These are React (Remotion) components for creating animated visualizations of prompt engineering and RAG concepts. They are reference implementations for building educational content -- not rendered in CLI or chat interfaces.
From coding-interview-agentnpx claudepluginhub preplabsai/interviewmentor --plugin coding-interview-agentManages AI Agent Skills on prompts.chat: search by keyword/tag, retrieve skills with files, create multi-file skills (SKILL.md required), add/update/remove files for Claude Code.
Manages AI prompt library on prompts.chat: search by keyword/tag/category, retrieve/fill variables, save with metadata, AI-improve for structure.
Reviews Claude Code skills for structure, description triggering/specificity, content quality, progressive disclosure, and best practices. Provides targeted improvements. Trigger proactively after skill creation/modification.
These are React (Remotion) components for creating animated visualizations of prompt engineering and RAG concepts. They are reference implementations for building educational content -- not rendered in CLI or chat interfaces.
To use these, set up a Remotion project: https://www.remotion.dev/
// Remotion component: RAGPipelineDemo.tsx
import { useCurrentFrame, useVideoConfig } from 'remotion';
export const RAGPipelineDemo = () => {
const frame = useCurrentFrame();
const { fps } = useVideoConfig();
// Animation phases: each pipeline stage appears in sequence
// 0-30: Query Processing
// 30-60: Retrieval
// 60-90: Context Assembly
// 90-120: Generation
// 120-150: Post-Processing
const stages = [
{ label: 'Query Processing', detail: 'Rewrite, classify, embed', color: '#3498db', start: 0, icon: 'Q' },
{ label: 'Retrieval', detail: 'Vector + keyword search, rerank', color: '#e67e22', start: 30, icon: 'R' },
{ label: 'Context Assembly', detail: 'Select top-N, order, fit token budget', color: '#2ecc71', start: 60, icon: 'C' },
{ label: 'Generation', detail: 'System prompt + context + query -> LLM', color: '#9b59b6', start: 90, icon: 'G' },
{ label: 'Post-Processing', detail: 'Verify citations, detect hallucinations', color: '#e74c3c', start: 120, icon: 'P' },
];
return (
<div style={{ width: 700, height: 500, background: '#0a0a0a', color: 'white', fontFamily: 'sans-serif', padding: 30, position: 'relative' }}>
<h2 style={{ textAlign: 'center', marginBottom: 30, color: '#ecf0f1' }}>
RAG Pipeline Architecture
</h2>
{stages.map((stage, i) => {
const progress = Math.min(1, Math.max(0, (frame - stage.start) / 20));
const isActive = frame >= stage.start && (i === stages.length - 1 || frame < stages[i + 1].start);
return (
<div key={stage.label} style={{
display: 'flex', alignItems: 'center', gap: 16, marginBottom: 14,
opacity: progress,
transform: `translateX(${(1 - progress) * 40}px)`,
}}>
<div style={{
width: 44, height: 44, borderRadius: '50%',
background: isActive ? stage.color : '#333',
display: 'flex', alignItems: 'center', justifyContent: 'center',
fontSize: 18, fontWeight: 'bold', flexShrink: 0,
}}>
{stage.icon}
</div>
<div>
<div style={{ fontSize: 16, fontWeight: 'bold', color: stage.color }}>{stage.label}</div>
<div style={{ fontSize: 13, color: '#888', marginTop: 2 }}>{stage.detail}</div>
</div>
</div>
);
})}
{frame > 130 && (
<div style={{
position: 'absolute', bottom: 30, left: 30, right: 30,
padding: 14, background: '#1a1a2e', borderRadius: 8,
borderLeft: '4px solid #e74c3c', fontSize: 13, color: '#ccc'
}}>
Key insight: RAG quality is bottlenecked by retrieval, not generation. Fix retrieval first.
</div>
)}
</div>
);
};