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Given a YouTube video ID or URL, runs the same caption-extraction +
LLM-analysis pipeline the watcher uses in prod, then prints the
extracted tickers + actions sorted by action priority and conviction
descending. No DB writes, no Redis publish — strictly observational.
Two entry points:
- scripts/analyze_kevin_video.py — pure Python; needs yt-dlp +
Anthropic OAuth token in env. Local laptop yt-dlp tends to hit
"Sign in to confirm you're not a bot" rate-limits; running inside
a cluster pod avoids this.
- scripts/kevin-analyze.sh — wrapper that finds the running
trading-bot-workers pod and execs the Python script in the
meet-kevin-watcher container. Easiest invocation.
Example:
$ ./scripts/kevin-analyze.sh poUJIZRmFew
=== Meet Kevin analysis — poUJIZRmFew ===
Market outlook: bullish
TICKERS (12):
SYMBOL ACTION CONV HORIZON RATIONALE
APPF buy 85.0% long_term Apploven's looking fantastic ...
SOX buy 80.0% months Semiconductor ETF momentum ...
...
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|---|---|---|
| .. | ||
| __init__.py | ||
| analyze_kevin_video.py | ||
| kevin-analyze.sh | ||
| seed_sample_data.py | ||
| seed_strategies.py | ||
| smoke_test.sh | ||