Video Transcribe

Use this skill when the user asks to understand, transcribe, summarize, or visually analyze a video/audio source.

Mode Selection

• Full note / no omission: user says 全量、完整、不要看视频、替代看视频、图文笔记, or asks about completeness. Download the source, transcribe the whole audio, extract frames, and produce a coverage-checked note.
• Audio transcript: user explicitly asks for 字幕、转录、他说了什么、transcribe. Produce a timestamped transcript or transcript-backed summary.
• Visual analysis: user explicitly asks about 画面、截图、视觉、展示了什么. Extract frames and analyze visuals; skip Groq unless speech content matters.
• Quick summary: user only wants a brief answer. Summarize, but still state whether the result is transcript-backed, frame-backed, or both.

When intent is unclear, default to transcript + keyframes for short videos and ask before spending API quota on long videos.

Core Rules

• For long-form technical content, prefer Groq whisper-large-v3 with response_format=verbose_json; do not use plain text when timestamps or completeness checks matter.
• Do not force language=zh for non-Chinese videos. Use the detected language or set --language en for English technical videos.
• Use a terminology prompt for product/tool names such as Codex, Remotion, Supabase, Typefully, TestFlight, Vercel, Claude Code.
• Source timestamps are an outline, not proof. Verify every listed timestamp has transcript coverage before claiming the note can replace watching the video.
• Do not add a personal status tag like 已读; that belongs to the user, not the agent.
• Keep full transcripts in the working directory unless the user asks to store them in the note. The published note should contain structured coverage, excerpts/paraphrase, screenshots, and validation notes.

Standard Workflow

1. Create a work directory under /tmp/video-transcribe/<slug>.
2. Download media with scripts/download_media.sh.
3. Transcribe with scripts/transcribe_groq.py when speech content is needed.
4. Extract frames with scripts/extract_frames.sh when visual context or screenshots are needed.
5. For Obsidian notes, read references/obsidian-video-note.md before writing.
6. Validate deliverables with scripts/verify_obsidian_note.sh and run touch <note> after editing an Obsidian file externally.

Example:

WORK=/tmp/video-transcribe/codex-super-app
mkdir -p "$WORK"

SKILL_DIR="$HOME/.codex/skills/video-transcribe"
# In this repo, use: SKILL_DIR=platforms/codex/skills/video-transcribe
# In Claude runtime, use: SKILL_DIR="$HOME/.claude/skills/video-transcribe"

VIDEO=$("$SKILL_DIR/scripts/download_media.sh" "$URL" "$WORK" full)

"$SKILL_DIR/scripts/transcribe_groq.py" \
  "$VIDEO" \
  --work-dir "$WORK" \
  --language en \
  --prompt "Technical terms: Codex, Remotion, Supabase, Typefully, TestFlight, Vercel, Claude Code."

"$SKILL_DIR/scripts/extract_frames.sh" \
  "$VIDEO" "$WORK/frames" --count 16

Output Standards

For a note intended to replace watching a video, use two layers:

• Readable layer: a short executive summary, key claims, reusable playbook, decisions, tools, gotchas, and screenshots.
• Coverage layer: collapsible timestamp groups or phase tables that map every source timestamp to the transcript-backed note.

Avoid a single flat list of dozens of timestamps. It is technically complete but hard to read.

Bundled Resources

• scripts/download_media.sh: yt-dlp wrapper with cookie retry and uvx --from yt-dlp fallback.
• scripts/transcribe_groq.py: media-to-audio extraction, size-based segmentation, Groq transcription, and timestamp merge. Writes transcript.txt (one segment per line), transcript_segments.json, and transcript_global.md.
• scripts/extract_frames.sh: uniform or timestamp-based keyframe extraction.
• scripts/verify_obsidian_note.sh: Markdown image/timestamp/frontmatter checks.
• references/obsidian-video-note.md: long-form Obsidian note structure and coverage standard.
• references/troubleshooting.md: common yt-dlp, Groq, ffmpeg, and note-validation failures.

Load reference files only when the current request needs that detail.