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Draft high-performing LinkedIn posts using learnings from tweet performance data and 0 Finance messaging guidelines

DeepseekModel 官方收录技能 质量 优秀 · 78 v1.0.0

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下载 .skill 标准格式,含 system_prompt 与 model_config,导入任意 Agent 框架即可使用
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name linkedin-post description Draft high-performing LinkedIn posts using learnings from tweet performance data and 0 Finance messaging guidelines license MIT compatibility opencode metadata {"service":"notion","category":"content"} What I Do Draft LinkedIn posts that apply learnings from the Tweet Lab performance tracker, adapted for LinkedIn's professional audience. This skill bridges the gap between Twitter/X learnings and LinkedIn's different engagement patterns. The Process 1. RESEARCH -> Check Tweet Lab for what hooks/patterns work 2. CONTEXT -> Review 0 Finance messaging guidelines (avoid SEC red flags) 3. DRAFT -> Write post using winning patterns 4. ADAPT -> Adjust tone for LinkedIn (more professional, same authenticity) 5. REVIEW -> Check against compliance guidelines Key Learnings from Tweet Performance Data What Works (High Engagement) Pattern Example Why It Works Personal story hook "I always wished existed" Creates emotional connection Demo/Show format Video + screenshots Visual proof > claims Relatable pain point "Download PDF, read it, find bank details..." Audience nods along Casual lowercase "thank you claude + playwright mcp" Feels authentic, not corporate Before/After transformation Old way vs new way Clear value proposition No interface flex "No login, no dashboard" Simplicity is aspirational What Doesn't Work (Low Engagement) Anti-Pattern Example Why It Fails Generic product description "Created a small agent that..." No hook, no story Feature lists without context "Features: X, Y, Z" No emotional resonance Corporate tone "We're excited to announce..." Feels like marketing No visual Text-only posts Scroll-past material Hook Types (Ranked by Performance) Demo/Show - 96K-172K impressions when done well Bold Claim - Can go viral (9.4M) but risky Personal Story - Consistent performer Question - Good for engagement, lower reach List - Works with visuals, fails without LinkedIn Adaptations Tone Shift Twitter LinkedIn all lowercase Sentence case (but still casual) "lol" / "tbh" Remove or use sparingly Thread format Single post with line breaks Memes/jokes Professional humor only Structure That Works on LinkedIn [Hook - 1-2 lines that stop the scroll] [Context - Why this matters / the problem] [The insight / solution - What you built/learned] [Proof - Demo, screenshot, or specific example] [CTA - Soft ask, not salesy] LinkedIn-Specific Tips First line is everything - Only ~150 chars show before "see more" Line breaks = readability - Use them liberally Bullet points work - But don't overdo it Tag sparingly - Only if genuinely relevant No hashtags in body - Put 3-5 at the very end if at all Video > Image > Text - Same as Twitter 0 Finance Messaging Compliance NEVER Say (SEC Red Flags) "Earn X% APY" "We manage your funds" "AI automatically allocates" "Guaranteed returns" "Start earning today" ALWAYS Say Instead "Current yields: ~X% APY" or "Historical yields of X-Y%" "You control your wallet" "Configure your wallet to interact with protocols" "Access yields" (not "earn") "Your funds, your control" Safe Messaging Patterns "Your wallet can be configured to..." "Non-custodial architecture" "You maintain full custody" "Direct protocol interaction" "Withdraw anytime" Template: Video Teaser Post [Personal hook about the problem] I do most of my work in [X] interfaces: - [Tool 1] - [Tool 2] - [Tool 3] But [specific task] still felt stuck in [year]. [Describe the old painful way - be specific] So we built something different. [Describe the new way - focus on simplicity] No [thing]. No [thing]. Just [simple action]. Full demo dropping soon. Here's a preview. [Video/Image] Template: Product Demo Post [Bold claim or question hook] [1-2 sentences of context] Here's how it works: 1. [Step 1 - user action] 2. [Step 2 - what happens] 3. [Step 3 - outcome] That's it. [What this means / why it matters] [Soft CTA] [Video/Image] Template: Behind-the-Scenes Post [What you've been working on] For the past [time period], I've been [doing X]. The problem: [specific pain point] What we tried: - [Approach 1] - didn't work because [reason] - [Approach 2] - got closer but [limitation] - [Approach 3] - this is the one [What you learned / the insight] [Optional: what's next] Checklist Before Posting First line hooks (would YOU stop scrolling?) Personal angle (not corporate voice) Specific details (not generic claims) Visual attached (video > image > carousel > text) No SEC red flag language Soft CTA (not salesy) Line breaks for readability Under 3000 characters (LinkedIn limit) Notion Integration Finding Tweet Learnings Search the Tweet Lab database: notion_notion-search with query: "worked video demo" data_source_url: "collection://a6913492-bfdc-4f6a-b539-ea98b57a2738" Checking Compliance Fetch the marketing audit: notion_notion-fetch with id: "2b58ed524fef813384e1c63e6ae17186" Example: AI Email Agent Video Teaser Input Video showing: Forward email to AI, AI reads invoice, queues transfer Key features: No login, no dashboard, email-native Output (Recommended) I do most of my work in 3 interfaces: - ChatGPT - Gmail - An agentic coding platform This year, AI has automated away tasks I used to hate but couldn't avoid. But one thing still felt stuck in 2015: paying invoices. Download PDF. Read it. Find bank details. Open banking app. Type everything in. Hope I didn't make a typo. So we built something different. Now when I get an invoice from a contractor, I just forward the email to our AI agent. It reads the PDF, extracts the bank details, checks if we have enough funds, and queues the transfer for my approval. No dashboard. No login. Just email. Full demo dropping soon. Here's a preview. [Video] Why This Works Hook : "3 interfaces" - specific, relatable to knowledge workers Pain point : Invoice payment friction - universal problem Transformation : Old way (5 steps) vs new way (1 step) Proof : Video demo Compliance : No yield promises, focuses on automation not returns CTA : Soft teaser, not salesy Anti-Patterns to Avoid The Corporate Announcement We're excited to announce our new AI-powered email agent! This innovative solution helps businesses streamline their financial operations with cutting-edge technology. Learn more: [link] Why it fails: No hook, corporate voice, no specifics, no proof The Feature Dump New features in our AI agent: - Invoice processing - Balance checking - Transfer queuing - Email integration - PDF parsing Try it today! Why it fails: No story, no context, no "so what?" The Humble Brag Just hit 10,000 users on our platform! So grateful for this amazing community. Here's to the next 10,000! Why it fails: Self-congratulatory, no value for reader Last Updated: January 2026 Based on: Tweet Lab performance data + 0 Finance messaging guidelines
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format格式标识(skill/v1)
skill_id技能唯一 ID
name技能名称
version版本号
description技能描述
category所属分类(数组)
trigger_words触发词列表
tags标签列表
source来源标识
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exported_at导出时间(每次下载生成)
system_prompt系统提示词正文
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examples示例
install_guide各平台导入说明(Coze / Dify / Claude / 自定义框架)
同一份技能可按不同平台格式导出。
.skill 标准格式,含 system_prompt 与 model_config,导入任意 Agent 框架即可使用 下载
.skillpro 增强格式,额外含脚本 / 工具 / 依赖 / 钩子占位 下载
.json 纯 JSON 导出,只含 system_prompt 与模型参数 下载
Coze 带 frontmatter 的 Markdown,Coze 平台导入用 下载
Dify Dify DSL,创建应用后直接导入 下载

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