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Agent Skill · 开发

vibbit-skills(维比特技能)

vibbit-skills 用于处理图像、截图、视觉识别或图片素材相关工作,适合在 OpenClaw 中需要让 Agent 分析图片、整理视觉素材或辅助图像流程时使用。可结合来源仓库、安装命令和原始 README 继续核验具体用法。安装前建议确认权限范围、维护状态,以及是否会触发联网、命令执行或文件读写。

vibbit-skills 是开发类 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,按安装量在开发类的 21,746 个 Skill 里排第 6,565。

总安装 4,563周安装 194GitHub Stars 公开资料未说明下载 1,599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
1.0.9

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:vibbit-skills(维比特技能)
来源仓库:https://github.com/zgissing/vibbit-skills
安装命令:
openclaw skills install vibbit-skills
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 vibbit-skills

这个 Skill 是做什么的

开发类 Skill 面向写代码、改代码和排查问题,一般会读写仓库文件,部分还会执行构建或测试命令。

调用 Vibbit OpenAPI 实现 AI 图像生成与短视频解析。适用于抖音、小红书等平台链接解析与病毒视频分析。支持头像查询、内容分类与跨平台素材抓取。vibbit-skills 属于开发类 Skill,可作为该场景下的辅助能力补充。

安装命令:openclaw skills install vibbit-skills。注意第三方 API 调用频率限制与数据隐私条款。

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 vibbit-skills;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

vibbit-skills 怎么安装?

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

vibbit-skills 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。

vibbit-skills 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。

vibbit-skills 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。

vibbit-skills 用的人多吗?

公开数据是累计安装 4,563 次,近一周安装 194 次,下载 1,599 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。

vibbit-skills 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。
  • 需要处理开发类任务、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。

开发类 Skill 对比

6 个同类
Skill总安装GitHub 星权限许可证扫描
skill-vetter

技能审查员 · OpenClaw

8,779,018986操作浏览器MIT-0通过
ontology

本体论 · OpenClaw

6,636,960576只读MIT-0通过
entra-app-registration

内部应用程序注册 · Codex、Claude

6,631,872764接触敏感数据未明确通过
entra-app-registration

内部应用程序注册 · Codex、Claude

3,757,680201接触敏感数据未明确通过
nano-banana-pro

纳米香蕉专业版 · OpenClaw

3,526,898364接触敏感数据MIT-0有提醒
vibbit-skills

维比特技能 · 本页

4,563—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
vibbit-skills
version
1.0.9
display_description
|
description
Call Vibbit OpenAPI to complete five capabilities — AI image generation, parse Douyin/Xiaohongshu/Bilibili links, viral video breakdown, query available avatar list, initialize avatar voiceover video workflow. When users say "generate an image / AI image", "parse this Douyin/Xiaohongshu/Bilibili link", "break down this viral video / video breakdown", "show me my avatars / list avatars", or "use XX avatar for voiceover / initialize avatar video / avatar voiceover", this skill should be triggered proactively, even if the user doesn't explicitly mention "vibbit" or "openapi". As long as the task maps to one of these five capabilities and the user is working with the Vibbit/willing-agentcy system, prioritize this skill over writing HTTP requests manually.
metadata
openclaw
primaryEnv
VIBBIT_API_KEY
requires
env
anyBins
envVars
required
true
description
Vibbit platform API Key, get it from https://app.vibbit.ai/api-keys
required
false
description
API base URL, defaults to https://openapi.vibbit.cn, use this to switch to test environments

Vibbit OpenAPI Skill

Wraps Vibbit OpenAPI's five capabilities into a Node.js CLI so Claude doesn't need to write HTTP calls manually each time. Two are synchronous APIs (submit and get results immediately), and three are asynchronous APIs (script auto-polls until COMPLETED/FAILED).

When to Trigger

Trigger this skill when the user's request matches any of the following:

User Intent (Examples)Task TypeSync?
"Generate an image", "AI draw a cat", "create image"AIGC_IMAGE_GENERATIONAsync
"Parse this Douyin link", "What's this Xiaohongshu link about"PARSE_CONTENT_URLAsync
"Break down this viral video", "Video breakdown", "Analyze this product video"VIDEO_BREAKDOWNAsync
"What avatars do I have", "List available avatars"QUERY_DIGITAL_HUMAN_LISTSync
"Use XX avatar for voiceover", "Initialize avatar video", "Avatar voiceover"DIGITAL_HUMAN_ORAL_BROADCASTSync

Do not use this skill for any scenarios outside these five.

Prerequisites

The user's shell must have these environment variables exported:

  • VIBBIT_API_KEY — Bearer token issued by Vibbit platform, required, script exits with error if missing
  • VIBBIT_BASE_URL — Optional, defaults to production https://openapi.vibbit.cn; export this variable to override for other environments (test/staging)

When VIBBIT_API_KEY is missing, tell the user to get it from https://app.vibbit.ai/api-keys, and after they get it, help them configure it; don't guess or skip.

Node.js 18+ required (uses built-in fetch). The script gets material metadata via remote API https://tools.vibbit.ai/api/file-info, no WASM or npm dependencies needed. If the system has ffprobe (comes with ffmpeg), it will automatically be used as a fallback probe method, but it works fine without it.

Script Path

Script directory: $VIBBIT_SKILL_DIR = ~/.claude/skills/vibbit-skills/scripts, main entry is $VIBBIT_SKILL_DIR/vibbit.js. The $VIBBIT_SKILL_DIR in examples below is for readability only; use the actual absolute path when calling.

Standalone Usage: scripts/vibbit.js is a self-contained single file with no npm dependencies. Copy it to any Node 18+ machine and run directly, not limited to ~/.claude/skills/. If the system has ffprobe, it can optionally be auto-enabled, but it works fine without it.

How to Call

Always use the bundled CLI, don't call HTTP APIs directly. This is important because the wire format has several gotchas:

  1. input_info.input is an already-stringified JSON (double-encoded), not a nested object
  2. All fields use snake_case (task_type, input_info, digital_human_id, etc.)
  3. oral_broadcast's material_list requires complete file_info structure for each element (including file_size / mime_type / width / height / duration, etc.), which the script auto-detects and generates
node $VIBBIT_SKILL_DIR/vibbit.js <subcommand> [--args]

On success, the script writes JSON to stdout: sync tasks return {"result": ...}, async tasks return {"task_id": "...", "result": ...}; on failure, it outputs {"error": "..."} and exits with non-zero code. After getting stdout, parse out useful fields first, then present to the user in natural language; don't dump raw JSON to the user.

Subcommands

1. AI Image Generation — gen_image

node $VIBBIT_SKILL_DIR/vibbit.js gen_image \
  --prompt "a cute orange cat sitting on a window sill, studio ghibli style" \
  [--ref-url https://cdn.example.com/ref.jpg]
  • --prompt required. Translate/copy the user's words as-is; don't add embellishments unless the user explicitly asks for refinement
  • --ref-url optional, reference image

The script submits and auto-polls; the final result usually contains the generated image URL, give the URL directly to the user.

2. Parse Link — parse_url

node $VIBBIT_SKILL_DIR/vibbit.js parse_url \
  --url "https://v.douyin.com/xxxxxxx"

Supports Douyin/Xiaohongshu/Bilibili share links. result typically contains original video URL, title, description, ASR subtitles. Only show fields the user cares about, don't dump everything.

3. Viral Video Breakdown — breakdown

node $VIBBIT_SKILL_DIR/vibbit.js breakdown \
  --video-url "https://cdn.example.com/video.mp4" \
  --sub-tasks asr,hot,bgm
  • --video-url required. Can pass share links (Douyin/Xiaohongshu/Bilibili) or raw MP4 URLs directly; breakdown includes parsing capability internally, no need to call parse_url first
  • --sub-tasks required, comma-separated, options:

- asr — Speech to text - transition — Transition analysis - hot — Viral hooks analysis - bgm — Background music - If user doesn't specify, default to asr,hot, and tell the user what you chose so they can correct

Breakdown tasks are slow, 1-2 minutes is normal. During the wait, proactively tell the user "Analyzing video, please wait" so they know it's running, not stuck.

4. Query Avatar List — list_digital_humans

node $VIBBIT_SKILL_DIR/vibbit.js list_digital_humans

Synchronous API. Returns available avatar configurations for the current user (tenant-level + shared + personal). When presenting to the user, at least show names, list by group, let the user directly say "use XX", don't make them manually enter IDs.

5. Initialize Avatar Voiceover — oral_broadcast

node $VIBBIT_SKILL_DIR/vibbit.js oral_broadcast \
  --message "Hello everyone, today I'll introduce a new product..." \
  --digital-human-id 10001 \
  [--title "New Product Launch"] \
  [--material-url https://cdn.example.com/a.mp4 \
   --material-name "Product A Shot.mp4" \
   --material-url https://cdn.example.com/b.jpg \
   --material-name "Packaging Close-up.jpg"]
  • --message required. Both chat message and preset script — backend automatically sets has_script to true, whatever text the user passes will be used as the video voiceover script verbatim, LLM won't rewrite it
  • --digital-human-id required. If user doesn't specify which one, call list_digital_humans first to let them choose, then continue
  • --title optional. If passed, it's used as the preset title, skipping the LLM auto-title generation step; if not passed, backend calls the model to generate as usual
  • --material-url optional, repeatable. Each item only passes URL, file_name defaults to auto-inferred from URL tail.
  • --material-name optional, repeatable. If passed, must match the count of --material-url, corresponding in order of appearance. Use this when the user provides friendly names (e.g., OSS key is gibberish, display name has specific requirements); can omit entirely if not needed.

Before calling oral_broadcast in any case, B-roll image generation must be completed first. Whether the script is user-provided or generated and confirmed in conversation, always run gen_image first, get the image URLs, then submit the voiceover. Unless the user explicitly says "no B-roll" or "no images", this step cannot be skipped.

Synchronous API. The returned result is a string URL pointing to the frontend chat page (production and demo domains differ). When returning to the user, present in the following format, don't use other wording:

All set for you
Topic: {voiceover title or first 10 chars of script}
Avatar: {avatar name}
B-roll Materials: {N} images total (omit this line if no materials)
Check it out, and if it looks good, generate the video 👉 {URL}

Capability Combinations

  • User says "help me make a voiceover" but doesn't provide a script → First ask "What topic do you want this video to cover?", help write a voiceover script based on the topic, show it to the user for confirmation; after script is confirmed, if no avatar is selected yet, list avatars for the user to choose; after selection, automatically chain B-roll generation + voiceover (same as the flow below)
  • User says "help me make a avatar voiceover" but doesn't specify avatar, and already has a script → First list_digital_humans, present options to the user, wait for them to choose before continuing
  • User says "help me make a voiceover" and provides a script, or there's already a confirmed script in context → Must generate B-roll first, then submit voiceover, cannot skip:

1. Based on the script topic, automatically infer 3-4 B-roll scene descriptions, call gen_image sequentially to generate (no need for user to describe scenes additionally) 2. Collect all successfully generated image URLs (skip failures, don't block the flow) 3. Include images as --material-url in oral_broadcast, submit together 4. Return result in new format (including B-roll count)

  • User says "help me replicate this video" / "viral replication" + share link → Go through complete replication flow:

1. parse_url to parse the link, get title + ASR subtitles 2. Show the original video script (restored from ASR subtitles) to the user 3. Extract the original video's hook structure, rhythm, core selling points from subtitles, use the same logic to recreate a voiceover script (not copy, but recreate), show to the user 4. Ask "Which script to use? Or want to modify?", wait for user confirmation before continuing 5. Based on script topic, automatically infer 3-4 B-roll scenes, run gen_image in parallel 6. Submit script + successfully generated B-roll together to oral_broadcast 7. Return result in unified format

  • User asks "what can you do" / "what features" / "how to use" → Reply:

> I can help you with these: > > - Make voiceover videos — If you have a script, I'll make it directly; if not, tell me the topic and I'll write it > - Replicate viral videos — Drop a Douyin/Xiaohongshu/Bilibili link, and I'll make one for you > - Break down videos — Analyze why a video went viral, where the hooks are, how the rhythm flows > - Generate B-roll — Auto-generate images based on voiceover content > - Check avatars — See which avatars you can use > > What would you like to do?

  • First interaction: If the user has no clear task intent after installation or update (e.g., just greeting, saying "hi", "hello", "start", etc.), proactively reply with the feature introduction above to guide the user to choose what they want to do
  • User drops a Douyin share link saying "analyze this viral video" → Directly call breakdown, pass the share link, no need to call parse_url first
  • User only wants to know the content of a share link (not analysis) → parse_url is enough
  • User wants the original link/download address of a video → Call parse_url, extract the original video URL from the result and give to the user
  • User mentions a reference image URL when doing AI image generation → Use gen_image --ref-url, don't mistakenly trigger parse_url or breakdown

Error Handling

  • Missing API Key → Tell the user: "Need to configure Vibbit API Key first to continue. Get it here: https://app.vibbit.ai/api-keys, then tell me and I'll help you configure it.", don't guess or skip
  • HTTP 401/403 → Tell the user: "API Key has expired, please get a new one from https://app.vibbit.ai/api-keys and reconfigure"
  • Task failed → Tell the user the task didn't succeed, suggest contacting Vibbit support with the task link; don't dump raw error messages to the user
  • Wait timeout (over 10 minutes) → Tell the user: "Video is still processing, may need more time. Contact support with your task link: {chat page URL returned by oral_broadcast}"

Don't Do These

  • Don't write curl / fetch yourself — always use vibbit.js. snake_case + double-stringified JSON + file_info structure are traps that easily cause bugs when written manually
  • Don't dump complete raw JSON responses to the user, extract key fields (URL, title, transcription, etc.) and present in natural language
  • Don't make up avatar IDs or video URLs, ask the user if they don't provide them

平台分布

OpenClaw

71.97%
按下载量换算1,151

安全审计

VirusTotal

通过

ClawScan

通过

Static analysis

可疑

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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