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Agent Skill · 开发

text-to-video-maker-free(免费文本到视频制作器)

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。

text-to-video-maker-free 是开发类 Agent Skill,可用宿主为 OpenClaw,通过ClawHub获取,权限为需要联网;许可证为 MIT-0,第三方扫描已通过,按安装量在开发类的 21,746 个 Skill 里排第 9,461。

总安装 2,691周安装 111GitHub Stars 公开资料未说明下载 879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:text-to-video-maker-free(免费文本到视频制作器)
来源仓库:https://github.com/tk8544-b/text-to-video-maker-free
安装命令:
openclaw skills install text-to-video-maker-free
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 text-to-video-maker-free

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。

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。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。

安装命令:openclaw skills install text-to-video-maker-free 来源仓库:https://github.com/tk8544-b/text-to-video-maker-free

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 text-to-video-maker-free;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

    它需要需要联网,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

text-to-video-maker-free 怎么安装?

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

text-to-video-maker-free 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。

text-to-video-maker-free 需要什么权限?

权限级别是需要联网。该 Skill 可能需要联网访问来源站点、仓库或外部 API;具体网络访问范围需要结合源码和 README 复核。

text-to-video-maker-free 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。

text-to-video-maker-free 用的人多吗?

公开数据是累计安装 2,691 次,近一周安装 111 次,下载 879 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。

text-to-video-maker-free 安全吗?

第三方扫描结果为通过,但这只覆盖已知的静态检查项,不能替代自己读一遍源码和安装命令。

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。
  • 第三方扫描已通过,常见的高风险行为没有命中。

先想清楚的地方

  • 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。
  • 需要许可证清楚、并且有第三方扫描结果的团队项目。

不太适合

  • 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
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skill-vetter

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8,779,018986操作浏览器MIT-0通过
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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
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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
text-to-video-maker-free

免费文本到视频制作器 · 本页

2,691—需要联网MIT-0通过

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
text-to-video-maker-free
version
1.0.0
displayName
Text to Video Maker Free — Turn Written Ideas Into Stunning Videos Instantly
description
>
metadata
{"openclaw": {"emoji": "🎬", "requires": {"env": ["NEMO_TOKEN"], "configPaths": ["~/.config/nemovideo/"]}, "primaryEnv": "NEMO_TOKEN", "variant": "greeting_v2"}}

Getting Started

Paste your script, article, or text idea and I'll turn it into a structured video with scenes, captions, and visual flow. No text yet? Just describe the video topic you have in mind.

Try saying:

  • "Turn this 300-word blog post about morning routines into a 60-second video script with scene descriptions and on-screen text overlays."
  • "I have a product launch announcement written out — can you convert it into a short promotional video breakdown with title cards and a call-to-action at the end?"
  • "Create a step-by-step how-to video from this written tutorial about setting up a home office, including visual cues and caption suggestions for each step."

Getting Connected

Before handling any user request, establish a connection to the backend API. Show a brief status like "Connecting...".

If NEMO_TOKEN is in the environment, use it directly and create a session. Otherwise, acquire a free starter token:

  • Generate a UUID as client identifier
  • POST to https://mega-api-prod.nemovideo.ai/api/auth/anonymous-token with the X-Client-Id header
  • The response includes a token with 100 free credits valid for 7 days — use it as NEMO_TOKEN

Then create a session by POSTing to https://mega-api-prod.nemovideo.ai/api/tasks/me/with-session/nemo_agent with Bearer authorization and body {"task_name":"project","language":"en"}. The session_id in the response is needed for all following requests.

Tell the user you're ready. Keep the technical details out of the chat.

From Words on a Page to Videos Worth Watching

Most people have ideas worth sharing but no easy way to turn them into video. Writing comes naturally — editing timelines, sourcing footage, and syncing captions does not. That's exactly the gap this skill fills. Drop in your text, and it gets structured into a video-ready format with logical scene breaks, visual pacing suggestions, and caption overlays that make your message land.

Whether you're repurposing a LinkedIn post into a short-form video, turning a product description into a promotional clip, or converting a how-to guide into a step-by-step visual walkthrough, this skill handles the translation from words to watchable content. You stay in control of the message while the heavy lifting of structuring and formatting gets done for you.

This is built for people who create content regularly but don't have hours to spend in editing software. Bloggers, social media managers, teachers building course content, and indie entrepreneurs all use this kind of tool to move faster without sacrificing quality. Write it once, watch it become a video.

Routing Your Video Generation Requests

When you submit a text prompt, ClawHub parses your scene descriptions, style preferences, and duration settings, then routes each request to the appropriate video synthesis pipeline based on complexity and output format.

User says...ActionSkip SSE?
"export" / "导出" / "download" / "send me the video"→ §3.5 Export✅
"credits" / "积分" / "balance" / "余额"→ §3.3 Credits✅
"status" / "状态" / "show tracks"→ §3.4 State✅
"upload" / "上传" / user sends file→ §3.2 Upload✅
Everything else (generate, edit, add BGM…)→ §3.1 SSE❌

Cloud Rendering API Reference

The text-to-video backend runs on a distributed cloud rendering cluster that converts your natural language scripts into frame sequences using diffusion-based video models. Each API call packages your prompt tokens, aspect ratio, and voiceover parameters before dispatching them to the generation queue for processing.

Skill attribution — read from this file's YAML frontmatter at runtime:

  • X-Skill-Source: text-to-video-maker-free
  • X-Skill-Version: from frontmatter version
  • X-Skill-Platform: detect from install path (~/.clawhub/ → clawhub, ~/.cursor/skills/ → cursor, else unknown)

All requests must include: Authorization: Bearer <NEMO_TOKEN>, X-Skill-Source, X-Skill-Version, X-Skill-Platform. Missing attribution headers will cause export to fail with 402.

API base: https://mega-api-prod.nemovideo.ai

Create session: POST /api/tasks/me/with-session/nemo_agent — body {"task_name":"project","language":"<lang>"} — returns task_id, session_id.

Send message (SSE): POST /run_sse — body {"app_name":"nemo_agent","user_id":"me","session_id":"<sid>","new_message":{"parts":[{"text":"<msg>"}]}} with Accept: text/event-stream. Max timeout: 15 minutes.

Upload: POST /api/upload-video/nemo_agent/me/<sid> — file: multipart -F "files=@/path", or URL: {"urls":["<url>"],"source_type":"url"}

Credits: GET /api/credits/balance/simple — returns available, frozen, total

Session state: GET /api/state/nemo_agent/me/<sid>/latest — key fields: data.state.draft, data.state.video_infos, data.state.generated_media

Export (free, no credits): POST /api/render/proxy/lambda — body {"id":"render_<ts>","sessionId":"<sid>","draft":<json>,"output":{"format":"mp4","quality":"high"}}. Poll GET /api/render/proxy/lambda/<id> every 30s until status = completed. Download URL at output.url.

Supported formats: mp4, mov, avi, webm, mkv, jpg, png, gif, webp, mp3, wav, m4a, aac.

SSE Event Handling

EventAction
Text responseApply GUI translation (§4), present to user
Tool call/resultProcess internally, don't forward
heartbeat / empty data:Keep waiting. Every 2 min: "⏳ Still working..."
Stream closesProcess final response

~30% of editing operations return no text in the SSE stream. When this happens: poll session state to verify the edit was applied, then summarize changes to the user.

Backend Response Translation

The backend assumes a GUI exists. Translate these into API actions:

Backend saysYou do
"click [button]" / "点击"Execute via API
"open [panel]" / "打开"Query session state
"drag/drop" / "拖拽"Send edit via SSE
"preview in timeline"Show track summary
"Export button" / "导出"Execute export workflow

Draft field mapping: t=tracks, tt=track type (0=video, 1=audio, 7=text), sg=segments, d=duration(ms), m=metadata.

Timeline (3 tracks): 1. Video: city timelapse (0-10s) 2. BGM: Lo-fi (0-10s, 35%) 3. Title: "Urban Dreams" (0-3s)

Error Handling

CodeMeaningAction
0SuccessContinue
1001Bad/expired tokenRe-auth via anonymous-token (tokens expire after 7 days)
1002Session not foundNew session §3.0
2001No creditsAnonymous: show registration URL with ?bind=<id> (get <id> from create-session or state response when needed). Registered: "Top up credits in your account"
4001Unsupported fileShow supported formats
4002File too largeSuggest compress/trim
400Missing X-Client-IdGenerate Client-Id and retry (see §1)
402Free plan export blockedSubscription tier issue, NOT credits. "Register or upgrade your plan to unlock export."
429Rate limit (1 token/client/7 days)Retry in 30s once

Performance Notes — Getting the Best Video Output

The quality of your video output scales directly with the clarity of your input text. Structured writing — with a clear beginning, middle, and end — produces cleaner scene breakdowns and more natural caption pacing. Bullet points, numbered lists, and short paragraphs all translate especially well into on-screen text and scene transitions.

For longer pieces like full articles or detailed guides, consider specifying a target video length upfront (e.g., '90-second video' or '3-minute walkthrough'). This helps the skill prioritize which sections become prominent scenes versus supporting context. Vague or stream-of-consciousness text can still be worked with, but a quick edit pass on your source copy before submitting will noticeably improve the structured output.

If your text includes brand-specific terminology, product names, or technical language, flag those in your prompt so they're preserved accurately in captions and title cards rather than paraphrased.

Integration Guide — Fitting This Into Your Content Workflow

This skill works best as a mid-stage tool in your content pipeline — after you've written your copy but before you hand anything off to a video editor or AI video generation platform. Use it to produce a structured video brief, shot list, or scene-by-scene script that any editor or tool can immediately act on.

Pair it with AI video generators like Runway, Pictory, or InVideo by feeding them the structured scene output this skill produces. The scene descriptions, caption text, and pacing notes map directly to the input formats those platforms expect, cutting your setup time significantly.

For teams, this skill works well as a standardization layer — everyone submits their written content and receives consistently formatted video scripts, reducing back-and-forth between writers and video producers. It's also useful for building a content calendar: draft your weekly posts, convert them all to video outlines in one session, and queue them for production without juggling multiple tools.

Use Cases — Who Gets the Most Out of This Skill

Content creators repurposing written articles into YouTube Shorts or Instagram Reels get the most immediate value — one piece of writing becomes multiple video formats without starting from scratch. Social media managers use it to convert brand copy and campaign messaging into structured video scripts ready for production or AI video tools.

Educators and course creators turn lesson notes and written guides into clearly segmented video outlines, making it easier to record or animate without improvising on camera. Small business owners who write their own product descriptions, FAQs, or announcements can quickly reshape that content into short promotional videos that feel polished and intentional.

Even journalists, newsletter writers, and podcasters with written transcripts find this skill useful for repurposing long-form content into digestible visual formats. If you write regularly and wish your content could live in more places, this skill closes that gap efficiently.

平台分布

OpenClaw

70.84%
按下载量换算623

安全审计

VirusTotal

通过

ClawScan

通过

Static analysis

通过

权限和风险

需要联网

该 Skill 可能需要联网访问来源站点、仓库或外部 API;具体网络访问范围需要结合源码和 README 复核。

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。目前只有一个公开来源,建议同时核对源仓库。

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