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Audio srt workflow

Skill Sariel2018/audio-srt-aligner/skill-only/plugins/audio-srt-skills/skills/audio-srt-workflow

Generate or align SRT subtitles from audio using this repository. Use when the user asks for subtitle generation, transcript-to-audio alignment, timing cleanup, SRT quality checks, or subtitle preview video rendering.From its SKILL.md

Install
npx -y skills add Sariel2018/audio-srt-aligner --skill audio-srt-workflow

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What its file declares

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The file declares its own license as MIT. That is the author’s claim about this one file, and it is not the same thing as the license GitHub reports for the repository, which is listed with the other numbers below.

SKILL.md

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Audio SRT Workflow

Use this skill for end-to-end subtitle work.

This package is self-contained for runtime entrypoints:

  • scripts/align_to_srt.py
  • scripts/gui_app.py
  • scripts/srt_stats.py
  • scripts/make_preview_mp4.py
  • scripts/requirements.txt

Scope

  • Mode A: audio + reference text -> aligned SRT
  • Mode B: audio only -> auto subtitle SRT
  • Timing QA with srt_stats.py
  • Burned preview generation with make_preview_mp4.py

Inputs To Collect First

  1. Audio path (wav, mp3, m4a, ...)
  2. Whether a reference transcript is available
  3. Output SRT path (or output directory)
  4. Language hint (zh, en, ...)
  5. Preferred run style: CLI, GUI, or Python API

Decision Rule

  • If transcript exists, run Mode A (align_to_srt.py --text ...).
  • If transcript does not exist, run Mode B via GUI or Python API (run_auto_subtitle_pipeline).

Workflow

  1. Validate environment and paths.
  2. Choose Mode A or Mode B by transcript availability.
  3. Run subtitle generation from packaged scripts.
  4. Run timing diagnostics (srt_stats.py).
  5. If needed, render a preview mp4 with burned subtitles.

Resolve Skill Script Path

Set a local variable to your installed skill directory.

Codex default path:

SKILL_DIR="${CODEX_HOME:-$HOME/.codex}/skills/audio-srt-workflow"

OpenClaw/ClawHub install path example:

SKILL_DIR="<your-workdir>/skills/audio-srt-workflow"

Environment Checks

Run these checks before execution:

python3 --version
ffmpeg -version
python3 -c "import faster_whisper; print('ok')"

If faster-whisper import fails:

# Review dependencies before installing:
cat "$SKILL_DIR/scripts/requirements.txt"
pip install -r "$SKILL_DIR/scripts/requirements.txt"

Mode A Command Template (Audio + Transcript)

python3 "$SKILL_DIR/scripts/align_to_srt.py" \
  --audio "<input_audio>" \
  --text "<transcript_txt>" \
  --output "<output_srt>" \
  --model small \
  --language zh

Mode B Command Template (Audio Only)

GUI:

python3 "$SKILL_DIR/scripts/gui_app.py"

Or use Python API in scripts:

  • Build config with build_alignment_config(...)
  • Run run_auto_subtitle_pipeline(...)

See command details in references/command-templates.md.

QA And Preview

Timing stats:

python3 "$SKILL_DIR/scripts/srt_stats.py" --srt "<output_srt>"

Preview video:

python3 "$SKILL_DIR/scripts/make_preview_mp4.py" \
  --audio "<input_audio>" \
  --srt "<output_srt>" \
  --output "<preview_mp4>"

Output Conventions

  • Default output uses .srt extension.
  • Prefer dated naming for batch runs (for example output_YYYYMMDD.srt).
  • Keep intermediate checks in a separate folder from final delivery files.

Notes

  • For Chinese output (zh), the pipeline strips commas/periods only.
  • If timings look off, inspect waveform snap related arguments before changing model size.
  • This skill requires explicit invocation (allow_implicit_invocation: false).

Keep looking

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