Video to SRT

Workflow

1. Create a new top-level task folder for the request in the workspace.
2. Locate the user's local media file and confirm the language choice only if it is unclear.
3. Run scripts/run_local_subtitles.sh from this skill folder.
4. Default to --language zh and --model small. Switch to --language auto for mixed language audio. Switch to --model medium only when the user wants better accuracy and accepts slower runtime.
5. Inspect the generated .srt file by checking the first and last few cues before handing it off.
6. Return the subtitle path and mention that editors which accept SRT, including Jianying desktop, can import it.

Stable Defaults

• Keep dependency installation inside a local virtual environment created by scripts/run_local_subtitles.sh.
• Keep caches local to the skill folder. This avoids macOS cache permission issues.
• Keep HF_HUB_DISABLE_XET=1 enabled. This avoids a common Hugging Face Xet download failure.
• Prefer SRT. It is the simplest subtitle format for broad editor compatibility.
• Override VENV_DIR, HF_HOME, or XDG_CACHE_HOME only when reusing an existing environment or model cache is helpful.

Commands

Use the wrapper script for the normal path:

scripts/run_local_subtitles.sh "/absolute/path/to/video.mp4" --output-dir "/absolute/path/to/task/output" --copy-next-to-input

Use these common variants:

scripts/run_local_subtitles.sh "/absolute/path/to/video.mp4" --language auto --output-dir "/absolute/path/to/task/output" --copy-next-to-input
scripts/run_local_subtitles.sh "/absolute/path/to/video.mp4" --model medium --output-dir "/absolute/path/to/task/output" --copy-next-to-input

Validation

• If the wrapper needs to install packages or download a model, request permission when required by the environment.
• Confirm that the final .srt exists.
• Preview the first and last cues with sed -n '1,24p' and tail -n 24.
• If the user wants a faster import workflow, keep a copy beside the source media with --copy-next-to-input.

Resources

• scripts/run_local_subtitles.sh: create or reuse a local virtual environment, install dependencies, configure stable cache paths, and run transcription.
• scripts/transcribe_to_srt.py: transcribe media and write timecoded SRT output.
• scripts/requirements.txt: minimal dependency list for the workflow.