pluviobyte/rnskill

ra-local-talking-head-cut

Produce a polished local talking-head or narrated screen-recording rough cut without a cloud editor.

First seen Jul 27, 2026

Installation

$ npx skills add pluviobyte/rnskill --skill ra-local-talking-head-cut

Summary

  • Produce a polished local talking-head or narrated screen-recording rough cut without a cloud editor.
  • Use when Codex must clean Chinese or mixed Chinese-English speech, correct product terminology before semantic editing, compress pauses without making speech breathless, preserve source resolution and frame rate, normalize dialogue loudness, generate final-audio subtitle artifacts, or benchmark local output against ChatCut/video-use/chengfeng/AI剪口播.

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More details

Agent compatibility

Declared targets from SKILL.md / docs. Unmarked agents are not listed — the skill may still install via the CLI.

Claude Code Declared
Cursor Not declared
Codex Not declared
GitHub Copilot Not declared
Windsurf Not declared
Gemini CLI Not declared
Cline Not declared
OpenCode Not declared

Repository health

Stars 1.5K
License LICENSE
Default branch main
Open issues 0
Status Active

Skill metadata

Parsed from SKILL.md frontmatter.

Declared agents claude-code

Package contents

Files included with this skill beyond the listing page.

  • skill md SKILL.md 7,198 B
  • docs SUMMARY.md 491 B

History

  1. First seen on skills.sh
  2. First recorded snapshot · 156 installs

SKILL.md

本地口播精剪

Deliver a reproducible local workflow, not an editing product. Keep upstream skills untouched and write every job under the source project's engineering directory.

Required workflow

  1. Probe the source. Preserve width, height, and frame rate unless the user

explicitly requests a delivery conversion.

  1. Transcribe with the installed video-use/helpers/transcribe.py using

volc.seedasr.auc and word timestamps. Reuse its cached normalized JSON.

  1. 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.

  1. 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.

  1. 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.

  1. 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.

  1. 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.

  1. 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.

  1. Run scripts/analyzevisualcuts.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.

  1. 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.

  1. Run scripts/generatefinalsubtitles.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.

  1. 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](references/artifact-contract.md) when integrating another renderer or modifying artifact schemas.