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- YouTube Content Pipeline: Automated video idea scouting with X/Twitter integration - Personal CRM: Contact discovery and meeting prep automation - AI Earnings Tracker: Tech earnings monitoring and summaries - Knowledge Base (RAG): Searchable repository of saved content - Health & Symptom Tracker: Food and symptom logging with pattern analysis - Multi-Channel Assistant: Unified interface across Telegram, Slack, Google Workspace All use cases verified in daily production use by @matthewberman
49 lines
1.9 KiB
Markdown
49 lines
1.9 KiB
Markdown
# YouTube Content Pipeline
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As a daily YouTube creator, finding fresh, timely video ideas across the web and X/Twitter is time-consuming. Tracking what you've already covered prevents duplicates and helps you stay ahead of trends.
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This workflow automates the entire content scouting and research pipeline:
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• Hourly cron job scans breaking AI news (web + X/Twitter) and pitches video ideas to Telegram
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• Maintains a 90-day video catalog with view counts and topic analysis to avoid re-covering topics
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• Stores all pitches in a SQLite database with vector embeddings for semantic dedup (so you never get pitched the same idea twice)
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• When you share a link in Slack, OpenClaw researches the topic, searches X for related posts, queries your knowledge base, and creates an Asana card with a full outline
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## Skills you Need
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- `web_search` (built-in)
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- [x-research-v2](https://clawhub.ai) or custom X/Twitter search skill
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- [knowledge-base](https://clawhub.ai) skill for RAG
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- Asana integration (or Todoist)
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- `gog` CLI for YouTube Analytics
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- Telegram topic for receiving pitches
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## How to Set it Up
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1. Set up a Telegram topic for video ideas and configure it in OpenClaw.
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2. Install the knowledge-base skill and x-research skill.
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3. Create a SQLite database for pitch tracking:
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```sql
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CREATE TABLE pitches (
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id INTEGER PRIMARY KEY,
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timestamp TEXT,
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topic TEXT,
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embedding BLOB,
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sources TEXT
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);
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```
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4. Prompt OpenClaw:
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```text
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Run an hourly cron job to:
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1. Search web and X/Twitter for breaking AI news
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2. Check against my 90-day YouTube catalog (fetch from YouTube Analytics via gog)
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3. Check semantic similarity against all past pitches in the database
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4. If novel, pitch the idea to my Telegram "video ideas" topic with sources
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Also: when I share a link in Slack #ai_trends, automatically:
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1. Research the topic
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2. Search X for related posts
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3. Query my knowledge base
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4. Create an Asana card in Video Pipeline with a full outline
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```
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