raven-sourav Skill: Client Showcase Generator
Trigger
"Create client showcase" / "Build portfolio demo" / "Demo for {prospect}" / "Show PMM Brain capabilities"
Process
Step 1: Load context
- Read
data/brain/pmm_brain.json— Brain summary for system proof - Scan
data/output/— Best output examples across formats - Reference Obsidian vault structure at
~/Documents/Knowledge-brain-Obsidian/Knowledge Brain/PMM Brain/
Step 2: Determine showcase type
Based on user request, generate one or more:
A. Pipeline Demo (Full workflow walkthrough)
Walk through a real example end-to-end:
- Input: Theme selection from Brain (show suggest-themes output)
- Research: Evidence sourcing from 13 newsletters, 861 raw posts, 37 mental models
- Generation: 3-angle draft production with format selection
- Critique: Rubber Duck Escalator scoring with real scores
- Distribution: Pillar → micro atomization across 4 formats
- Output: Final content package (LinkedIn + Twitter + Newsletter + Carousel)
B. Case Study (2-3 completed content packages)
For each package:
- Theme: What was written about and why
- Research brief: What evidence and models informed it
- Critique scores: Real Escalator scores showing quality bar
- Final outputs: The actual content across formats
- Results: Engagement metrics if available (optional)
C. Template Package (System architecture — exportable)
Document the system as a replicable blueprint:
- CLAUDE.md pattern: How the orchestrator routes between skills
- Skill structure: How each skill works (trigger → process → output)
- Brain schema: How knowledge is structured (mental models, evidence bank, topic layers, newsletter insights)
- Quality gate: How the Rubber Duck Escalator ensures output quality
- Distribution engine: How pillar content atomizes into platform-native formats
Step 3: Generate showcase artifacts
- Write in professional-but-personal tone (Sourav's voice, not corporate)
- Include real numbers: 13 newsletter sources, 37 mental models, 69 evidence stats, 861 raw posts
- Show before/after examples where possible
- Highlight what makes this system different from generic AI content tools
Step 4: Present to user
Show generated artifacts with clear sections. User can approve, tweak, or request different emphasis.
Output Format
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CLIENT SHOWCASE: [Type]
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[Showcase content organized by type]
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SYSTEM STATS
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Newsletter sources: 13
Raw post notes: 861
Mental models: 37
Evidence bank stats: 69
Content formats: 4 (LinkedIn, Twitter/X, Newsletter, Carousel)
Quality gate: 5-phase Rubber Duck Escalator (threshold: 8+)
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