菜单
Optimize X/Twitter posts for maximum reach using algorithm insights. Use when writing tweets, improving post engagement, or analyzing why posts underperform.
默认使用会先检查来源的 Prompt；你也可以切换为直接命令，或下载本地副本。
决定是否安装前，请先阅读 SKILL.md，以及 SkillsMP 当前展示的配套文件。
用 Codex 或 Claude 帮你安装 复制这段 Prompt，粘贴到 Codex、Claude 或其他助手里，让它检查 Skill 页面并帮你完成安装。
直接命令不会经过审查 Prompt；运行前请先检查来源。
npx skills add https://github.com/guzus/go-viral --skill x-boost命令会保持在同一行。复制前请横向滚动并检查完整内容。
想先保存到本地？可下载 SkillsMP 当前能够提供的文件。
基于 SOC 职业分类
正在显示 SKILL.md
| name | x-boost |
| description | Optimize X/Twitter posts for maximum reach using algorithm insights. Use when writing tweets, improving post engagement, or analyzing why posts underperform. |
Helps craft posts optimized for the X recommendation algorithm based on open-source algorithm analysis.
The algorithm predicts 19 engagement actions and combines them:
Positive signals (boost reach):
Negative signals (kill reach):
When asked to optimize a post or write for X:
The algorithm applies exponential decay to rapid posts from same author:
score = base_score × decay^(post_count)
Recommendation: Space posts 2-4 hours apart for maximum individual reach.
Posts to followers rank higher than discovery posts. Build genuine following over chasing virality.
When reviewing a draft post, check:
Before:
Just launched my new product! Check it out at example.com
After:
I spent 6 months building something I wish existed 3 years ago.
The problem: [specific pain point]
The solution: [what you built]
Here's what surprised me most about the process:
[insight that invites discussion]
What's been your experience with [related topic]?
Why it's better: