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Generate YouTube chapter markers from transcript content.
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Baseado na classificação ocupacional SOC
| name | video-chapters |
| description | Generate YouTube chapter markers from transcript content. |
Generate YouTube chapter markers by reading the transcript and identifying topic boundaries. No script — do this by reading the transcript and reasoning about where topics change.
All outputs go in <project_root>/claude-edits/.
<project_root>/claude-edits/
<video_stem>_chapters.txt # YouTube-format chapter list
<video_stem>_chapters.json # Structured chapter data with timeline times
_analysis.json or _review.md)Chapters reference source timestamps, but the edited video has cuts. To map:
# Build map from EDL kept segments
timeline_pos = 0.0
for seg in kept_segments:
if source_time >= seg["start"] and source_time <= seg["end"]:
timeline_time = timeline_pos + (source_time - seg["start"])
timeline_pos += seg["end"] - seg["start"]
_chapters.txt (paste directly into YouTube description):
0:00 Introduction
0:42 The Just File
1:48 Running Scripts with AI Agents
...
_chapters.json (for Resolve markers):
{
"chapters": [
{"source_time": 0.0, "title": "Introduction", "timeline_time": 0.0},
{"source_time": 51.3, "title": "The Just File", "timeline_time": 42.0}
]
}
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