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YouTube video transcription and memory workflow.
Passed 18 of 19 test cases with the skill, and 8 of 19 without it.
and 8 more in the full report
10 fixed8 passed either way1 still failing0 broke4 errored
Tokens, turns and time describe resource use, not a dollar price.
One of 10 test cases the skill fixed. Same model, same prompt, with and without the skill.
Show the top-level Markdown heading format when recording YouTube video title 'AI Breakthroughs' into the daily note.
| Checked | Without skill | With skill |
|---|---|---|
| Uses section heading ## YouTube 转录: AI Breakthroughs. | Missed | Passed |
The instructions your model reads when the skill loads.
Before running, the agent checks for available tools and sets PATH:
# Find tools dynamically — don't hardcode paths
export PATH="/tmp/miniforge/bin:$(python3 -m site --user-base)/bin:$PATH"
YTDLP=$(command -v yt-dlp 2>/dev/null || echo "yt-dlp")
FFMPEG=$(command -v ffmpeg 2>/dev/null || echo "ffmpeg")
WHISPER=$(command -v whisper 2>/dev/null || echo "whisper")
# Verify tools exist
for TOOL in "$YTDLP" "$FFMPEG" "$WHISPER"; do
[ -x "$TOOL" ] || echo "[WARN] Tool not found or not executable: $TOOL"
done
Tool requirements:
| Tool | Install | Fallback path |
|---|---|---|
| yt-dlp | pip3 install yt-dlp | $(python3 -m site --user-base)/bin/yt-dlp |
| ffmpeg | conda install -c conda-forge ffmpeg | /tmp/miniforge/bin/ffmpeg |
| whisper | pip3 install openai-whisper | $(python3 -m site --user-base)/bin/whisper |
export PATH="/tmp/miniforge/bin:$(python3 -m site --user-base)/bin:$PATH"
URL="https://www.youtube.com/watch?v=Q5kYrmzNhcU"
test cases passed, vs 8 / 19 without
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