video-content-strategist

Video Content Strategist Skill

Overview

Production-ready video content strategy toolkit for planning content calendars, analyzing thumbnail effectiveness, and optimizing video metadata for platform SEO. Designed for content creators, marketing teams, and video producers managing consistent video output across YouTube, TikTok, LinkedIn, and other platforms.

Clarify First

Before planning, confirm these inputs. If any is unknown or vague, ASK — do not assume:

• Platform(s) — YouTube, TikTok, LinkedIn, or Instagram — sets optimal video length and SEO approach
• Deliverable — content calendar, thumbnail analysis, or SEO metadata optimization — selects the tool and workflow
• Audience & content pillars — who it's for and the pillar mix/ratios — drives calendar topics and formats
• Posting frequency — videos per week and planning horizon — sets the production schedule

Stop rule: ask only the 2-3 that most change the output. If the user says "just draft it," proceed and list your assumptions at the top of the artifact.

Quick Start

# Plan a video content calendar from topics and audience data
python scripts/video_content_planner.py topics.json --weeks 8 --frequency 3

# Analyze thumbnail text and composition patterns
python scripts/thumbnail_analyzer.py thumbnails.csv

# Optimize video titles, descriptions, and tags for SEO
python scripts/video_seo_optimizer.py video_data.json --platform youtube

Tools Overview

Workflows

Workflow 1: Monthly Video Strategy

1. Define audience personas and content pillars in topics JSON
2. Run video_content_planner.py to generate 4-week calendar
3. For each planned video, run video_seo_optimizer.py for metadata
4. After publishing, collect thumbnail data and run thumbnail_analyzer.py
5. Feed learnings back into next month's planning cycle

Workflow 2: YouTube Channel Optimization

1. Export existing video data (titles, descriptions, tags, performance)
2. Run video_seo_optimizer.py on underperforming videos to identify metadata gaps
3. Run thumbnail_analyzer.py on top vs bottom performers
4. Apply optimizations to existing videos and use patterns for new content

Workflow 3: Multi-Platform Video Strategy

1. Create topics JSON with platform-specific audience data
2. Run video_content_planner.py with --platforms youtube,tiktok,linkedin
3. Get platform-adapted content recommendations
4. Optimize each platform's metadata with video_seo_optimizer.py

Reference Documentation

See references/video-strategy-guide.md for comprehensive frameworks covering:

• Content pillar strategy
• Platform-specific best practices
• Thumbnail design principles
• Video SEO fundamentals
• Production workflow optimization

Common Patterns

Pattern: Topics JSON Format

{
  "channel": "TechStartupTV",
  "audience": {
    "primary": "SaaS founders, 25-45",
    "interests": ["startup growth", "fundraising", "product development"],
    "pain_points": ["scaling teams", "finding product-market fit", "managing burn rate"]
  },
  "content_pillars": [
    {"name": "Founder Stories", "ratio": 0.3, "format": "interview", "avg_length_min": 25},
    {"name": "Tactical Guides", "ratio": 0.4, "format": "tutorial", "avg_length_min": 12},
    {"name": "Industry Analysis", "ratio": 0.2, "format": "commentary", "avg_length_min": 8},
    {"name": "Behind the Scenes", "ratio": 0.1, "format": "vlog", "avg_length_min": 5}
  ],
  "topics": [
    {"title": "How We Hit $1M ARR", "pillar": "Founder Stories", "priority": "high"},
    {"title": "5 Pricing Strategies That Work", "pillar": "Tactical Guides", "priority": "high"},
    {"title": "AI in SaaS: 2026 Trends", "pillar": "Industry Analysis", "priority": "medium"}
  ]
}

Pattern: Thumbnail CSV Format

video_id,title,views,ctr_pct,has_face,has_text,text_words,colors_dominant,emotion
V001,How to Scale,15000,8.2,yes,yes,3,red-yellow,surprise
V002,Tech Review,8500,4.1,no,yes,5,blue-white,neutral

Platform Video Length Guidelines