Toby Quirk

I automated my content engine and 2 hrs/day dropped to 10 min [ what’s new in v2 ]: - 9 platforms scraped while I sleep → 2,000+ topics/day - a 5-signal scoring brain that filters down to the 10 that matter - voice DNA writer.. same tone, different structure every time - a self-learning loop that remembers every approve and decline - profile DNA — knows exactly what goes viral on MY account v1 was a brain with no body v2 has eyes, a filter, and memory + fully automated Here’s how to build it step-by-step ↓ [ The architecture]: /content-engine ├── scrapers/ (9 platform scrapers) ├── extension/ (chrome ext for X, linkedin, reddit) ├── ai/ │ ├── ranker.py (5-signal scoring brain) │ ├── content_writer.py (voice DNA + structures) │ ├── profile_analyzer.py (your positioning DNA) │ └── sentiment_analyzer.py ├── publisher/ (export + time slot scheduling) ├── gui/dashboard.py (streamlit command center) ├── ingest_server.py (local server on localhost) └── data/content_engine.db (everything stored locally) let me walk you through each layer ↓ LAYER 1: Research engine 9 sources scanned 24/7 (X, reddit, YT, HN, github, trends + chrome ext for reddit and linkedin) every post you scroll past gets tagged and stored locally LAYER 2: Scoring brain every topic scored on 5 signals: - freshness (0.20) - velocity (0.25) - virality (0.25) - relevance (0.20) - uniqueness (0.10) velocity 8+ → forced min score of 7. catches late bloomers that suddenly explode 2,000 topics → top 10 ranked LAYER 3: Voice DNA writer not one structure every time. system picks the format: - short take - tactical playbook - QT contrast - contrarian - resource drop - proof post a voice guardian auto-rewrites anything that fails: lowercase ratio, no hashtags, no corporate words LAYER 4: Dashboard Streamlit dark theme. 5 tabs review queue = tinder for content. swipe approve, swipe decline LAYER 5: Publishing no auto-posting. zero account risk approve → pick a slot (8am / 12pm / 5pm) → exports a .txt → copy / paste / post also auto-drafts a linkedin version of every approved tweet LAYER 6: Self-learning loop every click logged. weekly the system embeds your decline notes and re-tunes the scoring brain month 1: you approve 30% month 3: 70% pre-filtered month 6: 10 min/day LAYER 7: Profile DNA analyzes your past tweets. tells you exactly which pillars, formats, and hooks perform best on YOUR account the scoring brain uses it to prioritize what already works for you daily run: open dashboard → 10 min reviewing → post 3x → close total cost: ~$15/month everything else: local, sqlite, no cloud, no subscription unfortunately I couldn’t paste in long-form format initial description which was made before but if this hits 2,000 likes I drop the full build guide with every prompt you need to ship it in claude code reply "ENGINE" + RT and I'll DM you access to test it (follow me first so I can write) save this so you don't lose it