segment-combiner
Combine multiple segment detection results into a unified list. Use when you need to merge segments from different detectors, prepare removal lists for video processing, or consolidate detection outputs.
Installation
Details
Usage
After installing, this skill will be available to your AI coding assistant.
Verify installation:
npx agent-skills-cli listSkill Instructions
name: segment-combiner description: Combine multiple segment detection results into a unified list. Use when you need to merge segments from different detectors, prepare removal lists for video processing, or consolidate detection outputs.
Segment Combiner
Combines multiple segment JSON files into a single unified segments file for video processing.
Use Cases
- Merging segments from multiple detectors
- Consolidating detection results
- Preparing unified input for video-processor
Usage
python3 /root/.claude/skills/segment-combiner/scripts/combine_segments.py \
--segments /path/to/segments1.json /path/to/segments2.json \
--output /path/to/all_segments.json
Parameters
--segments: One or more segment JSON files to combine--output: Path to output combined segments JSON
Input Format
Each input file should have a segments array:
{
"segments": [
{"start": 0, "end": 120, "duration": 120},
{"start": 300, "end": 305, "duration": 5}
]
}
Output Format
{
"segments": [
{"start": 0, "end": 120, "duration": 120},
{"start": 300, "end": 305, "duration": 5}
],
"total_segments": 2,
"total_duration_seconds": 125
}
Dependencies
- Python 3.11+
Example
# Combine segments from multiple detectors
python3 /root/.claude/skills/segment-combiner/scripts/combine_segments.py \
--segments initial_silence.json pauses.json \
--output all_segments.json
Notes
- Segments are sorted by start time
- Compatible with video-processor --remove-segments input
- All input files must have
segmentsarray
More by benchflow-ai
View allDetect pauses and silence in audio using local dynamic thresholds. Use when you need to find natural pauses in lectures, board-writing silences, or breaks between sections. Uses local context comparison to avoid false positives from volume variation.
Calculate per-second RMS energy from audio files. Use when you need to analyze audio volume patterns, prepare data for silence/pause detection, or create an energy profile for audio analysis tasks.
Process videos by removing segments and concatenating remaining parts. Use when you need to remove detected pauses/openings from videos, create highlight reels, or batch process segment removals using ffmpeg filter_complex.
Extract audio from video files to WAV format. Use when you need to analyze audio from video, prepare audio for energy calculation, or convert video audio to standard format for processing.