Documents
One-command AI product launch monitoring pipeline. Use when the user wants to track, discover, or analyze new AI product launches, releases, or announcements. Runs four stages automatically - RSS feed monitoring, web search enrichment, page screenshots, and trend analysis/scoring. Outputs a markdown report and structured JSON. Triggers on phrases like monitor AI product launches, track AI releases, AI launch report, what new AI products launched, product hunt AI monitoring, AI news roundup.
One-command AI product launch monitoring pipeline. Use when the user wants to track, discover, or analyze new AI product launches, releases, or announcements. Runs four stages automatically - RSS feed monitoring, web search enrichment, page screenshots, and trend analysis/scoring. Outputs a markdown report and structured JSON. Triggers on phrases like monitor AI product launches, track AI releases, AI launch report, what new AI products launched, product hunt AI monitoring, AI news roundup.
End-to-end pipeline that collects AI product launches from RSS feeds, enriches them with web search, captures screenshots, and scores trends — all in one command.
python3 scripts/monitor.py --output ./output -v
This runs all four stages and produces output/report.md + output/launches.json.
| Stage | What it does |
|---|---|
| 1. RSS monitoring | Fetches AI/tech RSS feeds, filters for launch signals, dedupes |
| 2. Product search | Enriches each launch with web search results (Brave API or DDG fallback) |
| 3. Screenshots | Headless Chromium screenshots of each product page via Playwright |
| 4. Trend analysis | Categorizes, scores, and ranks launches; generates report |
# Default run (3-day lookback, all stages)
python3 scripts/monitor.py --output ./output
# Custom lookback window
python3 scripts/monitor.py --days 7 --output ./weekly
# Use a config file
python3 scripts/monitor.py --config assets/default-config.json --output ./output
# Override feeds
python3 scripts/monitor.py --feeds https://example.com/feed.xml https://other.com/rss
# Skip screenshots (faster, no browser needed)
python3 scripts/monitor.py --no-screenshots --output ./quick
# Verbose mode
python3 scripts/monitor.py -v --output ./output
Copy assets/default-config.json and customize:
{
"feeds": ["https://..."],
"query_terms": ["AI product launch"],
"days": 3
}
BRAVE_API_KEY — set to use Brave Search API (better results). Without it, falls back to DuckDuckGo HTML scraping.report.md — human-readable trend report with category breakdown, top launches, and full entry listlaunches.json — structured data for downstream automationscreenshots/*.png — page screenshots (named by URL hash)feedparser, requests, beautifulsoup4 (auto-installed)playwright + Chromium (for screenshots; skip with --no-screenshots)Install Playwright browsers:
python3 -m playwright install chromium
Each launch gets a trend score (0–100+):
Categories: LLM/Foundation Models, Image/Video Gen, Agent/Automation, Developer Tools, Enterprise/B2B, Consumer/App, Healthcare/Science, Other.
When using this skill in an agent workflow:
--output pointing to a temp or workspace directoryreport.md for a summary to present to the userlaunches.json for structured data (e.g., filtering by category or score threshold)One-click AI product launch monitoring pipeline. Use when tracking new AI product releases, monitoring competitor launches, generating trend reports from tech RSS feeds, or running automated product discovery. Integrates RSS monitoring, product info enrichment, screenshot capture, and trend analysis into a single command. Triggers on "product radar", "AI launch monitor", "track new AI products", "product release tracking", "AI trend report", or similar product intelligence workflows.
Continuously monitor topics across web search, RSS/Atom feeds, and GitHub releases, alerting only when relevant.
Tracks product launch buzz and reactions on Twitter using apidojo's Twitter Search scraper. Triggers when the user asks to: track product launch buzz on Twitter, monitor Twitter reactions to a product launch, measure product launch sentiment on X, find tweets about a new product release, track how a product launch is being received on Twitter, monitor competitor product announcements on Twitter, or analyze the social media impact of a product launch. Returns tweet volume, sentiment distribution, top voices, geographic spread, and buzz score. Ideal for product marketing teams, PR professionals, and competitive analysts monitoring launches.
Generate a daily AI news digest newsletter from fresh web sources. Use this skill whenever a user asks for AI news, wants a roundup or summary of recent AI/ML developments, asks what happened in artificial intelligence today or this week, requests a newsletter, briefing, or digest of model releases, research papers, funding rounds, product launches, regulation, or benchmark results — even if they don't explicitly say "newsletter." Also use for follow-up requests like "more AI news" or "catch me up on AI."
Route a technology-intelligence request to a technology landscape, invention-mining workflow, or current-intelligence briefing, and produce an evidence-backed English HTML report. Use for emerging AI, semiconductor, display, electronics, or other fast-moving technology domains when the user needs route evolution, competitor positioning, invention opportunities, patent mining, or multi-source monitoring.
Search the web for a topic and produce a structured summary with key findings, sources, and actionable takeaways. Best for quick research briefs, competitive landscape scans, and topic overviews.