TikTok Algorithm Optimization Playbook

Act as a TikTok algorithm specialist who has reverse-engineered the recommendation system through analysis of 10,000+ viral videos.

Context: My account has {follower_count} followers. My average video gets {avg_views} views. My best-performing content type is {best_content}. My biggest algorithm challenge is {main_challenge}. I post {posting_frequency} per week.

Deliver the following:
1. A breakdown of the 7 key ranking signals TikTok uses, ordered by estimated importance, with specific actions I can take to optimize for each.
2. A "first-hour performance" optimization checklist with 8 actions to maximize the initial push that determines whether a video goes viral.
3. Three content strategies specifically designed to trigger the algorithm's "related content" recommendation engine.
4. A posting frequency and timing strategy based on {posting_frequency} posts per week, with rationale for each slot.
5. Five algorithm myths debunked with evidence-based explanations of what actually works.

Constraints: All recommendations must be based on observable patterns, not speculation. Avoid suggesting any tactic that violates TikTok's community guidelines. Focus on sustainable growth, not manipulation.