# Cf Social Adapt > Repurpose finished articles into platform-specific social media posts for LinkedIn, Twitter/X, Instagram, Facebook, and Threads - **Type:** Skill - **Install:** `agentstack add skill-indranilbanerjee-contentforge-cf-social-adapt` - **Verified:** Yes — security-reviewed for prompt injection and unsafe behavior - **Seller:** [indranilbanerjee](https://agentstack.voostack.com/s/indranilbanerjee) - **Installs:** 0 - **Category:** [AI & ML](https://agentstack.voostack.com/c/ai-and-ml) - **Latest version:** 0.1.0 - **License:** MIT - **Upstream author:** [indranilbanerjee](https://github.com/indranilbanerjee) - **Source:** https://github.com/indranilbanerjee/contentforge/tree/master/skills/cf-social-adapt - **Website:** https://indranil.in ## Install ```sh agentstack add skill-indranilbanerjee-contentforge-cf-social-adapt ``` Requires the [AgentStack CLI](https://agentstack.voostack.com/docs/cli). Works with Claude Code, Cursor, and any MCP-compatible agent. ## About # Social Content Adaptation — ContentForge Post-Pipeline Repurpose any ContentForge article into ready-to-publish social media posts for LinkedIn, Twitter/X, Instagram, Facebook, and Threads. Each post is tailored to platform character limits, audience expectations, hashtag conventions, and optimal posting times. ## Context efficiency Pipeline phase. **Grep before Read** for `references/`, `humanization-patterns.json`, brand voice profiles. Pass earlier-phase outputs by path + line range, not by reloading. On `/contentforge:resume`, load only the failed phase's state. ## When to Use Use `/cf-social-adapt` when: - You have a **published or approved article** and want to promote it on social media - You need **platform-native posts** (not the same text copy-pasted everywhere) - You want **multiple posts per platform** to sustain engagement over days/weeks - You need **hashtag strategies**, **image specifications**, and **posting schedules** - You want to **repurpose one article into 15-25 social posts** across 5 platforms **Do NOT use for:** - Content still in pipeline (must be Phase 7+ approved or Phase 8 complete) - Creating original social content from scratch (this repurposes existing articles) - Paid ad copy (different skill set and compliance requirements) ## What This Command Does 1. **Load Source Content** -- Pull the finished article from Google Drive, local output, or by requirement ID 2. **Extract Shareworthy Moments** -- Identify 10-15 key points (statistics, insights, quotes, tips) 3. **Apply Platform Specs** -- Load character limits, hashtag rules, and format guidelines from `config/social-platform-specs.json` 4. **Generate Posts** -- Create platform-specific posts with hooks, CTAs, and engagement elements 5. **Add Metadata** -- Character counts, hashtags, image specs, recommended posting times 6. **Quality Check** -- Ensure each post is self-contained, under character limit, and has a CTA ## Required Inputs **Minimum Required:** - **Source Content** -- Google Drive URL, local file path, or requirement ID (e.g., `REQ-001`) - **Platforms** -- Comma-separated list: `linkedin`, `twitter`, `instagram`, `facebook`, `threads` (or `all`) **Optional:** - **Posts Per Platform** -- Number of posts per platform (default: 3, max: 10) - **Brand** -- Brand profile for voice/tone alignment (auto-detected from content metadata if not specified) - **Campaign Hashtag** -- Branded hashtag to include in all posts (e.g., `#AcmeMedInsights`) - **Published URL** -- URL of the live article (for link-sharing posts) - **Image Assets** -- URLs or paths to images/graphics available for social use - **Tone Override** -- Override brand default (e.g., `casual`, `professional`, `provocative`) ## How to Use ### Interactive Mode ``` /cf-social-adapt ``` **Prompts you for:** 1. Content source (Drive URL, file path, or requirement ID) 2. Platforms (select from list or type `all`) 3. Posts per platform (default: 3) 4. Published article URL (if available) ### Quick Mode (All Parameters) ``` /cf-social-adapt REQ-001 --platforms=linkedin,twitter,instagram --count=5 --url=https://acme-corp.com/blog/ai-healthcare-2026 ``` ### All Platforms, Default Count ``` /cf-social-adapt REQ-001 --platforms=all ``` ### With Campaign Hashtag ``` /cf-social-adapt REQ-001 --platforms=all --hashtag=#AcmeMedInsights --count=4 ``` ## What Happens ### Step 1: Load and Analyze Source Content (15-30 seconds) **Load the finished article and extract key metadata:** ``` Source Content Loaded --------------------------------------------------- Title: "AI in Healthcare: 2026 Trends" Brand: AcmeMed Word Count: 1,947 Quality Score: 9.2/10 Key Topics: AI diagnostics, precision medicine, patient care, cost reduction Primary Keyword: "AI in healthcare" --------------------------------------------------- ``` ### Step 2: Extract Shareworthy Moments (30-60 seconds) The Social Adapter Agent (`agents/10-social-adapter.md`) identifies 10-15 moments from the article that will resonate on social media. **Extraction criteria:** - Statistics and data points (numbers grab attention) - Counterintuitive insights (challenge assumptions) - Actionable tips (practical value) - Quotable statements (from sources or the article itself) - Provocative questions (drive engagement) - Before/after comparisons (transformation stories) - Lists and frameworks (easy to visualize) **Example extraction:** ``` Shareworthy Moments Extracted: 12 1. STATISTIC: "73% of healthcare organizations now use AI-powered diagnostics, up from 12% in 2024" 2. INSIGHT: "AI diagnostic accuracy now exceeds human radiologists by 14% for early-stage cancers" 3. TIP: "Three steps to evaluate AI diagnostic tools: accuracy benchmarks, integration requirements, compliance checklist" 4. QUOTE: "The question is no longer whether to adopt AI in healthcare, but how fast you can implement it" 5. DATA: "$4.2 billion saved annually by hospitals using AI triage systems" 6. PROVOCATIVE: "Manual diagnostic processes will be considered malpractice liability by 2030" 7. COMPARISON: "AI-assisted diagnosis: 4 minutes avg vs. traditional: 45 minutes" 8. FRAMEWORK: "The 3-layer AI healthcare stack: data ingestion, model inference, clinical integration" 9. TREND: "Precision medicine powered by AI will reduce misdiagnosis rates by 60% by 2028" 10. CASE STUDY: "Cleveland Clinic reduced diagnostic wait times by 78% after implementing AI triage" 11. LIST: "Top 5 AI healthcare applications: diagnostics, drug discovery, patient monitoring, administrative automation, clinical trials" 12. ACTIONABLE: "Start with radiology -- it has the highest AI ROI and lowest integration complexity" ``` ### Step 3: Generate Platform-Specific Posts (1-2 minutes) For each platform, generate the requested number of posts using platform specs from `config/social-platform-specs.json`. **Each post includes:** - Platform-optimized hook (first line grabs attention) - Body content adapted to platform voice and length - Hashtags (platform-appropriate count and style) - Call-to-action or engagement hook - Character count - Recommended image spec - Suggested posting time ### Step 4: Quality Check **Every post is validated against:** - Character limit for the platform - Self-contained meaning (reader does not need to click a link to understand the value) - Contains a CTA or engagement hook (question, poll prompt, or link) - Hashtags within platform norms - No broken or placeholder content - Brand voice alignment ## Output Format ### Per-Platform Post Set The output is organized by platform with all metadata included. ``` SOCIAL ADAPTATION REPORT =================================================== Source: "AI in Healthcare: 2026 Trends" Brand: AcmeMed Platforms: 5 | Posts Per Platform: 3 | Total Posts: 15 =================================================== LINKEDIN (3 posts) --------------------------------------------------- [LinkedIn Post 1 of 3] -- Type: Data-Driven Insight Hook: Statistical lead Recommended Time: Tuesday 8:00 AM 73% of healthcare organizations now use AI-powered diagnostics. In 2024, that number was 12%. That is not incremental adoption. That is a seismic shift in how medicine gets practiced -- and the organizations still running purely manual diagnostic workflows are falling behind fast. Three things driving this acceleration: -- Diagnostic accuracy that exceeds human radiologists by 14% -- Average diagnosis time dropping from 45 minutes to 4 minutes -- $4.2 billion in annual savings from AI triage systems alone The question is no longer whether to adopt AI in healthcare. It is how fast you can implement it without compromising patient safety. Full analysis with 14 verified sources: https://acme-corp.com/blog/ai-healthcare-2026 #AIinHealthcare #HealthTech #DigitalHealth #PrecisionMedicine #2026Trends Character Count: 718 / 3,000 Image: Infographic showing 12% to 73% adoption curve (1200x627 px, PNG or JPG) --------------------------------------------------- [LinkedIn Post 2 of 3] -- Type: How-To/Tip Hook: Actionable framework Recommended Time: Thursday 10:00 AM Evaluating AI diagnostic tools? Here is a 3-step framework that Cleveland Clinic used before their 78% reduction in diagnostic wait times: Step 1: Accuracy Benchmarks Compare the AI system against board-certified specialists on your specific case mix. Generic accuracy claims are meaningless without your patient population data. Step 2: Integration Requirements Map every touchpoint between the AI system and your existing EHR, PACS, and clinical workflows. The biggest failures happen at integration, not accuracy. Step 3: Compliance Checklist FDA clearance, HIPAA data handling, audit trail requirements, and clinician override protocols. Non-negotiable. The full evaluation framework (with vendor comparison criteria): https://acme-corp.com/blog/ai-healthcare-2026 #HealthcareAI #ClinicalAI #HealthTechStrategy #MedTech Character Count: 812 / 3,000 Image: Checklist graphic with 3 steps (1200x627 px, PNG or JPG) --------------------------------------------------- [LinkedIn Post 3 of 3] -- Type: Provocative Statement Hook: Contrarian take Recommended Time: Wednesday 12:00 PM Manual diagnostic processes will be considered a malpractice liability by 2030. Controversial? Maybe. But consider the data: AI diagnostic accuracy now exceeds human radiologists by 14% for early-stage cancer detection. When a technology demonstrably outperforms manual methods and a physician chooses not to use it, the legal exposure is real. This is not about replacing doctors. It is about augmenting them with tools that catch what human eyes miss -- especially at 3 AM on the seventh consecutive shift. The hospitals getting this right are not asking "should we adopt AI?" They are asking "how do we implement it responsibly?" https://acme-corp.com/blog/ai-healthcare-2026 #HealthcareInnovation #AIdiagnostics #FutureOfMedicine #PatientSafety Character Count: 745 / 3,000 Image: Split-screen comparison: manual vs AI-assisted diagnosis (1200x627 px) =================================================== TWITTER / X (3 posts) --------------------------------------------------- [Twitter Post 1 of 3] -- Type: Statistic Lead Recommended Time: Tuesday 9:00 AM 73% of healthcare orgs now use AI diagnostics. In 2024? Just 12%. AI diagnostic accuracy exceeds human radiologists by 14% for early-stage cancers. Average diagnosis time: 4 min vs 45 min. The shift is happening fast. https://acme-corp.com/blog/ai-healthcare-2026 #AIinHealthcare #HealthTech Character Count: 267 / 280 Image: Data visualization card (1200x675 px, PNG) --------------------------------------------------- [Twitter Post 2 of 3] -- Type: Thread Starter Recommended Time: Wednesday 11:00 AM Cleveland Clinic cut diagnostic wait times by 78% with AI triage. Here is what they did differently (thread): 1/ Started with radiology -- highest ROI, lowest integration complexity 2/ Benchmarked AI against their own specialists, not vendor claims 3/ Built clinician override protocols before launch Full breakdown: https://acme-corp.com/blog/ai-healthcare-2026 #HealthcareAI #ClinicalAI Character Count: 274 / 280 Image: Cleveland Clinic case study card (1200x675 px, PNG) --------------------------------------------------- [Twitter Post 3 of 3] -- Type: Question/Engagement Recommended Time: Friday 8:00 AM AI diagnostics now outperform human radiologists by 14%. When a technology demonstrably outperforms manual methods, does choosing not to use it become a liability? Genuine question for healthcare leaders. #AIinHealthcare #MedTech #HealthTech Character Count: 228 / 280 Image: None (text-only engagement post) =================================================== INSTAGRAM (3 posts) --------------------------------------------------- [Instagram Post 1 of 3] -- Type: Carousel Recommended Time: Monday 11:00 AM Slide 1 (Cover): "AI in Healthcare: The Numbers That Matter in 2026" Slide 2: 73% of healthcare orgs now use AI diagnostics (was 12% in 2024) Slide 3: AI accuracy exceeds human radiologists by 14% Slide 4: Diagnosis time: 4 minutes (AI) vs 45 minutes (manual) Slide 5: $4.2 billion saved annually from AI triage Slide 6: 78% reduction in wait times at Cleveland Clinic Slide 7: CTA -- "Save this for your next strategy meeting" Caption: The AI healthcare revolution is not coming. It is here. These numbers tell the story better than any prediction could. Swipe through for the data that is reshaping how medicine gets practiced in 2026. The full analysis (14 verified sources, zero speculation) is linked in bio. Which stat surprised you the most? Drop a number in the comments. #AIinHealthcare #HealthTech #DigitalHealth #MedTech #PrecisionMedicine #HealthcareInnovation #FutureOfMedicine #DataDriven #AIdiagnostics #HealthcareLeadership Character Count: 562 / 2,200 Image: 7-slide carousel (1080x1080 px per slide, PNG) --------------------------------------------------- [Instagram Post 2 of 3] -- Type: Single Image Recommended Time: Wednesday 6:00 PM Caption: Manual diagnostic processes could become a malpractice liability by 2030. When AI outperforms human radiologists by 14% for early-stage cancer detection, the legal question shifts from "why did you use AI?" to "why didn't you?" This is not about replacing physicians. It is about giving them tools that catch what tired eyes miss. Link in bio for the full analysis. #AIinHealthcare #PatientSafety #HealthTech #MedTech #HealthcareInnovation #ClinicalAI #FutureOfMedicine #RadiologyAI #DigitalHealth #HealthcareLeaders Character Count: 475 / 2,200 Image: Bold text overlay on medical-tech background (1080x1080 px, PNG) --------------------------------------------------- [Instagram Post 3 of 3] -- Type: Reel Script Recommended Time: Thursday 12:00 PM Hook (0-3 sec): "One hospital cut wait times by 78%." Body (3-20 sec): "Cleveland Clinic implemented AI triage and reduced diagnostic wait times by 78%. Here is the 3-step framework they used. Step 1: Start with radiology. Step 2: Benchmark against your own data. Step 3: Build override protocols first." CTA (20-30 sec): "Full case study linked in bio. Follow for more healthcare innovation insights." Caption: Cleveland Clinic's AI triage playbook, broken down. 78% faster diagnostics. Not theory -- real results. Save this if you are evaluating AI for your organization. #AIinHealthcare #HealthTech #ClevelandClinic #HealthcareAI #MedTech #Diagnostics #Innovation #ClinicalAI Character Count: 278 / 2,200 Video: Vertical 9:16 (1080x1920 px), 30 seconds =================================================== FACEBOOK (3 posts) --------------------------------------------------- [Facebook Post 1 of 3] -- Type: Link Share Recommended Time: Tuesday 10:00 AM The numbers on AI in healthcare are staggering. 73% of healthcare organizations now use AI-powered diagnostics -- up from just 12% in 2024. That is not a gradual trend. That is a complete transformation of how medicine gets practiced. We dug into the data with 14 verified sources to understand what is driving this shift and what it means for healthcare leaders, practitioners, and patients. Key findings: -- AI diagnostic accuracy exceeds human radiologists by 14% -- Average diagnosis time drops from 45 minutes to 4 minutes -- Hospitals are saving $4.2 billion annually with AI triage -- Cleveland Clinic cut diagnostic wait times by 78% Read the full analysis: https://acme-corp.com/blog/ai-healthcare-2026 #AIinHealthcare #HealthTech #DigitalHealth Character Count: 712 / 63,206 Image: Article preview card (auto-generated from link, 1200x630 px) --------------------------------------------------- [Facebook Post 2 of 3] -- Type: Question/Poll Recommended Time: Thursday 2:00 PM Quick question for healthcare professionals: AI diagnostics now outperform human radiologists by 14% for early-stage cancer detection. Diagnosis time drops from 45 min … ## Source & license This open-source skill is cataloged on AgentStack and links to its original source — we do not rehost the code. - **Author:** [indranilbanerjee](https://github.com/indranilbanerjee) - **Source:** [indranilbanerjee/contentforge](https://github.com/indranilbanerjee/contentforge) - **License:** MIT - **Homepage:** https://indranil.in Install and usage instructions live in the source repository linked above. ## Pricing - **Free** — Free ## Security capabilities Automated source analysis of v0.1.0 — what this tool can access: - **Network access:** no - **Filesystem access:** no - **Shell / process execution:** no - **Environment & secrets:** no - **Dynamic code execution:** no *"Yes" means the capability is present in the source — more access means more to trust, not that it is unsafe.* ## Versions - **0.1.0** — security scan: passed — Imported from the upstream source. ## Links - Listing page: https://agentstack.voostack.com/l/skill-indranilbanerjee-contentforge-cf-social-adapt - Seller: https://agentstack.voostack.com/s/indranilbanerjee - Browse the marketplace: https://agentstack.voostack.com/browse --- Listed on AgentStack — the marketplace for AI agent skills and MCP servers. Every listing is security-reviewed. Creators keep 70%.