x-post-optimizer

X Post Optimizer

Strategic expertise for maximizing content reach on X. It focuses on the "Engagement Velocity" required to pass from candidate sourcing to the top of the "For You" timeline.

Context

The X algorithm utilizes a WeightedScorer that aggregates multiple probability heads (e.g., $P(\text{Like})$, $P(\text{Reply})$). While the HeavyRanker (Phoenix/MaskNet) predicts the likelihood of an action, the Weights determine the final distribution. Understanding these weights is key to "Algorithm-Native" content creation.

For specific tactical data, refer to:

• Engagement Weights
• Reputation & Trust (TweepCred)
• Distribution Logic & Penalties

What it does

• Calculates Expected Value: Estimates the "Score Boost" of different media types (e.g., Video vs. Static Text).
• Optimizes Conversation Depth: Advises on "Author-In-Thread" interactions, which carry massive weight in the WeightedScorer.
• Protects Account Reputation: Identifies "Anti-Signals" (external links, rapid-fire posting) that trigger the VisibilityLib de-amplification.
• Timing Strategy: Leverages knowledge of the "Frequency Deboost" window (3600s) to prevent internal cannibalization of posts.

Guidelines

• The 13.5x Rule: Replies are significantly more valuable than Likes in the modern ranker. Content that invites a meaningful "back-and-forth" creates a feedback loop that the HeavyRanker optimizes for.
• Author Reply Multiplier: In the code, author engagement on their own thread acts as a "Freshness" and "Conversation" signal, often effectively multiplying the thread's reach by keeping it at the top of the retrieval stack.
• Negative Signal Avoidance: Avoid "Engagement Bait" that leads to "Show Less Often" or "Report" actions. The weight for a "Report" (-369.0) is mathematically impossible to overcome with positive engagement.
• Media Strategy: Native video receives a dedicated weight (vqv_weight_eligibility), making it the preferred format for "Out-of-Network" discovery.