Probe the source. Preserve width, height, and frame rate unless the user explicitly requests a delivery conversion.
Transcribe with the installed video-use/helpers/transcribe.py using volc.seedasr.auc and word timestamps. Reuse its cached normalized JSON.
Run scripts/prepare_transcript.py with references/default-glossary.json. It must create review.md, precut-review.srt, corrected-script.md, uncertain-terms.md, and subtitle-approval.json.
Give the user the source video plus precut-review.srt and the readable review. Correct only well-supported terminology. Never guess an uncertain model or product name. Stop here and wait for explicit user approval. Do not build an EDL or render a cut while approval is pending.
Resolve uncertain terms by adding confirmed mappings to a job-local copy of the glossary, then rerun preparation so both the script and pre-cut SRT are regenerated together. Preparation always resets approval. After the user confirms the regenerated SRT, set subtitle-approval.json to approved: true, record the confirmation time, and leave unresolved_terms empty. Never keep approval across regeneration.
Write optional decisions.json for semantic deletions. Delete repeated starts and failed takes before their later complete version; preserve unique meaning. Use normalized word indexes only inside artifacts, never in the user-facing report.
Run scripts/build_edl.py with the approval file. The script must refuse to continue unless subtitles are approved and all uncertainty is resolved. Its default pacing keeps pauses up to 550 ms, compresses longer pauses to 380-450 ms, removes only unambiguous 呃/额, and pads source head/tail. Do not replace this with blanket deletion of every pause above 200 ms.
Run scripts/render_cut.py without transitions to create a hard-cut preview. It preserves source dimensions/fps, applies 15 ms audio fades at every cut, uses light dialogue cleanup, and performs two-pass loudness normalization to -16 LUFS / -1.5 dBTP. Stronger denoise or gates are candidates, not defaults: reject a candidate when the same ASR alignment test drops by more than 0.01 or falls below 0.90.
Run scripts/analyze_visual_cuts.py on the hard-cut preview. Inspect its contact sheet and use only its recommended 80-120 ms transitions, capped at three per video. Rerender with --transitions only when a valid semantic cut also has a large visual discontinuity. Do not add blanket transitions.
Run scripts/qc.py against the chosen clean final MP4 and pass it the same transition JSON when transitions were used. Require matching dimensions/fps, valid audio/video, expected duration, and loudness within the gate. Inspect both the general and transition contact sheets.
Run scripts/generate_final_subtitles.py against the exact final MP4 and approved corrected-script.md. It delegates timing/alignment to ra-audio-to-subtitles and refuses delivery unless caption-qc.json is PASS. ASR is the timing source; approved script text is the display source. Never reuse precut-review.srt after timeline edits.
When the deliverable needs visible subtitles, run skill-captions with the final captions.json and PASS caption-qc.json. Use anchor-dark unless the contract selects another style. Preview a representative frame, burn the derivative, and require caption-render-qc.json to pass. Keep the clean rough cut and portable SRT.

Commands

SKILL_DIR="<this skill directory>"
JOB="<engineering job directory>"
WORDS="$JOB/transcripts/<source-name>.json"

python3 "$SKILL_DIR/scripts/prepare_transcript.py" \
  "$WORDS" --out-dir "$JOB/transcript-review" \
  --glossary "$SKILL_DIR/references/default-glossary.json"

python3 "$SKILL_DIR/scripts/build_edl.py" \
  <source.mp4> "$WORDS" --out "$JOB/edl.json" \
  --approval "$JOB/transcript-review/subtitle-approval.json" \
  --decisions "$JOB/decisions.json"

python3 "$SKILL_DIR/scripts/render_cut.py" \
  "$JOB/edl.json" --out "$JOB/local-hard-cut-preview.mp4"

CODEX_PY="$HOME/.cache/codex-runtimes/codex-primary-runtime/dependencies/python/bin/python3"
"$CODEX_PY" "$SKILL_DIR/scripts/analyze_visual_cuts.py" \
  "$JOB/local-hard-cut-preview.mp4" --edl "$JOB/edl.json" \
  --out-dir "$JOB/visual-cut-qc"

python3 "$SKILL_DIR/scripts/render_cut.py" \
  "$JOB/edl.json" --out "$JOB/local-benchmark.mp4" \
  --transitions "$JOB/visual-cut-qc/visual-cut-qc.json"

python3 "$SKILL_DIR/scripts/qc.py" \
  <source.mp4> "$JOB/local-benchmark.mp4" \
  --edl "$JOB/edl.json" \
  --transitions "$JOB/visual-cut-qc/visual-cut-qc.json" \
  --out-dir "$JOB/qc"

python3 "$SKILL_DIR/scripts/generate_final_subtitles.py" \
  "$JOB/local-benchmark.mp4" \
  --script "$JOB/transcript-review/corrected-script.md" \
  --approval "$JOB/transcript-review/subtitle-approval.json" \
  --out-dir "$JOB/captions"

"$CODEX_PY" ".claude/skills/skill-captions/scripts/render_captions.py" \
  "$JOB/local-benchmark.mp4" "$JOB/captions/captions.json" \
  --qc "$JOB/captions/caption-qc.json" --style anchor-dark \
  --out "$JOB/local-benchmark-captioned.mp4" \
  --preview "$JOB/qc/caption-preview.png" --preview-at 15

Omit --decisions when no semantic repeats or failed takes exist.

Decision gates

Prefer missed filler over lost meaning.
Treat transcript correction and playback deletion as separate operations.
Do not create an EDL while subtitle approval is false or unresolved terms remain.
Treat precut-review.srt as source-timeline review material only.
Do not burn captions while caption-qc.json is absent or not PASS.
Do not accept audio cleanup whose same-input ASR coverage regresses by more than one percentage point, even when it sounds superficially quieter.
Do not add transitions to every cut; a transition requires both a valid semantic boundary and measured visual discontinuity.
Do not call a rough-cut subtitle timeline production-ready.
Do not deliver when cut-qc.json reports fail.
Keep intermediates in 01-内容生产/视频工作台/制作中/<日期-主题>/; archive only the user-approved final under 视频工作台/已制作/月上旬或月下旬/日期-主题/.

Read references/artifact-contract.md when integrating another renderer or modifying artifact schemas.

ra-local-talking-head-cut

本地口播精剪

Required workflow