Requirements
- Target platform
- OpenClaw
- Install method
- Manual import
- Extraction
- Extract archive
- Prerequisites
- OpenClaw
- Primary doc
- SKILL.md
Marketing intelligence pipeline - gather signals from RSS, X/Twitter, Telegram, and Gmail newsletters. Generate daily posts, weekly summaries, and monthly de...
Marketing intelligence pipeline - gather signals from RSS, X/Twitter, Telegram, and Gmail newsletters. Generate daily posts, weekly summaries, and monthly de...
Hand the extracted package to your coding agent with a concrete install brief instead of figuring it out manually.
I downloaded a skill package from Yavira. Read SKILL.md from the extracted folder and install it by following the included instructions. Then review README.md for any prerequisites, environment setup, or post-install checks. Tell me what you changed and call out any manual steps you could not complete.
I downloaded an updated skill package from Yavira. Read SKILL.md from the extracted folder, compare it with my current installation, and upgrade it while preserving any custom configuration unless the package docs explicitly say otherwise. Then review README.md for any prerequisites, environment setup, or post-install checks. Summarize what changed and any follow-up checks I should run.
A marketing intelligence pipeline that aggregates signals from multiple sources, stores them in SQLite, and generates content for personal branding.
RSS feeds โ SQLite database (rss_db.py) X/Twitter โ SQLite database (x_monitor.py) Telegram channels โ SQLite database (telegram_monitor.py) Gmail newsletters โ Signal extraction (newsletter_monitor.py) Daily signals โ Draft posts Weekly synthesis โ Theme analysis Monthly deep-dive โ Essay/book chapter
signal-pipeline/ โโโ SKILL.md # This file โโโ README.md # Setup instructions โโโ requirements.txt # Python dependencies โโโ daily_signals.py # Main script (daily/weekly/monthly) โโโ rss_db.py # RSS feed storage โโโ x_monitor.py # X/Twitter monitoring โโโ telegram_monitor.py # Telegram channel scraping โโโ newsletter_monitor.py # Gmail newsletter extraction
# Install dependencies cd skills/signal-pipeline pip install -r requirements.txt # Run daily signals python daily_signals.py # Generate weekly summary python daily_signals.py --weekly # Generate monthly report python daily_signals.py --monthly
Edit rss_db.py to add your feed URLs: new_feeds = [ ('Feed Name', 'https://example.com/feed.xml'), ]
Edit telegram_monitor.py: CHANNELS = ['channel_name_1', 'channel_name_2']
Edit x_monitor.py: MONITOR_URLS = [ 'https://x.com/username/status/123456789', ]
The newsletter_monitor.py uses gog CLI. Ensure it's configured: gog gmail search 'newer_than:30d label:newsletter'
Python 3.8+ feedparser>=6.0.0 beautifulsoup4>=4.12.0 requests>=2.31.0 httpx>=0.25.0
Three SQLite databases are created: rss_db.db - RSS articles x_monitor.db - X/Twitter data telegram_db.db - Telegram posts
Content Creation - Daily signals for X/LinkedIn posts Market Research - Track industry trends Competitive Intelligence - Monitor competitors Personal Branding - Build content streak Book Writing - Compile monthly insights
Open source - free to use and modify.
Workflow acceleration for inboxes, docs, calendars, planning, and execution loops.
Largest current source with strong distribution and engagement signals.