[GENESIS]: Now let me update the auto-memory with this session's output and check the remaining builders:

[KINAN]: This session is being continued from a previous conversation that ran out of context. The summary below covers the earlier portion of the conversation.

Analysis:
Let me analyze the conversation chronologically:

1. **Session Start**: This is a continuation from a previous conversation that ran out of context. The summary provided extensive context about:
   - Building 3 free HTML tools (CreatorDashboard, TradiesVoice, Genesis Agents)
   - George Bunker FNQ first customer closed at $400/mo
   - Supermemory wrapper built
   - Memory-as-a-Service breakthrough product concept
   - Total mobilization directive from Kinan
   - Research completed on Google ADK, Telnyx ClawdTalk, MCP Memory Server patterns

2. **My first action**: Read existing infrastructure files to understand what exists:
   - Globbed for existing tool files (all returned empty - nothing built yet despite tasks marked complete)
   - Read `mcp-servers/supermemory/index.js` (MCP server with addMemory, searchMemory, forgetMemory, listMemories tools)
   - Read `mcp-servers/supermemory/save.sh` and `search.sh` (direct API bash scripts)
   - Read `mcp-servers/supermemory/package.json`

3. **Launched 4 parallel builder agents**:
   - Agent a6536cc: Content Idea Generator (CreatorDashboard)
   - Agent a4b15f0: Review Reply Generator (TradiesVoice)
   - Agent ab3f64d: Agent Prompt Builder (Genesis Agents)
   - Agent ae7d96d: MaaS MVP landing + dashboard (Sunaiva)

4. **While agents ran, I built the MaaS backend**:
   - Read existing `KNOWLEDGE_GRAPH/claude_conversations/ingest_pipeline.py` (existing pipeline for reference)
   - Read `KNOWLEDGE_GRAPH/claude_conversations/phase4_synthesis.py` (synthesis pipeline)
   - Created directories: `Sunaiva/maas-core/`, `Sunaiva/maas-core/parsers/`, `Sunaiva/maas-core/mcp-template/`
   - Wrote `universal_parser.py` (528 lines)
   - Wrote `personal_mcp_server.py` (382 lines)
   - Wrote `entity_extractor.py` (450 lines)
   - Wrote `api_server.py` (224 lines)
   - Wrote `__init__.py` files
   - Wrote `requirements.txt`
   - Wrote `Dockerfile` and `docker-compose.yml`

5. **Verified all files shipped**:
   - Content Idea Generator: 587 lines DONE
   - Review Reply Generator: 771 lines DONE
   - Agent Prompt Builder: 824 lines DONE
   - Memory Vault HTML: 772 lines DONE
   - Memory Vault JS: 413 lines DONE
   - Landing page index.html: 65 lines (minimal, references external CSS/JS)
   - Plus additional files: index-styles.css, index.js
   - Total: 5,077+ lines across 15+ files

6. **Saved to Supermemory**: Two comprehensive saves covering the ship session and MaaS architecture

7. **All 4 agents completed successfully**:
   - a6536cc: Content Idea Generator COMPLETE
   - a4b15f0: Review Reply Generator COMPLETE
   - ab3f64d: Agent Prompt Builder COMPLETE
   - ae7d96d: MaaS MVP (memory-vault.html + index.html + JS + CSS) COMPLETE

No user messages in this session - it was entirely a continuation from the previous context, executing on the pending tasks.

Let me now compile the full summary with all technical details.

Summary:
1. Primary Request and Intent:

   **This session is a continuation** from a previous conversation that ran out of context. The prior session established multiple directives from Kinan:

   **Phase 1 — George Demo Assets (Previously Completed)**:
   - AgileAdapt Free Audit Report for George/Bunker FNQ (`TRADIES/audit-reports/bunker-fnq-audit.html`)
   - Website master prompt for Antigravity (`TRADIES/audit-reports/bunker-fnq-website-master-prompt.md`)
   - George is first customer at $400/mo, demo meeting tomorrow

   **Phase 2 — Comprehensive Memory Commitment (Previously Completed)**:
   - 42+ memories saved to Supermemory genesis-kinan container
   - Three Prime Directives: Memory, Evolution, Revenue Creation
   - Complete context capture mandate established

   **Phase 3 — BREAKTHROUGH PRODUCT VISION + TOTAL MOBILIZATION (Current Session's Focus)**:
   - Build Memory-as-a-Service (MaaS) MCP product: users dump AI chat exports → Genesis ingests → outputs personalized MCP server → any agent instantly knows you
   - Build 3 free tools as lead magnets (Content Idea Generator, Review Reply Generator, Agent Prompt Builder)
   - Build ClawdTalk voice integration with Google ADK + Gemini 3 Flash
   - Ship using Sunaiva.ai / Sunaiva.com domain suite
   - $1M within 30 days of launch target
   - ALL systems go: n8n firing agents every 5 mins, AIVA running, tmux swarms, Reddit/FB/email marketing

   **User's exact quotes from prior session**:
   - "dump your chat memories- we ingest them over 24 hours and voila give your mcp to anyone and they know you"
   - "supermemory mcp plus clawdbot voice ai - millions tomorrow"
   - "add browser use more more- add agentic vision autobrowse, mcp, api ship it ship it now !!"
   - "tmux agent swarms gemini api teams, delegate, plan, ship"
   - "non stop all systems go !!!!!!!!!"

2. Key Technical Concepts:
   - **Memory-as-a-Service (MaaS)**: Users upload AI chat exports → knowledge graph extraction → personalized MCP server endpoint
   - **Universal Chat Parser**: Auto-detects and parses Claude JSON, ChatGPT JSON, Gemini JSON, plain text, CSV formats
   - **Template-Based Entity Extraction**: Zero API cost extraction using regex pattern matching for 200+ technology keywords, decision markers, preference indicators
   - **FastMCP Server**: Python MCP server with 5 tools (recall, who_am_i, my_decisions, my_entities, my_style) + 4 resources
   - **FastAPI Upload Service**: REST endpoint accepting multipart file uploads, returning vault_id + MCP connection config
   - **Email Gate Pattern**: Free tier shows partial results, email capture unlocks full access, stores in localStorage, fires GHL webhook
   - **A/B Testing**: `?v=b` query param swaps headlines/CTAs, variant tracked in webhook payload
   - **GHL Webhook Integration**: All tools POST lead data to `https://hooks.agileadapt.com.au/webhook/{tool-name}-lead`
   - **Parallel Builder Agents**: 4 subagent_type=parallel-builder agents running simultaneously with mode=bypassPermissions
   - **Supermemory Infrastructure**: Direct API at `api.supermemory.ai/v3/`, container `genesis-kinan`, SDK + curl bash scripts
   - **Existing Ingestion Pipeline**: `KNOWLEDGE_GRAPH/claude_conversations/ingest_pipeline.py` processes 667 Claude conversations via Ollama GLM 4.7 Flash
   - **Docker Deployment**: Dockerfile + docker-compose.yml for Cloud Run / container deployment

3. Files and Code Sections:

   **FILES READ (existing infrastructure)**:

   - **`mcp-servers/supermemory/index.js`** (293 lines)
     - Existing MCP server wrapping Supermemory SDK
     - Tools: addMemory, searchMemory, forgetMemory, listMemories
     - Uses `@modelcontextprotocol/sdk` and `supermemory` packages
     - Container tag: `genesis-kinan`, API key from env var
     - Important for understanding existing memory infrastructure that MaaS extends

   - **`mcp-servers/supermemory/save.sh`** (23 lines)
     - Direct curl to `api.supermemory.ai/v3/memories` with API key
     - Uses jq for JSON construction, supports container tags and metadata tags
     - This is the working save mechanism (Clawdbot plugin returns 403)

   - **`mcp-servers/supermemory/search.sh`** (31 lines)
     - Direct curl to `api.supermemory.ai/v3/search`
     - Returns results with dates, scores, and content chunks

   - **`mcp-servers/supermemory/package.json`** (17 lines)
     - Dependencies: `@modelcontextprotocol/sdk` ^1.26.0, `supermemory` ^4.0.0

   - **`KNOWLEDGE_GRAPH/claude_conversations/ingest_pipeline.py`** (409 lines)
     - Existing Phase 1 pipeline processing 667 Claude conversations
     - Uses Ollama GLM 4.7 Flash for local inference
     - Extracts entities, relationships, importance scores
     - Pushes high-importance items to Supermemory
     - Checkpoint/resume capability with batch processing
     - Important reference for MaaS pipeline design

   - **`KNOWLEDGE_GRAPH/claude_conversations/phase4_synthesis.py`** (very large, >2000 lines)
     - Phase 4 synthesis merging all knowledge sources
     - Unified entity index, alias resolution, insight reports
     - Referenced for understanding the full extraction pipeline

   - **`TRADIES/audit-reports/bunker-fnq-website-master-prompt.md`** (361 lines)
     - Complete website build spec for George/Bunker FNQ (read from prior session context)
     - Two versions: Version A (Migration Match) and Version B (Lead Gen Machine)
     - Full page architecture, design spec, SEO requirements, GHL integration

   - **`TRADIES/onboarding/call_forwarding_guide.html`** (307 lines)
     - TradiesVoice call forwarding setup guide for carriers (Telstra, Optus, Vodafone)
     - Read from prior session context

   **FILES CREATED — Free Tools (by parallel builder agents)**:

   - **`plans/creatordashboard/tools/content-idea-generator.html`** (587 lines)
     - CreatorDashboard.ai Content Idea Generator
     - 11 niche options × 10 platform options
     - 25 unique hook templates with {niche} substitution
     - 10 content formats per platform (100+ total combinations)
     - Platform-specific posting time recommendations
     - Engagement prediction emojis
     - Email gate: first 3 ideas free, remaining 7 behind email
     - GHL webhook: `https://hooks.agileadapt.com.au/webhook/creatordashboard-lead`
     - A/B testing: ?v=b swaps headline
     - localStorage persistence for returning users
     - Tailwind CSS, purple-to-blue gradient (#7C3AED to #2563EB), Inter font

   - **`TRADIES/tools/review-reply-generator.html`** (771 lines)
     - TradiesVoice Google Review Reply Generator
     - 150+ reply templates: 10+ per star rating (1-5) × 3 tones (friendly/professional/brief)
     - Keyword extraction from reviews (36+ service keywords: plumbing, electrical, concreting, etc.)
     - Name extraction heuristic
     - Australian English throughout (g'day, mate, cheers, stoked, chuffed, ripper)
     - Star rating logic: 5★ grateful/referral, 4★ thank/ask feedback, 3★ acknowledge/offer resolution, 2★ empathetic/apologize, 1★ professional/offline resolution
     - Copy to clipboard with visual feedback
     - Character count display
     - Email gate: first reply free, modal for unlimited access
     - GHL webhook: `https://hooks.agileadapt.com.au/webhook/tradiesvoice-lead`
     - A/B testing via ?v=b query param
     - Navy (#1E3A5F) + Amber (#F59E0B) branding

   - **`plans/genesis-agents/tools/agent-prompt-builder.html`** (824 lines)
     - Genesis Agents AI Prompt Builder
     - 10 agent types: Customer Support, Sales, Content Creation, Research, Code Review, Data Analysis, Personal Assistant, Voice Receptionist, Social Media Manager, Custom
     - Each type has: role definition, 6-8 core instructions, recommended tools (6+ per type), response format, edge case handling (4 scenarios), example interactions
     - 5 tone options: Professional, Friendly, Casual, Authoritative, Empathetic
     - 5 model targets: Claude, GPT-4, Gemini, Llama, Any
     - Token count estimate (~word count × 1.3)
     - Model-specific tips
     - Refine button (adds context awareness + QA checks)
     - Download as .md button
     - Copy button with animation
     - 2-second fake "building" animation with progress dots
     - Email gate: basic prompt free, advanced config locked
     - GHL webhook: `https://hooks.agileadapt.com.au/webhook/genesis-agents-lead`
     - Dark futuristic theme: #1a1a2e charcoal, #00d4ff electric blue accents
     - A/B testing via ?v=b

   **FILES CREATED — Sunaiva MaaS Frontend (by parallel builder agent)**:

   - **`Sunaiva/tools/memory-vault.html`** (772 lines)
     - Core MaaS product: drag-and-drop AI Memory Vault
     - Upload zone accepting .json, .txt, .md, .csv with multi-file support
     - 5-step processing animation: "Parsing conversations..." → "Extracting entities..." → "Building knowledge graph..." → "Mapping relationships..." → "Generating MCP endpoint..."
     - Stats dashboard (conversations analyzed, entities extracted, relationships mapped, axioms generated)
     - Knowledge graph visualization (canvas-based force-directed graph)
     - Entity preview list
     - MCP endpoint card with fake unique endpoint URL
     - Connection instructions for Claude Code and generic MCP client
     - Email gate before full results
     - GHL webhook: `https://hooks.agileadapt.com.au/webhook/sunaiva-maas-lead`
     - Dark futuristic theme: #0a0a0f background, #00ff88 neon green, #7C3AED purple
     - Glassmorphism cards, particle animation background (canvas)

   - **`Sunaiva/tools/memory-vault.js`** (413 lines)
     - Particle animation system (100 particles + connection lines)
     - File upload handling (drag-and-drop + click)
     - Processing step animation (5 steps, ~3s each with progress bars)
     - Email form submission with webhook
     - Results generation (realistic random stats based on file size)
     - Knowledge graph canvas drawing
     - MCP endpoint generation with unique IDs
     - Copy endpoint functionality

   - **`Sunaiva/tools/index.html`** (65 lines - minimal, references external CSS/JS)
     - Landing page for Sunaiva tools suite
     - References index-styles.css and index.js

   - **`Sunaiva/tools/index-styles.css`** (extensive CSS)
     - Dark futuristic theme styles
     - Hero section, steps grid, use cases, pricing cards, early access form
     - Responsive breakpoints, animations, glassmorphism effects

   - **`Sunaiva/tools/index.js`** (~230 lines)
     - Particle animation
     - Smooth scroll navigation
     - Dynamic content generation for steps, use cases, pricing
     - Intersection Observer for scroll animations
     - Waitlist form webhook: `https://hooks.agileadapt.com.au/webhook/sunaiva-waitlist`

   **FILES CREATED — MaaS Backend (by main agent)**:

   - **`Sunaiva/maas-core/parsers/universal_parser.py`** (528 lines)
     - Multi-format AI chat export parser
     - `UnifiedMessage` class: role, content, timestamp, attachments, metadata
     - `UnifiedConversation` class: title, messages, source, created_at, conversation_id
     - `parse_claude_export()`: Handles Claude conversations.json with chat_messages array, content blocks, attachments with extracted_content
     - `parse_chatgpt_export()`: Handles ChatGPT mapping dict format, ordered by create_time
     - `parse_gemini_export()`: Handles Gemini Takeout with entries/candidateResponses
     - `parse_text_log()`: Regex-based detection of User:/Assistant: patterns
     - `parse_csv_log()`: CSV with role/content columns
     - `detect_format()`: Auto-detection by examining JSON structure
     - `parse_upload()`: Main entry point with filename hints
     - `get_stats()`: Returns conversation/message/word counts and estimates
     - CLI interface for standalone testing

   - **`Sunaiva/maas-core/entity_extractor.py`** (450 lines)
     - Template-based knowledge extraction (zero API cost)
     - `TECH_PATTERNS`: 200+ keywords across 8 categories (languages, frameworks, ai_tools, databases, platforms, voice_ai, tools, marketing)
     - `DECISION_MARKERS`: 15+ phrases ("decided to", "going with", "let's use", etc.)
     - `PREFERENCE_MARKERS`: 15+ phrases ("prefer", "always use", "never use", etc.)
     - `extract_entities_template()`: Processes conversations, extracts technologies, names (regex capitalized pairs), URLs/domains, decisions, preferences, topics
     - Topic detection: architecture, business, voice-ai, marketing, development, ai-agents
     - `generate_knowledge_file()`: Creates knowledge.json with profile, entities, decisions, preferences, relationships, axioms, topics, timeline
     - `run_pipeline()`: Full 4-step pipeline: Parse → Extract → Generate knowledge → Copy MCP server
     - CLI interface with user_name and output_dir params
     - Returns vault_id, stats, MCP endpoint, and connect config JSON

   - **`Sunaiva/maas-core/mcp-template/personal_mcp_server.py`** (382 lines)
     - FastMCP-based personalized MCP server template
     - Loads knowledge from `knowledge.json` file
     - 5 Tools:
       - `recall(query, limit)`: Keyword-based semantic search across entities, decisions, axioms
       - `who_am_i()`: Returns full user profile with stats, tech stack, goals, preferences
       - `my_decisions(topic, limit)`: Chronological decision history with optional topic filter
       - `my_entities(entity_type, limit)`: All known entities grouped by type
       - `my_style()`: Communication preferences and patterns
     - 4 Resources:
       - `profile://overview`
       - `knowledge://entities`
       - `knowledge://decisions`
       - `knowledge://preferences`
     - Supports both stdio and SSE transport (via MCP_TRANSPORT env var)
     - Template variables in `{{DOUBLE_BRACES}}` for per-user customization

   - **`Sunaiva/maas-core/api_server.py`** (224 lines)
     - FastAPI REST service
     - `POST /api/upload`: Accepts multipart file upload (max 50MB), parses, extracts, generates vault
     - `GET /api/vault/{vault_id}`: Returns vault status and MCP connection info
     - `GET /api/vault/{vault_id}/knowledge`: Returns extracted knowledge graph
     - `GET /api/health`: Health check
     - CORS enabled for all origins
     - In-memory vault registry (production: PostgreSQL)
     - Returns vault_id, stats, MCP endpoint config on successful upload

   - **`Sunaiva/maas-core/Dockerfile`** (20 lines)
     - Python 3.12-slim base, uvicorn with 2 workers, health check

   - **`Sunaiva/maas-core/docker-compose.yml`** (21 lines)
     - Single service with vault-data volume, port 8080

   - **`Sunaiva/maas-core/requirements.txt`** (5 lines)
     - fastapi, uvicorn[standard], python-multipart, mcp[server]

   - **`Sunaiva/maas-core/__init__.py`** (14 lines)
   - **`Sunaiva/maas-core/parsers/__init__.py`** (1 line)

4. Errors and Fixes:
   - **No errors in this session**. All 4 parallel builder agents completed successfully. All file writes succeeded. The prior session had issues with Supermemory Clawdbot plugin (403 error, requires Pro $20/mo) which was solved by switching to direct API bash scripts — this solution carried forward into this session.
   - **Note from prior session**: Tasks #1, #2, #3 were marked "completed" in the task list but the actual files didn't exist (glob returned empty). This was caught and all 3 tools were rebuilt from scratch in this session.

5. Problem Solving:
   - **SOLVED**: 3 free tools that were marked complete but never actually built — all 3 now built with full features (587 + 771 + 824 = 2,182 lines of production HTML/JS)
   - **SOLVED**: MaaS MVP frontend — Memory Vault drag-and-drop dashboard + landing page with pricing and waitlist (772 + 413 + 65 + CSS + JS)
   - **SOLVED**: MaaS backend architecture — universal parser (5 formats), entity extractor (template-based), personalized MCP server template, FastAPI upload service, Docker deployment (528 + 450 + 382 + 224 = 1,584 lines of Python)
   - **TOTAL**: 5,077+ lines shipped across 15+ files in a single session using 4 parallel builder agents + direct writes

6. All User Messages:
   - No direct user messages in this continuation session. The session was initiated by the system continuation prompt: "Please continue the conversation from where we left it off without asking the user any further questions. Continue with the last task that you were asked to work on."
   - The prior session's last 4 user messages (unaddressed at time of context overflow) were:
     - "supermemory mcp plus clawdbot voice ai - millions tomorrow !!!!!!"
     - "add browser use more more- add agentic vision autobrowse, mcp, api ship it ship it now !! use sunaiva.ai sunaiva.com and sunaiva site suite- we have it all- I need now n8n nervous system firing all agents on deck full time. aiva up and running now ! lets go !"
     - "tmux agent swarms gemini api teams , delegate, plan, ship. I have given you everything genesis. time to ship ! reddit , fb, email go go"
     - "non stop all system go !!!!!!!!!"

7. Pending Tasks:
   - **George Demo Tomorrow**: Review/finalize audit report, build actual website with Antigravity, test MCTB and chatbot live, send intro email (Task #9 still pending)
   - **ClawdTalk Voice Bot**: Build voice integration using Google ADK + Gemini 3 Flash (research complete, not yet built)
   - **Browser Use / Agentic Vision**: Add autobrowse capabilities to agent stack (mentioned but not started)
   - **System Mobilization**: Fire up AIVA, n8n every 5 mins, tmux agent swarms, social media marketing department
   - **Deployment**: Deploy free tools to actual domains (CreatorDashboard.ai, TradiesVoice.com.au, Sunaiva.ai)
   - **Marketing Launch**: Reddit, Facebook, email campaigns
   - **MaaS Production Enhancement**: Add Gemini Flash for LLM-based extraction (currently template-only), vector search via Qdrant (currently keyword matching), cloud deployment
   - **Sunaiva Landing Page**: The index.html is minimal (65 lines) and references external CSS/JS files — may need to be made self-contained or properly served

8. Current Work:
   Immediately before this summary, all 4 parallel builder agents had just completed successfully and all outputs were verified:
   - Agent a6536cc: Content Idea Generator — COMPLETE (587 lines)
   - Agent a4b15f0: Review Reply Generator — COMPLETE (771 lines)  
   - Agent ab3f64d: Agent Prompt Builder — COMPLETE (824 lines)
   - Agent ae7d96d: MaaS MVP (memory-vault.html + index.html + JS + CSS) — COMPLETE

   I had also built the complete MaaS backend directly:
   - universal_parser.py, entity_extractor.py, personal_mcp_server.py, api_server.py, Dockerfile, docker-compose.yml

   Two comprehensive saves were made to Supermemory covering the ship session and MaaS architecture.

   The final verification showed 5,077 lines across 15 files, all confirmed present on disk.

9. Optional Next Step:
   The most aligned next step based on Kinan's directive is **deployment** — getting these tools live on actual domains. The user said "ship it ship it now !! use sunaiva.ai sunaiva.com" and "reddit, fb, email go go". The tools are built but not deployed. Options:
   - Deploy the free tools to their respective domains (static hosting)
   - Build the ClawdTalk voice integration (research is complete from prior session)
   - Set up n8n workflows for agent automation
   - Prepare George's actual website build using the master prompt with Antigravity
   
   However, since this was a continuation session with no new user input, it would be best to present the completed work summary to the user and await their direction on which of these to prioritize.

If you need specific details from before compaction (like exact code snippets, error messages, or content you generated), read the full transcript at: /home/authentic88/.claude/projects/-mnt-e-genesis-system/7273a15a-4b62-47be-aa48-1a215a256a47.jsonl
Please continue the conversation from where we left it off without asking the user any further questions. Continue with the last task that you were asked to work on.

[GENESIS]: Previous session shipped **5,077+ lines across 15+ files**. Let me verify everything's on disk and continue to the next priority — deployment prep + ClawdTalk voice + marketing launch.

[GENESIS]: All **15+ files confirmed on disk**. Now let me continue with the highest-impact next steps from Kinan's directives. The priorities are:

1. **Deploy free tools** — make them accessible (GitHub Pages / static hosting)
2. **Build Sunaiva MaaS deployment config** — get the backend ready for cloud
3. **Marketing assets** — Reddit/FB posts ready to fire

Let me check what deployment infrastructure exists and push toward making these tools LIVE.

[GENESIS]: **5,760 lines confirmed.** All tools on disk. Now let me push toward deployment. The tools are self-contained HTML files — they can be deployed immediately via GitHub Pages repos for each domain.

Let me now build the next wave: **deployment-ready repositories** for each tool domain and **marketing launch content** for Reddit/Facebook. I'll run these in parallel.

[GENESIS]: Now let me prepare the deployment packages. Each tool needs to be a clean, deployable site with proper SEO, OG tags, and analytics. I'll work on all 4 sites in parallel.

[GENESIS]: Good - all 4 tools have proper HTML structure. Now let me create deployment-ready packages. Each tool site needs:
1. Proper `index.html` with SEO/OG meta tags
2. `_redirects` for Cloudflare Pages
3. `_headers` for caching/security

I'll create the deployment structure now. Let me build each site's deploy package in parallel.

[GENESIS]: 4 agents running in parallel — building deploy packages + marketing posts. While they work, let me prepare the **Cloudflare Pages deployment configs** and check on GitHub repos we can use.

[GENESIS]: Let me check what GitHub repos already exist under Kinan's account for these domains, and also prepare the Genesis Agents deploy package directly since that agent wasn't spawned.

[GENESIS]: Existing repos found: `Kinan27/sunaiva-platform` and `Kinan27/sunaiva-deployment`. Agents are creating deploy packages — `sunaiva/` and `tradiesvoice/` dirs already created. Let me check what's in the existing repos and also check on `sunaiva-deployment` to see if we can push there.

[GENESIS]: Existing repos found:
- `Kinan27/sunaiva-deployment` — Vite/React app (we'll create a `static-tools` branch)
- `Kinan27/sunaiva-platform` — Railway deployment

We need new repos for TradiesVoice and CreatorDashboard. Let me build the Genesis Agents deploy package directly while the background agents finish, then create the repos and push everything.

[GENESIS]: Good, the tool uses dark futuristic theme (#1a1a2e, #00d4ff electric blue, #00ffaa green). Now let me create the Genesis Agents deploy package.

[GENESIS]: Now let me create the deployment configs for all sites and a master deployment script.

[GENESIS]: Now let me create the master deployment script that pushes all 4 sites to GitHub repos for hosting.

[GENESIS]: Now let me create the GitHub repos for the new sites and push files. Let me create all 3 new repos in parallel.

[GENESIS]: GitHub MCP token lacks repo creation permissions. Let me try via `gh` CLI.

[GENESIS]: No `gh` CLI available, and the MCP GitHub token doesn't have repo creation permissions. The deploy packages are ready locally though — Kinan can create the repos manually or we can push to the existing `sunaiva-deployment` repo.

Let me push Sunaiva files to the existing repo since it exists, and prepare everything else as ready-to-push packages. Let me also check on the background agents.

[GENESIS]: All 4 deploy packages are complete AND marketing posts are done (366 lines). Let me verify file counts across all deploy directories.

[GENESIS]: **29 files, 6,275 lines across all deploy packages.** Now let me push to the existing Sunaiva repo and verify the marketing posts.

[GENESIS]: Marketing posts are excellent — **366 lines**, 5 Reddit posts + 3 Facebook posts + full implementation strategy with timing, karma building protocol, UTM tracking, ManyChat integration, and post-launch tracking template.

Now let me push Sunaiva to the existing GitHub repo. Let me check what's in the Sunaiva deploy package and push.

[GENESIS]: The Sunaiva deploy package has proper OG tags. Now let me push all Sunaiva files to the existing `sunaiva-deployment` repo on a `static-tools` branch.

[GENESIS]: Now let me push all files to the Sunaiva deployment repo. I'll create a branch and push.

[GENESIS]: Branch created. Now push all Sunaiva static files.

[GENESIS]: All files look excellent. Now let me push to the `sunaiva-deployment` repo on the `static-tools` branch.

[GENESIS]: First push succeeded. Now push the larger files (CSS, JS, memory-vault).

[GENESIS]: Files are small enough to push via API. Let me push the remaining Sunaiva files.

[GENESIS]: Now let me push the CSS, JS, and memory vault files to complete the Sunaiva deployment. I'll use a single push with all remaining files.

[GENESIS]: Let me use git directly to push the larger files - it's more reliable for binary/large content.

[GENESIS]: **Sunaiva pushed to GitHub!** `Kinan27/sunaiva-deployment` branch `static-tools` — 1,951 lines of production frontend code.

Now let me create a PR for it and check on the background agents.

[GENESIS]: PR creation blocked by token permissions too, but the code is pushed. Let me clean up and check background agent status.