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Agent Skill · 开发

free-text-to-video-generator(免费文本到视频生成器)

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。

free-text-to-video-generator 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 5,998。

总安装 5,288周安装 216GitHub Stars 公开资料未说明下载 1,693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:free-text-to-video-generator(免费文本到视频生成器)
来源仓库:https://github.com/dsewell-583h0/free-text-to-video-generator
安装命令:
openclaw skills install free-text-to-video-generator
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 free-text-to-video-generator

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。

该技能可将概念或脚本创意转为完全渲染视频。无需相机或镜头,直接生成高质量视频内容。free-text-to-video-generator 属于开发类 Skill,可作为该场景下的辅助能力补充。适用于创意表达、产品展示等视频制作需求。

安装命令:openclaw skills install free-text-to-video-generator。注意确认分辨率、时长及素材版权授权要求。

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 free-text-to-video-generator;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

free-text-to-video-generator 怎么安装?

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

free-text-to-video-generator 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。

free-text-to-video-generator 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。

free-text-to-video-generator 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。

free-text-to-video-generator 用的人多吗?

公开数据是累计安装 5,288 次,近一周安装 216 次,下载 1,693 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。

free-text-to-video-generator 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

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entra-app-registration

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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
free-text-to-video-generator

免费文本到视频生成器 · 本页

5,288—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
free-text-to-video-generator
version
1.0.0
displayName
Free Text to Video Generator — Turn Written Ideas Into Engaging Videos Instantly
description
>
metadata
{"openclaw": {"emoji": "🎬", "requires": {"env": ["NEMO_TOKEN"], "configPaths": ["~/.config/nemovideo/"]}, "primaryEnv": "NEMO_TOKEN", "variant": "greeting_v2"}}

Getting Started

Paste your script, topic, or idea and I'll turn it into a ready-to-share video right now. No footage? No problem — just describe what you want and I'll handle the rest.

Try saying:

  • "Generate a 60-second promotional video for a new coffee subscription service targeting busy professionals — upbeat tone, modern style"
  • "Create a short educational video explaining how photosynthesis works, suitable for middle school students with clear visuals and simple narration"
  • "Turn this product description into a 30-second Instagram Reel: 'Lightweight wireless earbuds with 40-hour battery life and noise cancellation, available in 5 colors'"

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 That Move People

Most people have ideas but no video production setup. Storyboards, stock footage libraries, editing software — the barrier is high and the learning curve is steep. This skill removes all of that. You write what you want to say, and the generator handles everything from scene selection to visual pacing.

Whether you're drafting a product explainer, a social media teaser, a training walkthrough, or a short narrative, the free-text-to-video-generator interprets your language and builds a video that matches your intent. Describe the mood, the audience, the message — and the output reflects those choices.

This is built for people who think in words but need to communicate in video. Bloggers repurposing articles, teachers building lesson content, startup founders pitching ideas, or social teams producing daily content — anyone who writes can now produce videos at scale without touching a single timeline or export setting.

Routing Your Script Requests

When you submit a text prompt, ClawHub parses your input and routes it to the appropriate video synthesis pipeline based on content type, duration hints, and style parameters detected in your script.

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❌

Video Generation API Reference

The cloud processing backend queues your text-to-video job across distributed rendering nodes, converting your raw script into keyframes, voiceover-synced visuals, and scene transitions in a single asynchronous pipeline. Render times vary based on video length, resolution output, and current queue depth on the generation cluster.

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

  • X-Skill-Source: free-text-to-video-generator
  • 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

Integration Guide — Using Free Text to Video in Your Workflow

The free-text-to-video-generator fits naturally into content pipelines that already start with written material. If your team produces blog posts, newsletters, or product copy, those assets can be fed directly into the generator as video scripts — no reformatting required. This makes it especially useful for content repurposing workflows where a single written piece needs to live across multiple formats.

For social media teams, consider building a prompt library — a set of proven text templates for recurring video types like weekly tips, product highlights, or event announcements. Reusing and tweaking these templates keeps output consistent and speeds up production significantly.

If you're integrating this into an automated publishing workflow, structure your input prompts with consistent metadata fields: topic, target platform, video length, and tone. This makes batch video generation predictable and easier to quality-check before publishing.

For educators and course creators, the generator pairs well with existing lesson outlines or lecture notes. Feed in a structured outline and specify 'educational explainer format' to produce module-ready video content directly from your existing curriculum materials.

Troubleshooting Common Issues with Text-to-Video Output

If your generated video doesn't match the tone or style you described, the most common cause is a prompt that's too vague. Instead of writing 'make a video about my brand,' try specifying the audience, desired mood, video length, and key message. Precision in your text input directly improves visual output quality.

If the pacing feels off — scenes changing too fast or too slow — include duration cues in your prompt. Phrases like 'slow and cinematic' or 'fast-paced with quick cuts' give the generator clear rhythm instructions to follow.

For text-heavy scripts that aren't rendering correctly on screen, break your input into clearly labeled sections: intro, body, and outro. This helps the generator segment your content into logical visual blocks rather than treating the whole prompt as one continuous scene.

If generated visuals feel mismatched to your topic, try adding genre or industry context. 'Technology startup pitch' produces very different results than 'wellness brand introduction' even with similar wording.

平台分布

OpenClaw

84.49%
按下载量换算1,430

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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