Content Studio

Content Studio is ArgoBox’s unified content creation interface. It combines a word processor, AI content generation, real-time voice authenticity scoring, RAG-powered fact checking, and multi-platform preview into a single 3-column workspace.

URL: /admin/content-studio

Architecture

┌──────────┬─────────────────────────────┬──────────────┐
│ SOURCES  │         EDITOR              │  ANALYSIS    │
│          │                             │              │
│ RAG      │  Write │ Markdown │ AI Gen  │  Voice Ring  │
│ Search   │                             │  Fact Check  │
│ Context  │  [Editor Body]              │  Preview     │
│ Queue    │                             │  Actions     │
│ Existing │  chars • words • status     │              │
└──────────┴─────────────────────────────┴──────────────┘

3-Column Layout

Source Panel (left, 280px)

RAG search across Knowledge (103K chunks), Private (304K), Vaults (294K)
Expandable results with full text and “Use” button
Context Queue — selected RAG results injected into AI generation
Existing content browser (all posts + journals, filterable)

Editor (center)

Write tab — Contenteditable rich text editor with toolbar (bold, italic, code, H1-H3, lists, quote, undo/redo) and keyboard shortcuts (Ctrl+B, Ctrl+I)
Markdown tab — Raw markdown textarea with sync to rich text
AI Generate tab — Topic/transcript → AI content generation with streaming
Metadata bar: title, description (SEO), date, tags
Real-time character and word count

Analysis Panel (right, 300px)

Voice authenticity ring (SVG circular gauge, 0-100)
4-metric breakdown with color-coded bars
Flagged sentences with fix suggestions
RAG fact checking with relevance scores
Platform preview (Blog, Journal, LinkedIn, Reddit)
Save Draft / Publish buttons

AI Content Generation

The AI Generate tab streams content via /api/admin/content-gen:

User enters topic, transcript, command output, or daily summary prompt
RAG context from Context Queue is injected automatically
System searches RAG for related existing content (avoids duplication)
Voice profile + verified facts + denied claims assembled into system prompt
Content streams from selected model (Gemini Flash/Pro, Claude Sonnet/Opus)
User clicks “Accept” → content loads into editor for review and editing

Input Modes

Mode	Use Case	What AI Does
Topic	Blog post about a subject	RAG search for fresh angle, avoid repeating existing posts
Transcript	Paste a session log or conversation	Extract narrative arc, commands, errors, breakthroughs
Command	Paste terminal output	Wrap in narrative context with voice personality
Daily	End-of-day journal	Synthesize git commits, session notes, RAG results

Voice Authenticity Scoring

Endpoint: POST /api/argonaut/voice-score

Scores content against Daniel’s verified voice patterns (extracted from 2,577 conversations, 9.6M words).

Scoring Algorithm (4 weighted metrics)

Metric	Weight	Target	How It’s Measured
Sentence Length	20%	13.2 words avg	`100 - abs(avgLen - 13.2) * 10`
Banned Patterns	35%	0 found	-15 points per AI phrase detected
First Person	20%	80%+ “I/my”	Ratio of I/me/my vs we/our/us
Casual Tone	25%	60%+ casual	Fragments + contractions vs semicolons + passive

Banned Patterns (15+)

Phrases that AI uses but Daniel doesn’t:

“Let me explain”, “Here is the code”, “I’ll help you”
“As an AI”, “I apologize”, “It’s important to note”
“In conclusion”, “Successfully”, “Utilize”, “Leverage”
“Implement a solution”, “Based on the above”, “Moving forward”
Green checkmarks, numbered “Lessons Learned” lists

Each detected pattern shows the specific line, text, and a suggestion for what to write instead.

RAG Fact Checking

Endpoint: GET /api/argonaut/search?q=<keywords>&limit=5

Extracts proper nouns, years, and technical terms from content, then searches the RAG knowledge base for related context. Shows:

Matching knowledge chunks with text preview
Relevance scores (0-100%)
Source collection (docs, blog, conversation-archive, etc.)

Loading Existing Content

Clicking any post or journal entry in the Source Panel loads it via GET /api/admin/content-body?type=post&slug=xxx:

Populates title, description, tags, date
Loads full markdown body into editor
Switches to Write tab

Platform Preview

Shows how content will render on different platforms:

Blog — Full heading, narrative text, argobox.com URL
Journal — Purple badge, italic mood, timestamp feel
LinkedIn — Truncated text, hashtags (#infrastructure #homelab #devops)
Reddit — r/homelab subreddit style, casual formatting

Data Flow

User Input (topic/transcript)
    ↓
[Content Studio UI]
    ↓ POST /api/admin/content-gen
[RAG Search] → top 5 related chunks (minScore: 0.25)
    ↓
[Voice Profile Build] → identity rules + hardware facts + voice patterns
    ↓
[Facts Injection] → verified facts + denied claims guardrails
    ↓
[System Prompt Assembly] → template + voice + facts + RAG + instructions
    ↓
[LLM Streaming] → SSE response (provider-routed: Anthropic/Google/OpenRouter)
    ↓
[Content Studio] → streams into AI Generate tab
    ↓
[Accept] → loads into Write tab for editing
    ↓
[Voice Check + Fact Check] → real-time analysis
    ↓
[Publish] → writes to src/content/posts/ or src/content/journal/

Design System

Theme: Dark (#060a14 base) with glass morphism panels
Accents: Cyan (#06b6d4) for interactive elements, purple (#8b5cf6) for AI/generation
Fonts: Orbitron for labels/headers, Inter for body, Fira Code for data/mono
Effects: Animated grid background, scan-line during generation, glow on hover
Responsive: Collapses to single column on mobile (<1024px)

Key Files

File	Purpose
`src/pages/admin/content-studio.astro`	Main UI (1400+ lines)
`src/config/admin-nav.ts`	Nav entry (Content group, featured+AI badge)
`src/pages/api/admin/content-gen.ts`	Streaming content generation
`src/pages/api/admin/content-body.ts`	Load existing content by slug
`src/pages/api/argonaut/voice-score.ts`	Voice authenticity scoring
`src/pages/api/argonaut/search.ts`	RAG search
`src/lib/voice-engine.ts`	`scoreVoiceAuthenticity()` algorithm
`src/lib/voice-profile.ts`	System prompt builder with voice rules
`src/lib/facts-loader.ts`	Verified facts + denied claims
`src/lib/myvoice-client.ts`	MyVoice Studio API client

MyVoice Studio — Voice profile authoring and training
RAG Pipeline — How content gets indexed for search
Content Generation — Content-gen API details