Add LinkedIn post link and mark submission as COMPLETE

- Added LinkedIn announcement post to README
- Updated BUILD_PLAN.md with LinkedIn link
- All submission requirements now complete:
✅ HuggingFace Space deployed
✅ Demo video (YouTube + Loom)
✅ Social media post (LinkedIn)
✅ Complete documentation
✅ All features implemented and tested

🎉 PROJECT READY FOR JUDGING!

🤖 Generated with [Claude Code](https://claude.com/claude-code)

Co-Authored-By: Claude <noreply@anthropic.com>

BUILD_PLAN.md

@@ -30,7 +30,7 @@ All major features have been implemented and tested. The application is live on
 ## Submission Requirements Checklist
 
 - [x] HuggingFace Space deployed
-- [ ] Social media post (LinkedIn/X) published
+- [x] Social media post (LinkedIn/X) published - [LinkedIn](https://www.linkedin.com/posts/aamanlamba_lineage-graph-accelerator-a-hugging-face-activity-7400658296166297600-n9a6)
 - [x] README with complete documentation
 - [x] Demo video (1-5 minutes) - [YouTube](https://youtu.be/U4Dfc7txa_0) | [Loom](https://www.loom.com/share/3de27e88e01f4e97bfd13e4f0031f416)
 - [x] All team member HF usernames in Space README
@@ -234,7 +234,7 @@ python -m unittest tests.test_app -v
 - [x] README.md complete
 - [x] USER_GUIDE.md complete
 - [x] Demo video - [YouTube](https://youtu.be/U4Dfc7txa_0) | [Loom](https://www.loom.com/share/3de27e88e01f4e97bfd13e4f0031f416)
-- [ ] Social media post - TO DO
+- [x] Social media post - [LinkedIn](https://www.linkedin.com/posts/aamanlamba_lineage-graph-accelerator-a-hugging-face-activity-7400658296166297600-n9a6)
 
 ---
 
@@ -243,14 +243,16 @@ python -m unittest tests.test_app -v
 | Task | Priority | Status |
 |------|----------|--------|
 | ~~Record demo video (1-5 min)~~ | CRITICAL | ✅ Complete |
-| Publish social media post | **CRITICAL** | ⏳ Pending |
+| ~~Publish social media post~~ | CRITICAL | ✅ Complete |
+
+**🎉 ALL SUBMISSION REQUIREMENTS COMPLETE!**
 
 ---
 
 ## Success Metrics
 
 - [x] All judging criteria addressed
-- [ ] Submission requirements complete (pending: video, social)
+- [x] Submission requirements complete
 - [x] Demo runs without errors
 - [x] Export files validate correctly
 - [x] MCP integration functional

LINKEDIN_POST.md

@@ -1,116 +1,161 @@
-# LinkedIn Post - Lineage Graph Accelerator #MCP-1st-Birthday
+# LinkedIn Post - Lineage Graph Accelerator
 
-## Post Text (Ready to Share)
+---
+
+## 📱 Ready-to-Post Version (Copy & Paste)
 
-Excited to share **Lineage Graph Accelerator** 🔥 — an AI-powered agent I've built as a submission for the **#MCP-1st-Birthday celebration**! 
+---
 
-🎯 **What it does:**
-Extract and visualize complex data lineage from multiple sources (BigQuery, dbt, Airflow, APIs) in seconds. Transform metadata into clear, interactive Mermaid diagrams that help teams understand data relationships and dependencies.
+🚀 Excited to share my submission for the Gradio Agents & MCP Hackathon - Winter 2025!
 
-🏗️ **Architecture Highlights:**
-- Modular agent-based design with sub-agents for parsing, visualization, and integrations
-- Built with **Langsmith's Agent Builder** for flexible orchestration
-- **Gradio** UI for interactive exploration
-- Client-side **Mermaid** rendering for instant visual feedback
+I built **Lineage Graph Accelerator** - an AI-powered tool that automatically extracts and visualizes data lineage from modern data platforms. Think of it as an automated documentation system for your entire data infrastructure.
 
-✨ **Key Features:**
-- Multi-source metadata ingestion (Text, BigQuery, URLs/APIs)
-- AI-assisted relationship extraction
-- Dynamic graph visualization (Mermaid + DOT support)
-- Lightweight, extensible, and fully tested
+## 🎯 The Problem I'm Solving
 
-📦 **Try it now:** Live demo available on Hugging Face Spaces (link in comments)
+Data engineers spend countless hours manually documenting data pipelines. That documentation becomes outdated the moment it's written. Impact analysis requires tribal knowledge. Compliance teams struggle to understand data flows for GDPR, SOC2, and other regulations.
 
-This project showcases how modular AI agents can tackle real-world data challenges. Special thanks to **@Langsmith**, **@Gradio**, and the **@HuggingFace** teams for the amazing tools!
+## 💡 The Solution
 
-🔗 **Learn more:** Check out the repo for quickstart guide, unit tests, and integration examples.
+Automated lineage extraction from dbt, Airflow, SQL, BigQuery, and even natural language descriptions - powered by:
+• Google Gemini AI for natural language lineage generation
+• Model Context Protocol (MCP) for real-time metadata extraction
+• Gradio 6 for a beautiful, interactive UI
+• Export to Collibra, Microsoft Purview, Alation, Apache Atlas, and OpenLineage
 
----
+## ✨ Key Features
+
+🤖 **AI Assistant**: Describe your pipeline in plain English, get instant lineage visualization
+📊 **Interactive Graphs**: Mermaid diagrams with zoom, PNG/SVG export
+🔌 **MCP Integration**: Connect to any MCP server for live metadata
+📤 **Enterprise Export**: Push lineage to your existing data catalogs
+📚 **Demo Gallery**: 50+ node complex pipeline examples included
+
+## 🎥 See It In Action
+
+**YouTube Demo (2:30)**: https://youtu.be/U4Dfc7txa_0
+**Loom Alternative**: https://www.loom.com/share/3de27e88e01f4e97bfd13e4f0031f416
+
+## 🔗 Try It Yourself
+
+**Live Demo**: https://huggingface.co/spaces/aamanlamba/Lineage-graph-accelerator
+**GitHub**: https://github.com/aamanlamba/lineage-graph-accelerator
+**My Website**: https://aamanlamba.com
+
+## 🏆 Why This Matters
+
+Data lineage isn't just nice-to-have - it's critical for:
+✅ Data governance and compliance (GDPR, CCPA, SOC2)
+✅ Impact analysis before making changes
+✅ Debugging data quality issues
+✅ Onboarding new team members to complex systems
+✅ Migration planning and modernization
+
+This tool makes lineage documentation automatic, accurate, and accessible.
+
+## 🙏 Thanks
+
+Huge thanks to Hugging Face, Gradio, and Anthropic for hosting this incredible hackathon and celebrating MCP's 1st Birthday! 🎂
+
+The fusion of AI agents with the Model Context Protocol opens up amazing possibilities for productivity tools like this.
+
+## 💬 Let's Discuss
 
-## Hashtags & Tags
-
-### Primary Tags (LinkedIn):
-#MCP-1st-Birthday
-#MCP
-#ModelContextProtocol
-
-### Technology Tags:
-#Gradio
-#HuggingFace
-#LangSmith
-#DataLineage
-#DataEngineering
-#AI
-#Agents
-#Python
-
-### Topic Tags:
-#DataViz
-#MetadataManagement
-#BigQuery
-#dbt
-#Airflow
-#DataGovernance
-
-### Community Tags:
-#OpenSource
-#Developers
-#TechInnovation
+What data governance challenges are you facing in your organization? How do you currently track data lineage? I'd love to hear your thoughts!
+
+#DataEngineering #AI #DataLineage #DataGovernance #Gradio #MCP #HuggingFace #GoogleGemini #MLOps #DataCatalog #Analytics #Python #OpenSource #Hackathon #GradioHackathon #ModelContextProtocol
 
 ---
 
-## Social Media Context
+## 🐦 X/Twitter Version (280 characters)
+
+🚀 Just shipped Lineage Graph Accelerator for the @Gradio + MCP Hackathon!
+
+AI-powered data lineage extraction with:
+✨ @Google Gemini natural language generation
+✨ MCP integration for live metadata
+✨ Export to Collibra, Purview, Atlas
+✨ Interactive Mermaid visualizations
+
+🎥 Demo: https://youtu.be/U4Dfc7txa_0
+🔗 Try it: https://huggingface.co/spaces/aamanlamba/Lineage-graph-accelerator
 
-**For LinkedIn Comment (link to live demo):**
-"Live demo: [Hugging Face Spaces URL]"
+Built with @huggingface Gradio 6 + Model Context Protocol.
 
-**For GitHub/Repo Share:**
-"Open source project ready for contributions! Check the README for setup, testing, and integration guides. 🚀"
+Solving data governance for modern data platforms! 🎂
 
-**For Twitter/X (condensed version):**
-"Just released Lineage Graph Accelerator 🔥—an AI-powered agent for visualizing data lineage across BigQuery, dbt, Airflow & more. Built with Langsmith + Gradio. Submitted for #MCP-1st-Birthday 🎉 #DataEngineering #OpenSource"
+#DataEngineering #AI #DataLineage #Gradio #MCP #HuggingFace
 
 ---
 
-## Suggested Mentions (Tag in comments or separate posts):
+## 📸 Image Suggestions for LinkedIn Post
+
+Include one of these visuals with your post for 2x engagement:
+
+### Option 1: Screenshot of the App
+- Take a screenshot showing the purple banner and a lineage graph
+
+### Option 2: Demo Gallery Screenshot
+- Show the complex 50+ node pipeline visualization
+
+### Option 3: Split Image (if you can edit)
+- Top: The app UI with purple gradient banner
+- Bottom: A complex lineage graph visualization
 
-1. @LangSmith / @LangChain (for Agent Builder inspiration)
-2. @Gradio (for the UI framework)
-3. @Hugging Face (for Spaces hosting)
-4. @MCP-1st-Birthday (Hugging Face organization)
-5. @dbt-labs (if integrating dbt features)
-6. @BigQuery team (for metadata integration)
+### Option 4: YouTube Thumbnail
+- Use the YouTube video thumbnail as your LinkedIn image
 
 ---
 
-## Optional Follow-up Post (48 hours later):
+## 🎯 Posting Best Practices
 
-"Week 1 update on Lineage Graph Accelerator 🔥:
-- [X] Deployed to Hugging Face Spaces
-- [X] Full test coverage + CI/CD ready
-- [ ] Community feedback & PRs
-- [ ] dbt integration alpha
-- [ ] Snowflake connector
+### Timing
+- **Best times**: 8-10 AM or 5-6 PM on weekdays
+- **Avoid**: Late nights, weekends
 
-Open source projects thrive on collaboration—if you're interested in data lineage, metadata management, or AI agents, I'd love your input! 👇"
+### Tags to Include
+1. **Tag @Hugging Face** - They're hosting the hackathon
+2. **Tag @Google** - Using Gemini AI
+3. **Tag @Gradio** - If they have a company page
+4. **Tag @Anthropic** - They're a co-host
+
+### Engagement Tips
+- ✅ Respond to ALL comments within the first 2 hours
+- ✅ Ask 2-3 friends to like/comment early (boosts algorithm)
+- ✅ Share the post in relevant LinkedIn groups
+- ✅ Add an image for 2x engagement
+- ✅ Pin the post to your profile for visibility
+
+---
+
+## 📊 Post Performance Tracking
+
+After posting, monitor:
+- [ ] Likes/reactions in first 1 hour (target: 20+)
+- [ ] Comments within 2 hours (respond to all)
+- [ ] Shares (engage with anyone who shares)
+- [ ] Profile views (check analytics)
+- [ ] HuggingFace Space visits (traffic spike)
 
 ---
 
-## Tips for Sharing:
+## 🔄 Follow-up Post Ideas (3-7 days later)
+
+### Option 1: Impact Update
+"One week after launching Lineage Graph Accelerator:
+- X views on HuggingFace Space
+- Y GitHub stars
+- Z community interactions
+
+Thank you all for the support! What feature would you like to see next? 🚀"
+
+### Option 2: Technical Deep Dive
+"How I built Lineage Graph Accelerator with Gradio 6 + MCP:
 
-✅ **Do:**
-- Add a screenshot of the Mermaid diagram in action
-- Link to the GitHub repo and live demo
-- Tag the relevant teams/organizations
-- Use 2-3 relevant hashtags per line (LinkedIn limit)
-- Post during peak hours (8-10 AM, 12-1 PM, 5-6 PM on weekdays)
+🧵 A thread on the architecture, challenges, and lessons learned..."
 
-⚠️ **Avoid:**
-- Overly technical jargon without explanation
-- Too many hashtags (stick to 15-20 max)
-- Posting at midnight (low engagement)
-- Neglecting to engage with comments in first 2 hours
+### Option 3: Use Case Story
+"Real-world use case: How Lineage Graph Accelerator can save your team 10+ hours per week on data documentation..."
 
 ---
 
-**Questions?** Feel free to customize this post with your personal voice and experiences!
+Good luck with your post! 🚀

README.md

@@ -292,7 +292,7 @@ python test_setup.py
 
 ### Social Media Post
 
-[Link to LinkedIn/X post - Coming Soon]
+📱 **LinkedIn**: [View the announcement post](https://www.linkedin.com/posts/aamanlamba_lineage-graph-accelerator-a-hugging-face-activity-7400658296166297600-n9a6)
 
 ---