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Free Text To Video Generator

作者 dsewell-583h0 · GitHub ↗ · v1.0.0 · MIT-0
cross-platform ✓ 安全检测通过
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在 OpenClaw 中安装
/install free-text-to-video-generator
功能描述
Type a concept, script, or story idea and watch it transform into a fully rendered video — no camera, no footage, no editing timeline required. This free-tex...
使用说明 (SKILL.md)

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... Action Skip 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 \x3CNEMO_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":"\x3Clang>"} — returns task_id, session_id.

Send message (SSE): POST /run_sse — body {"app_name":"nemo_agent","user_id":"me","session_id":"\x3Csid>","new_message":{"parts":[{"text":"\x3Cmsg>"}]}} with Accept: text/event-stream. Max timeout: 15 minutes.

Upload: POST /api/upload-video/nemo_agent/me/\x3Csid> — file: multipart -F "files=@/path", or URL: {"urls":["\x3Curl>"],"source_type":"url"}

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

Session state: GET /api/state/nemo_agent/me/\x3Csid>/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_\x3Cts>","sessionId":"\x3Csid>","draft":\x3Cjson>,"output":{"format":"mp4","quality":"high"}}. Poll GET /api/render/proxy/lambda/\x3Cid> 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

Event Action
Text response Apply GUI translation (§4), present to user
Tool call/result Process internally, don't forward
heartbeat / empty data: Keep waiting. Every 2 min: "⏳ Still working..."
Stream closes Process 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 says You 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

Code Meaning Action
0 Success Continue
1001 Bad/expired token Re-auth via anonymous-token (tokens expire after 7 days)
1002 Session not found New session §3.0
2001 No credits Anonymous: show registration URL with ?bind=\x3Cid> (get \x3Cid> from create-session or state response when needed). Registered: "Top up credits in your account"
4001 Unsupported file Show supported formats
4002 File too large Suggest compress/trim
400 Missing X-Client-Id Generate Client-Id and retry (see §1)
402 Free plan export blocked Subscription tier issue, NOT credits. "Register or upgrade your plan to unlock export."
429 Rate 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.

安全使用建议
This skill is internally consistent for a text→video service, but take the following precautions before installing or using it: - Verify the remote API domain (mega-api-prod.nemovideo.ai) and the service's legitimacy (homepage, docs, privacy policy) before sending sensitive data. - Treat NEMO_TOKEN as a bearer credential: do not reuse high-privilege keys. Prefer a scoped/ephemeral token for testing. - Do not upload files that contain secrets, private keys, or personally identifiable information unless you trust the service and its data retention policy. - Be aware the skill will send any prompt text and uploaded files to the third-party API and will set attribution headers derived from local paths; avoid including secret paths or credentials in prompts. - Because the package has no homepage or clear provenance, exercise extra caution and consider testing with dummy data first. If you need higher assurance, ask the publisher for documentation or source code before trusting real data.
功能分析
Type: OpenClaw Skill Name: free-text-to-video-generator Version: 1.0.0 The skill bundle provides instructions for an AI agent to interface with the Nemo Video text-to-video generation API (mega-api-prod.nemovideo.ai). It includes detailed logic for authentication (including an anonymous token flow), session management, and video rendering/exporting. The instructions are transparent about required environment variables (NEMO_TOKEN) and configuration paths (~/.config/nemovideo/), and the behavior is entirely consistent with the stated purpose of generating video content from text prompts.
能力评估
Purpose & Capability
The name/description (text→video) match the declared requirement (NEMO_TOKEN) and the SKILL.md describes calls to a nemo video API. The declared config path (~/.config/nemovideo/) and the single primary env var are coherent with the stated purpose.
Instruction Scope
Runtime instructions stay within the stated scope: create sessions, send SSE messages, upload files, check credits, and export renders. They do instruct network calls to https://mega-api-prod.nemovideo.ai and to upload user-provided files (multipart @/path or URL). The skill also instructs detecting an install path for an attribution header (minor local path read). These behaviors are expected for this capability but do mean user text and any uploaded files will be sent to a third-party API.
Install Mechanism
Instruction-only skill with no install spec and no code files — nothing is written to disk by an installer. This is low install risk.
Credentials
Only one credential (NEMO_TOKEN) is required and used as a Bearer token for API requests; the SKILL.md also documents a fallback anonymous-token flow if no token is present. The number and type of env vars are proportional to the service's needs. Note: the token will be transmitted to the remote API in Authorization headers.
Persistence & Privilege
The skill does not request always:true and has no install actions. It does not ask to modify other skills or system-wide settings. Autonomous invocation is allowed by default (platform behavior) — combine that knowledge with network access when deciding trust.
如何使用
  1. 确保已安装 OpenClaw(本地或 Docker 部署)
  2. 在对话框中输入安装命令:/install free-text-to-video-generator
  3. 安装完成后,直接呼叫该 Skill 的名称或使用 /free-text-to-video-generator 触发
  4. 根据 Skill 的参数说明提供必要输入,即可获得结构化输出
版本历史
v1.0.0
Initial release of Free Text to Video Generator - Instantly convert your written ideas, scripts, or concepts into shareable videos—no footage or editing skills required. - Supports automatic scene matching, pacing, and style based on your text input. - Designed for marketers, educators, and creators needing fast, polished video content. - Simple setup: connects automatically with free starter credits if no token is provided. - Easy workflows for generating, editing, uploading, exporting videos, and checking credit balance. - Error handling guides and user-friendly status updates included for seamless experience.
元数据
Slug free-text-to-video-generator
版本 1.0.0
许可证 MIT-0
累计安装 0
当前安装数 0
历史版本数 1
常见问题

Free Text To Video Generator 是什么?

Type a concept, script, or story idea and watch it transform into a fully rendered video — no camera, no footage, no editing timeline required. This free-tex... 它是一个面向 Claude Code / OpenClaw 的 AI Agent Skill 插件,目前累计下载 171 次。

如何安装 Free Text To Video Generator?

在 OpenClaw 或 Claude Code 对话框中运行命令「/install free-text-to-video-generator」即可一键安装,无需额外配置。

Free Text To Video Generator 是免费的吗?

是的,Free Text To Video Generator 完全免费,采用 MIT-0 许可证,可自由下载、安装和使用。

Free Text To Video Generator 支持哪些平台?

Free Text To Video Generator 跨平台运行,可在任意部署了 OpenClaw / Claude Code 的环境中使用(cross-platform)。

谁开发了 Free Text To Video Generator?

由 dsewell-583h0(@dsewell-583h0)开发并维护,当前版本 v1.0.0。

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