideas using RICE framework, generate prioritized roadmap with rationale
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通过并置(juxtaposition)手法，揭示任何领域中"承诺与交付之间巨大落差"的普遍困境。左侧呈现理想化的完美渲染，右侧揭示真实的日常面貌。
$domain，计算图片宽高比为 $ratioworks well with skills: image-to-prompt, prompt-to-image
用户上传图片后，分析其当前状态：
| 状态 | 特征 | 输出目标 |
|---|---|---|
| 破败 | 质量问题、使用痕迹、维护不良 | 生成理想化渲染图（即 step 2.1） |
| 理想 | 用户上传了营销图片、广告图片等精修后照片 | 生成轻微破败渲染图片（即 step 2.2） |
| 普通/正常 | 无明显破损、日常使用状态 | 生成理想化渲染和轻微破败的对比图（即 step 2.3） |
如状态模糊，无法判断意图，主动询问用户期望方向
2.1 理想化渲染 (Ideal)
2.2 真实面貌 (Reality)
2.3 对比图 (Comparison)
基于图像内容关键词匹配：
建筑领域: 建筑外观、城市景观、室内空间、建筑效果图、楼盘、住宅、商业空间
人像领域: 人像写真、Cosplay、自拍、证件照、活动拍摄、肖像
产品领域: 电商产品、商品展示、包装设计、电子产品、服饰
食物领域: 美食摄影、菜品展示、烘焙、饮品、餐厅菜单
旅游领域: 风景照、景点打卡、酒店房间、度假胜地
游戏领域: 游戏截图、游戏宣传、UI界面、角色设计
健身领域: 健身照、运动场景、瑜伽、健身房
家居领域: 室内装修、家具展示、样板间、智能家居
科技领域: 产品发布会、概念设计、VR/AR、智能汽车
所有领域共享以下五个核心对比维度：
| 理想侧 | 现实侧 |
|---|---|
| 精心计算的完美光照 | 自然/现场实际光线 |
| 黄金时刻或柔和补光 | 硬光、顶光或平淡漫射光 |
| 明暗层次丰富、无死黑/过曝 | 曝光妥协、阴影浓重 |
| 方向性明确、立体感强 | 低对比度、缺乏层次 |
| 理想侧 | 现实侧 |
|---|---|
| 完美无瑕的表面 | 真实使用痕迹 |
| 色彩饱和、质感强化 | 褪色、污渍、磨损 |
| 无灰尘、无水痕、无瑕疵 | 自然老化、环境痕迹 |
| CG般的精确反射/折射 | 混浊、不完美的反射 |
| 理想侧 | 现实侧 |
|---|---|
| 高饱和度、鲜艳夺目 | 低饱和度、略显平淡 |
| 色温精准、统一协调 | 色温偏移、白平衡未校正 |
| 后期精修的色彩增强 | 相机原生色彩还原 |
| 广告级别的视觉吸引力 | 日常感、朴素感 |
| 理想侧 | 现实侧 |
|---|---|
| 充满活力、生机勃勃 | 冷清、平凡或略显尴尬 |
| 精心布置的场景元素 | 杂乱的现场环境 |
| 梦幻、理想化的背景 | 真实、暴露现场的环境 |
| 情绪饱满、引人入胜 | 纪实感、冷峻客观 |
| 理想侧 | 现实侧 |
|---|---|
| 完美的透视与比例 | 自然的镜头畸变 |
| 瑕疵移除、穿帮修复 | 保留所有现场细节 |
| 精心安排的元素布局 | 随机、不规则的真实分布 |
| 后期添加的特效/光效 | 无后期加持的原始状态 |
如生成对比图，需根据原图宽高比 $ratio 判断新的排列规则：
Make data-driven prioritization decisions faster
Draft PRDs, status updates, and stakeholder presentations
Example
Create executive summary of Q3 roadmap, monthly progress report, feature launch announcement
Save 3-5 hours/week on communication overhead
Prerequisites
Time Estimate
30-60 minutes to see productivity improvements
Steps
Common Pitfalls
✓ Do
✗ Don't
💡 Pro Tips
✓ Use when
Use for user story writing, competitive research, roadmap prioritization, stakeholder communication, and PRD drafting. Best for reducing repetitive documentation and research work.
✗ Avoid when
Avoid for strategic product vision (requires deep customer empathy), pricing decisions (needs market and financial expertise), or when face-to-face customer discovery is more valuable than speed.
mattpocock/skills
parcadei/continuous-claude-v3
cursor/plugins
ailabs-393/ai-labs-claude-skills
pproenca/dot-skills
mattpocock/skills
anti-render is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.
Keeps context tight: anti-render is the kind of skill you can hand to a new teammate without a long onboarding doc.
Solid pick for teams standardizing on skills: anti-render is focused, and the summary matches what you get after install.
Solid pick for teams standardizing on skills: anti-render is focused, and the summary matches what you get after install.
We added anti-render from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.
Keeps context tight: anti-render is the kind of skill you can hand to a new teammate without a long onboarding doc.
anti-render fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.
We added anti-render from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.
anti-render is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.
We added anti-render from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.
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