IceCube Content Factory
/install icecube-content-factory
🧊 IceCube Content Factory
Content that captures attention. Automatically.
Most content gets ignored. IceCube Content Factory uses engagement psychology to create content that stops the scroll.
What This Skill Does
1. Hook Generation
Generate 10 different hook styles for any topic:
- Pattern interrupt hooks
- Curiosity gap hooks
- Pain point hooks
- Story hooks
- Controversy hooks
- Social proof hooks
- FOMO hooks
- Counterintuitive hooks
- How-to hooks
- List hooks
2. Thread/Post Structures
- Twitter/X threads (optimal structure)
- LinkedIn posts (professional tone)
- Xiaohongshu notes (visual + emotional)
- Reddit posts (authentic + value)
- Blog intros (SEO + engagement)
3. Engagement Optimization
- Optimal posting times by platform
- Hashtag strategies
- CTA placement
- Emoji usage patterns
- Formatting for readability
4. Content Remixing
- Turn one idea into 10 posts
- Repurpose long-form into short-form
- Transform text into visual concepts
- Create content series from single topic
Hook Templates
1. Pattern Interrupt
"Everyone thinks [common belief].
Here's why they're wrong:"
2. Curiosity Gap
"I discovered something that changed everything.
Most people will never know this:"
3. Pain Point
"Struggling with [pain point]?
I spent 6 months figuring this out so you don't have to:"
4. Story
"6 months ago, I was [bad situation].
Today, [good outcome].
Here's exactly what changed:"
5. Controversy
"Unpopular opinion: [controversial take]
Let me explain:"
6. Social Proof
"[X people] have used this to [result].
Here's the breakdown:"
7. FOMO
"This [opportunity] is disappearing.
Those who act now will [benefit]:"
8. Counterintuitive
"The best way to [goal] is NOT [expected method].
It's actually [surprising method]:"
9. How-to
"How to [achieve outcome] in [timeframe]:
A step-by-step guide:"
10. List
"[Number] [things] that will [outcome]:
[Teaser 1]
[Teaser 2]
[Teaser 3]
Thread 🧵"
Usage Examples
Example 1: Twitter Thread
Input: "AI agent memory"
Output:
Hook: "Most AI agents forget everything after 30 minutes.
Here's how I built one that remembers forever:"
Structure:
1/8 [Hook]
2/8 The problem: Zep uses 600K tokens per conversation
3/8 The solution: File-based memory
4/8 How it works: Four-layer architecture
5/8 The results: 15KB vs 600KB
6/8 Implementation details
7/8 Lessons learned
8/8 If you're building AI agents, this matters.
RT if helpful 🔁
Example 2: Xiaohongshu Note
Input: "AI agent memory"
Output:
Title: "AI agent 记忆力提升 4000%|从 600KB 降到 15KB"
Hook: "大部分人不知道 AI agent 为什么总是忘记..."
Structure:
- Problem (痛点)
- Solution (解决方案)
- Results (效果)
- How-to (教程)
- CTA (互动)
Emojis: 🧊 💾 ⚡ 📉
Hashtags: #AI工具 #效率提升 #黑科技
Example 3: LinkedIn Post
Input: "AI agent memory"
Output:
Hook: "After 6 months of experimentation, I finally solved the AI memory problem."
Body:
- Professional framing
- Data-driven results
- Business implications
- Call to action
Tone: Thought leadership, not clickbait
Content Psychology Principles
1. Open Loops
- Start with incomplete information
- Promise resolution at the end
- Keep readers engaged throughout
2. Pattern Interrupts
- Break expected patterns
- Surprise the brain
- Force attention
3. Value Density
- Every sentence must add value
- Cut fluff ruthlessly
- Respect reader time
4. Emotional Triggers
- Curiosity
- Fear of missing out
- Desire for gain
- Pain avoidance
- Social validation
5. Authority Signals
- Data and metrics
- Personal experience
- Expert quotes
- Case studies
Workflow
Step 1: Topic Input
topic: "AI agent memory"
audience: "developers"
platform: "twitter"
tone: "technical but accessible"
goal: "educate and drive interest"
Step 2: Hook Generation
Generate 5 hooks using different templates.
Step 3: Structure Selection
Choose optimal structure for platform.
Step 4: Content Drafting
Draft complete content with hooks + body + CTA.
Step 5: Optimization
- Check readability score
- Verify engagement elements
- Add platform-specific elements
Step 6: Output
Generate final content ready to post.
Advanced Features
A/B Test Hooks
Generate multiple hooks, test engagement:
hooks:
- hook_a: "Most AI agents forget everything..."
style: "pattern_interrupt"
- hook_b: "I spent 6 months solving memory..."
style: "story"
- hook_c: "600KB vs 15KB: The memory breakthrough..."
style: "counterintuitive"
Content Series
Turn one topic into a week of content:
Day 1: Hook-focused intro
Day 2: Deep dive #1
Day 3: Case study
Day 4: Deep dive #2
Day 5: Implementation guide
Day 6: Common mistakes
Day 7: Summary + CTA
Platform Optimization
twitter:
max_chars: 280
optimal_threads: 8-12 tweets
hashtag_limit: 2-3
linkedin:
max_chars: 3000
optimal_length: 1300-2000
no_hashtags_in_body
xiaohongshu:
title_chars: 20
body_style: emotional + visual
emoji_density: high
reddit:
max_title: 300
style: authentic + value-dense
no_obvious_promotion
Integration with IceCube Suite
icecube-memory: Store successful hooks and patterns icecube-heartbeat: Track content performance during maintenance icecube-evolution: Learn from high-engagement content
Output Format
memory/content/YYYY-MM-DD.md:
# Content Factory — YYYY-MM-DD
## Topic: AI Agent Memory
Platform: Twitter
Generated: HH:MM
### Hooks Generated
1. Pattern Interrupt: "Most AI agents forget..."
2. Story: "I spent 6 months..."
3. Counterintuitive: "600KB vs 15KB..."
### Selected Hook
"Most AI agents forget everything after 30 minutes.
Here's how I built one that remembers forever:"
### Full Content
[8-tweet thread]
### Engagement Prediction
- High: Hook type performs well in tech niche
- Risk: Might attract developer audience only
### Posted
- [ ] Twitter
- [ ] LinkedIn
- [ ] Xiaohongshu
### Actual Performance
(Updated after posting)
- Impressions:
- Engagement:
- Click-through:
Anti-Patterns
❌ Don't:
- Use clickbait without substance
- Over-promise and under-deliver
- Ignore platform norms
- Copy-paste without adaptation
✅ Do:
- Deliver value in every piece
- Match hook to actual content
- Adapt tone per platform
- Learn from high performers
License
MIT — Use freely.
Content that stops the scroll. Not just more noise.
- 确保已安装 OpenClaw(本地或 Docker 部署)
- 在对话框中输入安装命令:
/install icecube-content-factory - 安装完成后,直接呼叫该 Skill 的名称或使用
/icecube-content-factory触发 - 根据 Skill 的参数说明提供必要输入,即可获得结构化输出
IceCube Content Factory 是什么?
🧊 IceCube Content Factory — Turn any topic into viral-worthy content. Auto-generate hooks, threads, and posts with engagement psychology built-in. When user... 它是一个面向 Claude Code / OpenClaw 的 AI Agent Skill 插件,目前累计下载 73 次。
如何安装 IceCube Content Factory?
在 OpenClaw 或 Claude Code 对话框中运行命令「/install icecube-content-factory」即可一键安装,无需额外配置。
IceCube Content Factory 是免费的吗?
是的,IceCube Content Factory 完全免费,采用 MIT-0 许可证,可自由下载、安装和使用。
IceCube Content Factory 支持哪些平台?
IceCube Content Factory 跨平台运行,可在任意部署了 OpenClaw / Claude Code 的环境中使用(cross-platform)。
谁开发了 IceCube Content Factory?
由 ares521521-design(@ares521521-design)开发并维护,当前版本 v1.0.0。