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video-short-creator视频短片创作者

Agent Skill

用于辅助视频生成、动画合成、脚本化剪辑或 Remotion 等视频项目开发。它适合让 Agent 组织镜头、生成素材说明、维护合成代码或排查渲染问题。使用时需要确认分辨率、时长、素材路径和导出格式;涉及外部素材、人物肖像或商业发布时,应先核对版权授权和内容审核要求。

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安装说明

本站只整理中文说明和来源信息,不托管安装包,也不代用户安装。

GitHub

来源数

2

许可证

MIT-0

最后核验

2026-05-01

来源状态

来源可访问

安装方式

通过对话安装

复制提示词发给支持本地命令或 Skills 的 AI 助手,先确认命令和权限,再让它执行。

请帮我安装这个 Agent Skill:video-short-creator(视频短片创作者)
来源仓库:https://github.com/jessy-huang/video-short-creator
安装命令:
openclaw skills install video-short-creator
安装前请先检查当前环境是否支持对应 CLI,并向我确认将要执行的命令、安装目录、联网范围和文件读写权限;确认后再执行。

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复制命令到本机终端执行。该命令会通过 OpenClaw 从第三方来源获取 Skill;本站只展示命令,不托管安装包,也不自动执行。

ClawHubOpenClaw
openclaw skills install video-short-creator

简介

两阶段 AI 叙述短片生成器,含人工审核环节。

  • 首先生成 TTS 旁白,再合成配套视觉素材。
  • 上传源材料,设定时长与平台偏好,输出成片预览。
  • 采用 edge-tts 技术保障语音自然度与本地化体验。
  • 最终成片需通过人工检查方可正式发布。video-short-creator 属于研究检索类 Skill,可作为该场景下的辅助能力补充。

SKILL.md

name
video-short-creator
description
Two-phase AI-narrated video short creator with human review checkpoints. Phase 1 analyzes source materials, generates TTS narration via edge-tts, and exports a subtitle review sheet for user approval. Phase 2 assembles the final video with FFmpeg including clipping, scaling, xfade transitions, SRT subtitle burning, and audio merge. Use when creating a short-form video with AI voiceover from existing video clips and a script, especially for tech/AI paper explanation videos for social media.

Video Short Creator

Two-phase workflow for creating AI-narrated short videos from source clips and a script, with human review at every critical step.

Prerequisites

ToolPurposeInstall
FFmpegVideo processingwinget install FFmpeg or download from ffmpeg.org
Python 3.8+Script executionUse the managed runtime
edge-ttsMicrosoft TTSpip install edge-tts (no API key needed)
SimHei fontChinese subtitle renderingUsually pre-installed on Windows (C:\Windows\Fonts\simhei.ttf)

Phase 1: Material Preparation & Review

This phase generates the narration audio and exports a review sheet. Stop and wait for user approval before proceeding.

Step 1.1: Analyze Materials

  1. Ask the user for:

- Source video clips (paths or a folder) - Script / narration text (or generate one from provided reference material) - Target resolution (default: 1920x1080 landscape) - Voice preference (default: zh-CN-YunxiNeural, young male Mandarin) - Publishing platform (optional, affects aspect ratio recommendations)

  1. Scan all source clips with ffprobe to catalog:

- Resolution, duration, file size - Generate a clip inventory table

  1. If no script is provided but reference material (paper URL, markdown, etc.) is given:

- Research the content and draft a narration script - Structure as 3-5 segments with natural flow

Step 1.2: Build SCRIPT Data Structure

Create a Python list of segment dicts that maps each narration segment to source clips:

SCRIPT = [
    {
        "id": "seg1",          # unique segment ID
        "text": "...",         # narration text for this segment
        "videos": [            # source clips to use
            {"file": "clip1.mp4", "start": 0, "max_dur": 14},
            {"file": "clip2.mp4", "start": 5, "max_dur": 30},
        ],
    },
    # ... more segments
]

Key design decisions:

  • Each segment's total available video duration should exceed narration duration by ~0.5s
  • Use multiple clips per segment for visual variety
  • max_dur prevents over-long clips from a single source

Step 1.3: Generate TTS & Export Review Sheet

Run scripts/step1_generate_review.py with the SCRIPT config:

python scripts/step1_generate_review.py

This script:

  1. Generates TTS audio for each segment using edge-tts
  2. Extracts clean subtitle timing from SentenceBoundary events (NOT WordBoundary)
  3. Exports subtitle_review.md with all subtitle entries + timing info

Step 1.4: Present Review Materials to User

Display the following for user review:

  1. Clip Inventory - All source clips with metadata
  2. Script Review - Full narration text organized by segment
  3. Subtitle Review Sheet (subtitle_review.md) - All subtitle entries with:

- Sequence number, segment ID, start/end time, duration, text content

  1. Segment-to-Clip Mapping - Which clips are used for each narration segment

Ask the user to review and confirm or provide modifications:

  • Text corrections in narration or subtitles
  • Timing adjustments
  • Clip substitutions or reorderings
  • Adding/removing subtitle entries
CRITICAL: Do NOT proceed to Phase 2 until the user explicitly approves.

Phase 2: Video Assembly

Only start after user approval of Phase 1 materials.

Step 2.1: Apply User Edits (if any)

If the user provided subtitle edits:

  1. Parse their feedback and update the subtitle entries accordingly
  2. If they created a subtitle_edited.txt, load it (format: start_sec|end_sec|text per line)
  3. Re-verify that all source clip paths exist

Step 2.2: Execute Video Assembly

Run scripts/step2_edit_video.py:

python scripts/step2_edit_video.py

The assembly pipeline:

  1. Clip & Scale - Extract clips at specified start/duration, scale to target resolution (1920x1080)
  2. Concatenate - Join multiple clips per segment using concat demuxer
  3. Burn Subtitles - Overlay subtitles using .srt file + FFmpeg subtitles filter
  4. xfade Transitions - Chain segments with alternating fade/fadeblack transitions (0.8s)
  5. Build Audio - Concatenate narration segments with short silences between them
  6. Final Merge - Combine video + audio into final output

Step 2.3: Output

  • Final video at output/{PROJECT_NAME}_FINAL.mp4
  • Resolution: 1920x1080, 30 FPS
  • Subtitle style: SimHei font, size 14, white text, thin outline, bottom-aligned (movie-style)
  • Audio: AAC 128kbps
  • Video: H.264 CRF 20

Step 2.4: Present Final Video

Use open_result_view to present the final video. Ask user for feedback on:

  • Subtitle readability and positioning
  • Transition smoothness
  • Audio-video sync
  • Overall pacing

Configuration

All configuration lives in the SCRIPT data structure at the top of each script. Key constants:

ConstantDefaultDescription
VOICEzh-CN-YunxiNeuraledge-tts voice (Mandarin, young male)
TARGET_W/H1920x1080Output resolution
XFADE_DUR0.8Transition duration in seconds
SUBTITLE_FONT_SIZE14Subtitle font size
SUBTITLE_MARGIN_V50Bottom margin for subtitles

Known Pitfalls (Windows)

  • Never use drawtext filter — shell escaping for `\

and special characters is unreliable on Windows. Always use .srt file + subtitles` filter instead.

  • SRT file paths need escaping for FFmpeg subtitles filter: replace \ with / and : with \:.
  • edge-tts SentenceBoundary gives clean text; WordBoundary may contain artifacts like stray n characters.
  • Always re-fetch subtitle timing even when audio files are cached — edge-tts does not store boundary events.
  • xfade filter labels must use tmp0, tmp1 format (not v01, v02) to avoid FFmpeg parsing errors.
  • For detailed pitfalls and debugging guidance, see references/ffmpeg-pitfalls.md.

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