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Agent Skill · 研究检索

video-short-creator(视频短片创作者)

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。

video-short-creator 是研究检索类 Agent Skill,可用宿主为 OpenClaw,通过ClawHub获取,权限为接触敏感数据;许可证为 MIT-0,第三方扫描有提醒项,按安装量在研究检索类的 73,675 个 Skill 里排第 33,257。

总安装 2,376周安装 101GitHub Stars 公开资料未说明下载 832核验 2026-05-01

安装说明

本站只整理中文说明,不托管安装包,也不代用户安装。
GitHub
许可证
MIT-0
版本
1.0.0

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。

命令行安装

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

这个 Skill 是做什么的

研究检索类 Skill 主要解决「找资料、核对事实、把来源整理清楚」的问题,通常会让助手先检索再总结。

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。

上手步骤

4 步
  1. 1

    确认自己的宿主工具

    公开资料标注支持 OpenClaw;先确认自己用的是其中之一,再按对应工具的 Skills 目录放置。

  2. 2

    拿到安装命令

    可以直接复制的命令是 openclaw skills install video-short-creator;命令里的占位符换成自己的路径或密钥再执行。

  3. 3

    安装后重启宿主

    命令执行完要完全退出宿主工具再打开,让新装的 Skill 被重新扫描到,否则列表里可能看不到。

  4. 4

    按最小权限试用

    它需要接触敏感数据,先在测试目录或测试账号里跑,确认没问题再放到正式项目。

常见问题

6 条

video-short-creator 怎么安装?

在终端执行 openclaw skills install video-short-creator。装完完全退出宿主工具再打开,让它重新扫描本地 Skill。

video-short-creator 支持哪些 AI 工具?

公开资料标注支持 OpenClaw。其他工具只要能读取本地 Skill 目录,一般也能手动放进去,但要自己确认触发方式是否一致。

video-short-creator 需要什么权限?

权限级别是接触敏感数据。该 Skill 可能接触密钥、Token、环境变量或敏感配置,应进入高风险复核队列,默认不自动发布。

video-short-creator 是免费的吗?

来源标注的许可证是 MIT-0。本站不代收任何费用,也不托管安装包;能否商用、要不要署名,以许可证原文为准。

video-short-creator 用的人多吗?

公开数据是累计安装 2,376 次,近一周安装 101 次,下载 832 次。这些数字来自第三方目录统计,只能当作热度参考,不代表质量或安全性。

video-short-creator 安全吗?

第三方扫描有提醒项,说明存在需要人工确认的行为。安装前请打开源码看清它读了什么、联网到哪里。

值得选的地方和要先想清楚的地方

值得选的地方

  • 专注 OpenClaw 一种宿主,触发方式和使用习惯不用来回切换。
  • 许可证明确为 MIT-0,商用和分发边界好判断。

先想清楚的地方

  • 需要接触敏感数据,装到常用环境前要先评估影响面。
  • 第三方扫描存在提醒项或未通过项,需要人工逐条确认。
  • 第三方目录整理,版本更新和行为细节以来源仓库为准。

适不适合你

更适合

  • 已经在用 OpenClaw,想直接扩展它能力的人。
  • 需要处理研究检索类任务、又不想每次都手写提示词的人。

不太适合

  • 环境里有大量密钥、凭证,不方便给第三方 Skill 读取的人。
  • 需要厂商级技术支持和 SLA 的生产系统。

研究检索类 Skill 对比

6 个同类
Skill总安装GitHub 星权限许可证扫描
find-skills

寻找技能 · Codex、Claude

31,199,81316,486操作浏览器MIT有提醒
self-improving-agent

自我改进 Agent · OpenClaw

16,464,0023,396接触敏感数据MIT-0通过
soultrace

灵魂追踪 · Codex、Claude

7,588,94412需要联网未明确有提醒
self-improving

自我完善 · OpenClaw

6,829,2841,046需要联网MIT-0通过
microsoft-foundry

微软代工厂 · Codex、Claude

6,614,144764调用外部服务未明确有提醒
video-short-creator

视频短片创作者 · 本页

2,376—接触敏感数据MIT-0有提醒

按安装量取同分类前几名;数字来自第三方目录统计,只作热度参考,不代表质量结论。

SKILL.md 原文

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.

平台分布

OpenClaw

70.72%
按下载量换算588

安全审计

VirusTotal

可疑

ClawScan

可疑

Static analysis

通过

权限和风险

接触敏感数据

该 Skill 可能接触密钥、Token、环境变量或敏感配置,应进入高风险复核队列,默认不自动发布。

安装前确认

本站仅展示第三方公开信息,不托管安装包,不提供自动安装或运行环境。安装前应自行审查源码、依赖和命令行为。来源安全扫描存在提醒或未通过项,安装前请自行复核。目前只有一个公开来源,建议同时核对源仓库。

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