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Agent Skill · 开发

tellers(tellers 视频)

tellers 用于辅助视频、动画、脚本化剪辑和多媒体生成流程,适合在 OpenClaw 中需要整理视频素材、生成脚本或维护合成项目时使用。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。

tellers 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 6,876。

总安装 4,260周安装 174GitHub Stars 1下载 1,378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
1.0.2

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:tellers(tellers 视频)
来源仓库:https://github.com/yxdunc/tellers
安装命令:
openclaw skills install tellers
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 tellers

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。

使用 Tellers.ai 创建、编辑和共享 AI 生成的视频 — Tellers.ai 是一个 AI 视频平台,聚合了领先的一代模型(Kling、Veo、LTX、ElevenLabs 等)

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 tellers;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

tellers 怎么安装?

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

tellers 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。

tellers 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。

tellers 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。

tellers 用的人多吗?

公开数据是累计安装 4,260 次,近一周安装 174 次,下载 1,378 次,GitHub 1 星。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。

tellers 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
tellers

tellers 视频 · 本页

4,2601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
tellers
description
Create, edit, and share AI-generated videos using tellers.ai — an AI video platform that aggregates leading generation models (Kling, Veo, LTX, ElevenLabs, and more) for video, image, and music. Use when a user wants to upload and edit real or user footage, generate videos from scratch using stock footage or AI models, add overlays, subtitles, music, or effects, create news summaries, highlight reels, promos, or custom client videos, share or export a finished video. Also handles uploading media, checking processing status, making assets public, and any tellers CLI operation. Triggers on phrases like 'create a video', 'make a highlight reel', 'upload footage to tellers', 'generate a summary video', 'create an edit', 'add subtitles', 'use stock footage', 'share a video preview', 'export video', 'tellers'.

Tellers Skill

Tellers.ai is a video creation platform. The tellers CLI lets you upload media and generate AI-produced videos via a conversational agent.

Installation

1. Install the CLI

brew tap tellers-ai/tellers && brew install tellers

2. Get an API key

Go to app.tellers.ai → user menu (top right) → API keys → Create new. Credits are required. New Google SSO users get free starter credits.

3. Configure

# Required
export TELLERS_API_KEY=sk_...

Add the export to your shell profile (~/.zshrc, ~/.bashrc) to persist it.

Workflow 1: Upload Media (non-blocking)

Always spawn an isolated subagent for uploads — they can take minutes and shouldn't block the main session.

# The blocking command (run inside a subagent):
tellers upload upload /path/to/footage \
  --show-status-until-analysed \
  --machine-readable

OpenClaw pattern for uploads:

sessions_spawn({
  task: "Run this command and report the full JSON output when it finishes:\
\
tellers upload upload \"/path/to/footage\" --show-status-until-analysed --machine-readable\
\
Parse the JSON and reply with the asset_ids on success.",
  runtime: "subagent"
})

The subagent announces the result when done. Extract asset_ids from the output to use in generation.

Output (parsed from subagent result):

{
  "success": true,
  "elapsed_seconds": 161,
  "assets": [
    {"asset_id": "abc123", "local_path": "/path/to/file.mp4", "status": "success"}
  ]
}

Upload options:

--show-status-until-analysed       # Wait until AI analysis done (recommended)
--show-status-until-done           # Wait until transcoding done too
--disable-description-generation   # Skip AI time-based descriptions (faster)
--force-upload                     # Re-upload even if already tracked
--parallel-uploads 4               # Concurrent uploads (default: 4)
--ext mp4 --ext mov                # Filter by extension
--in-app-path "shoots/2026-03"     # Organise in-app path

Workflow 2: Generate a Video (long-running)

Video generation runs the tellers AI agent and can take 5–20 minutes. Always run generation inside an isolated subagent — never block the main session.

# Blocking command: waits until agent finishes, prints the final JSON result
tellers --background --json-response "Generate a 90-second news summary video from today's footage"

Output (on completion):

{
  "assets": [{"id": "abc123", "type": "video"}],
  "chat_id": "88425c45-d302-4af2-89d6-e72d7bd13239",
  "message": "...",
  "projects": ["7781484c-c396-44b3-a7b0-5dda23f33bef"],
  "status": "done"
}

Extract projects[0] as the project ID and chat_id to build the result URL.

OpenClaw pattern for generation: Spawn an isolated subagent with the full blocking command. The subagent waits however long it takes and announces the result (preview link) when done. The main session stays free.

sessions_spawn({
  task: "Run this command and report the result when it finishes:\
\
tellers --background --json-response \"<prompt>\"\
\
Parse the JSON output and reply with the project ID and chat_id so the URL can be constructed.",
  runtime: "subagent"
})

The tellers.json_result SSE event carries the final output. The --background --json-response flags extract and print it automatically.

Workflow 3: Combined Upload + Generate

Common pattern for "upload these videos and make an edit":

  1. Spawn subagent for upload → wait for it to finish and return asset_ids
  2. Spawn a second subagent for generation with the asset context

Both steps use isolated subagents. Upload must complete before generation starts (asset needs to be processed first).

# Step 1 — spawn upload subagent, wait for result
upload_result = sessions_spawn({
  task: "Run: tellers upload upload \"/path/to/footage\" --show-status-until-analysed --machine-readable\
Report the full JSON output.",
  runtime: "subagent"
})
# → extract asset_ids from result

# Step 2 — spawn generation subagent with context
sessions_spawn({
  task: "Run: tellers --background --json-response \"Create a highlight reel from asset_id: <id>\"\
Report the full JSON output including project IDs.",
  runtime: "subagent"
})

Other CLI Commands

# Interactive chat REPL (for exploration)
tellers "your prompt"

# Single response, no REPL
tellers --no-interaction "your prompt"

# List assets
tellers asset list

# Export a project to have a rendered and downloadable mp4 file
tellers project export <project-id>

Result URL

After upload or generation, construct the app link from the returned IDs:

https://app.tellers.ai/?asset_id={asset_id or project_id}&chat_id={chat_id}

Examples:

# After upload — link to the asset:
https://app.tellers.ai/?asset_id=1830d8d9-c64a-4941-bf24-bcba9acdb2e0

# After generation — link to the project with chat context:
https://app.tellers.ai/?asset_id=7781484c-c396-44b3-a7b0-5dda23f33bef&chat_id=88425c45-d302-4af2-89d6-e72d7bd13239

Always surface this URL to the user when a generation or upload completes.

Sharing & Public Previews

By default assets and projects are private. To share a public preview link:

# Make an asset or project publicly accessible
tellers asset set-anonymous-read {id}

# Public preview URL (shareable with anyone, no login required):
https://www.tellers.ai/preview/{asset_id}

For maximum device compatibility (especially mobile), don't share the project preview directly. Instead:

  1. Export the project first — this renders a proper MP4: tellers project export <project-id>
  2. The export produces a new asset ID
  3. Make that asset public: tellers asset set-anonymous-read <export-asset-id>
  4. Share: https://www.tellers.ai/preview/<export-asset-id>

Project previews may not play on all devices; exported assets always will.

Credits & Support

Every upload, export, and generation request spends Tellers credits. To buy more, go to app.tellers.ai and click "Get more tokens".

Questions or issues:

Error Handling

  • Exit code 0 = success
  • Exit code 1 = error (check stderr)
  • HTTP 401 = bad/missing API key
  • HTTP 402 = insufficient credits — direct user to app.tellers.ai to top up

Reference

Full API docs: https://www.tellers.ai/docs/dev/api CLI source: https://github.com/tellers-ai/tellers-cli OpenAPI spec: src/tellers_api/openapi.tellers_public_api.yaml in the repo

平台分布

OpenClaw

87.46%
按下载量换算1,205

安全审计

VirusTotal

通过

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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