x 代码编写
- 作者仓库星标 12
- 许可证 MIT
- 作者仓库 go-viral
X Post Optimizer
Helps craft posts optimized for the X recommendation algorithm based on open-source algorithm analysis.
How the Algorithm Scores Posts
The algorithm predicts 19 engagement actions and combines them:
Positive signals (boost reach):
- Likes, Replies, Retweets, Quotes
- Dwell time (time spent reading)
- Profile clicks, Follows from post
- Shares (DM, copy link)
- Video quality views, Photo expands
Negative signals (kill reach):
- "Not interested" clicks
- Blocks, Mutes, Reports
Instructions
When asked to optimize a post or write for X:
1. Hook First
- Lead with the most compelling point
- Stop the scroll in first 5 words
- Use pattern interrupts
2. Maximize Dwell Time
- Add depth that rewards reading
- Use line breaks for scanability
- Include images/videos that make people pause
3. Encourage Replies
- End with questions
- Make takes that invite discussion
- Leave threads open-ended
4. Avoid Author Penalty
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.
5. Leverage In-Network Advantage
Posts to followers rank higher than discovery posts. Build genuine following over chasing virality.
Quick Checklist
When reviewing a draft post, check:
- Hook in first line?
- Rewards reading (dwell time)?
- Invites replies?
- No spam/repetitive content?
- Authentic voice (not engagement bait)?
- Appropriate timing from last post?
What Doesn't Work
- Engagement pods (artificial patterns detected)
- Keyword stuffing (algorithm learns behavior, not keywords)
- Rapid-fire posting (author diversity penalty)
- Controversial content that triggers blocks/mutes
Example Optimization
Before:
Just launched my new product! Check it out at example.comAfter:
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:
- Hook creates curiosity (dwell time)
- Structure rewards reading
- Ends with question (replies)
- Authentic story (avoids mute/block signals)
- 流狐分类
- 文档
- 作者声明 Agent
- 未找到明确声明；不据此推断已兼容或已测试
- 静态检查
- 94 / 100 · 启发式扫描，不代表运行安全
- 作者 / 版本 / 许可
- @guzus · MIT
- 流狐 Token 估算
- 低消耗
- 流狐接入估算
- 即装即用
- 是否需要外部 API Key
- 未发现要求
- 检测到的系统要求
- 未声明
- 底层运行要求
- 未声明
- 检测到的文件与系统行为
-
- 只读
- 允许写入 / 修改
- 检测到的网络行为
- 仅限本地
- 安装命令数
- 无（仅作为资料）
档案由构建时根据 SKILL.md 与安装命令自动衍生，可能与作者实际意图存在差异。
需要注意： 未限定 allowed-tools，默认拥有全部工具权限。
作者没有在当前 SKILL.md 中定义固定输出样例。The algorithm predicts 19 engagement actions and combines them: Positive signals (boost reach): Likes, Replies, Retweets, Quotes
When asked to optimize a post or write for X:
Lead with the most compelling point Stop the scroll in first 5 words Use pattern interrupts
Add depth that rewards reading Use line breaks for scanability Include images/videos that make people pause
End with questions Make takes that invite discussion Leave threads open-ended
The algorithm applies exponential decay to rapid posts from same author: Recommendation: Space posts 2-4 hours apart for maximum individual reach.
# X Post Optimizer
Helps craft posts optimized for the X recommendation algorithm based on open-source algorithm analysis.
## How the Algorithm Scores Posts
The algorithm predicts **19 engagement actions** and combines them:
**Positive signals (boost reach):**
- Likes, Replies, Retweets, Quotes
- Dwell time (time spent reading)
- Profile clicks, Follows from post
- Shares (DM, copy link)
- Video quality views, Photo expands
**Negative signals (kill reach):**
- "Not interested" clicks
- Blocks, Mutes, Reports
## Instructions
When asked to optimize a post or write for X:
### 1. Hook First
- Lead with the most compelling point
- Stop the scroll in first 5 words
- Use pattern interrupts
### 2. Maximize Dwell Time
- Add depth that rewards reading
- Use line breaks for scanability
- Include images/videos that make people pause
### 3. Encourage Replies
- End with questions
- Make takes that invite discussion
- Leave threads open-ended
### 4. Avoid Author Penalty
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.
### 5. Leverage In-Network Advantage
Posts to followers rank higher than discovery posts. Build genuine following over chasing virality.
## Quick Checklist
When reviewing a draft post, check:
- [ ] Hook in first line?
- [ ] Rewards reading (dwell time)?
- [ ] Invites replies?
- [ ] No spam/repetitive content?
- [ ] Authentic voice (not engagement bait)?
- [ ] Appropriate timing from last post?
## What Doesn't Work
- Engagement pods (artificial patterns detected)
- Keyword stuffing (algorithm learns behavior, not keywords)
- Rapid-fire posting (author diversity penalty)
…作者原文负责流程事实；流狐只索引当前章节、要点、文件与命令。
章节 -> How the Algorithm Scores Posts → Instructions → 1. Hook First → 2. Maximize Dwell Time → 3. Encourage Replies → 4. Avoid Author Penalty
要点 -> 19 engagement actions · Positive signals (boost reach) · Negative signals (kill reach) · Recommendation · Before · After · Why it's better
文件/命令 -> images/videos · spam/repetitive · blocks/mutes · mute/block
内容 SHA-256 -> f1356edcf02a
原文结构
适用与边界
原文中的明确线索
images/videos、spam/repetitive、blocks/mutes、mute/block