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Colab Text To Video

作者 mory128 · GitHub ↗ · v1.0.0 · MIT-0
cross-platform ✓ 安全检测通过
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在 OpenClaw 中安装
/install colab-text-to-video
功能描述
Skip the learning curve of professional editing software. Describe what you want — turn this text into a 30-second video with visuals and background music —...
使用说明 (SKILL.md)

Getting Started

Send me your text prompts and I'll handle the AI video creation. Or just describe what you're after.

Try saying:

  • "convert a 3-sentence product description into a 1080p MP4"
  • "turn this text into a 30-second video with visuals and background music"
  • "generating videos from written scripts or descriptions for content creators, marketers, students"

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.

Colab Text to Video — Convert Text Into Video Clips

This tool takes your text prompts and runs AI video creation through a cloud rendering pipeline. You upload, describe what you want, and download the result.

Say you have a 3-sentence product description and want to turn this text into a 30-second video with visuals and background music — the backend processes it in about 1-3 minutes and hands you a 1080p MP4.

Tip: shorter, clearer text prompts produce more accurate and coherent video output.

Matching Input to Actions

User prompts referencing colab text to video, aspect ratio, text overlays, or audio tracks get routed to the corresponding action via keyword and intent classification.

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

Cloud Render Pipeline Details

Each export job queues on a cloud GPU node that composites video layers, applies platform-spec compression (H.264, up to 1080x1920), and returns a download URL within 30-90 seconds. The session token carries render job IDs, so closing the tab before completion orphans the job.

All calls go to https://mega-api-prod.nemovideo.ai. The main endpoints:

  1. SessionPOST /api/tasks/me/with-session/nemo_agent with {"task_name":"project","language":"\x3Clang>"}. Gives you a session_id.
  2. Chat (SSE)POST /run_sse with session_id and your message in new_message.parts[0].text. Set Accept: text/event-stream. Up to 15 min.
  3. UploadPOST /api/upload-video/nemo_agent/me/\x3Csid> — multipart file or JSON with URLs.
  4. CreditsGET /api/credits/balance/simple — returns available, frozen, total.
  5. StateGET /api/state/nemo_agent/me/\x3Csid>/latest — current draft and media info.
  6. ExportPOST /api/render/proxy/lambda with render ID and draft JSON. Poll GET /api/render/proxy/lambda/\x3Cid> every 30s for completed status and download URL.

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

Three attribution headers are required on every request and must match this file's frontmatter:

Header Value
X-Skill-Source colab-text-to-video
X-Skill-Version frontmatter version
X-Skill-Platform auto-detect: clawhub / cursor / unknown from install path

Include Authorization: Bearer \x3CNEMO_TOKEN> and all attribution headers on every request — omitting them triggers a 402 on export.

Draft JSON uses short keys: t for tracks, tt for track type (0=video, 1=audio, 7=text), sg for segments, d for duration in ms, m for metadata.

Example timeline summary:

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

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

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.

Error Codes

  • 0 — success, continue normally
  • 1001 — token expired or invalid; re-acquire via /api/auth/anonymous-token
  • 1002 — session not found; create a new one
  • 2001 — out of credits; anonymous users get a registration link with ?bind=\x3Cid>, registered users top up
  • 4001 — unsupported file type; show accepted formats
  • 4002 — file too large; suggest compressing or trimming
  • 400 — missing X-Client-Id; generate one and retry
  • 402 — free plan export blocked; not a credit issue, subscription tier
  • 429 — rate limited; wait 30s and retry once

Tips and Tricks

The backend processes faster when you're specific. Instead of "make it look better", try "turn this text into a 30-second video with visuals and background music" — concrete instructions get better results.

Max file size is 500MB. Stick to TXT, DOCX, PDF, plain text for the smoothest experience.

Export as MP4 for widest compatibility across platforms and devices.

Common Workflows

Quick edit: Upload → "turn this text into a 30-second video with visuals and background music" → Download MP4. Takes 1-3 minutes for a 30-second clip.

Batch style: Upload multiple files in one session. Process them one by one with different instructions. Each gets its own render.

Iterative: Start with a rough cut, preview the result, then refine. The session keeps your timeline state so you can keep tweaking.

安全使用建议
This skill appears to be what it says: it uploads your prompts and any files you provide to the nemovideo backend and uses an API token (NEMO_TOKEN). Before installing, confirm you trust the destination (mega-api-prod.nemovideo.ai) with the content you will upload and with any NEMO_TOKEN you provide. Ask the publisher to clarify the configPath discrepancy (~/.config/nemovideo/ in SKILL.md vs none in registry) if you care about local config access. If you don’t want to supply a permanent token, you can rely on the anonymous-token flow (limited credits), but be aware that prompts and files will still be sent to the third‑party service. If the content is sensitive, do not upload it to this skill.
功能分析
Type: OpenClaw Skill Name: colab-text-to-video Version: 1.0.0 The skill is a functional integration for the NemoVideo AI service, designed to convert text prompts and documents into video clips. It manages authentication using the NEMO_TOKEN environment variable or an anonymous token acquisition process and communicates with a legitimate-appearing backend at mega-api-prod.nemovideo.ai. The instructions in SKILL.md correctly guide the agent through session management, file uploads, and polling for video rendering results without any indicators of data exfiltration, unauthorized system access, or malicious prompt injection.
能力评估
Purpose & Capability
The name/description match the runtime instructions: the skill calls a nemo-video backend to render videos and uses a single API token (NEMO_TOKEN). Minor incoherence: the SKILL.md frontmatter lists a config path (~/.config/nemovideo/) while the registry metadata shows no required config paths — this mismatch should be clarified but does not by itself break purpose alignment.
Instruction Scope
The SKILL.md explicitly instructs the agent to create sessions, stream SSE for editing, upload user files (TXT/DOCX/PDF up to 500MB), and poll for render results at mega-api-prod.nemovideo.ai. All of that is within the stated purpose (cloud render pipeline). Important privacy note: user prompts and uploaded files are transmitted to the external service; the skill also instructs the agent to hide technical details from the user.
Install Mechanism
This is an instruction-only skill with no install spec and no code files, so nothing is written to disk by an installer. Low install risk.
Credentials
Only one credential is required (NEMO_TOKEN), which is proportional for a cloud API. The skill also supports obtaining an anonymous token by POSTing to the provider's auth endpoint. Clarify whether reading the optional local config path (~/.config/nemovideo/) is required — frontmatter mentions it but the package metadata did not declare it. Keep in mind NEMO_TOKEN will be sent as Authorization: Bearer to the external service.
Persistence & Privilege
The skill does not request always:true and is only user-invocable by default. It does not ask to modify other skills or system-wide config. Agent autonomous invocation is allowed by platform default (no extra privilege requested).
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 colab-text-to-video
  3. 安装完成后,直接呼叫该 Skill 的名称或使用 /colab-text-to-video 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 Colab Text to Video. - Instantly convert text prompts or files (TXT, DOCX, PDF, up to 500MB) into AI-generated 30-second video clips with visuals and background music. - Automatic backend connection: acquires API tokens and establishes sessions for video creation. - Supports user workflows: uploading files, exporting videos, checking credits, and viewing project state. - Simple chat interface: just describe your video, and the skill handles rendering and delivery (MP4, MOV, AVI, and more). - Designed for content creators, marketers, and students—no need for editing software or recording footage.
元数据
Slug colab-text-to-video
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

Colab Text To Video 是什么?

Skip the learning curve of professional editing software. Describe what you want — turn this text into a 30-second video with visuals and background music —... 它是一个面向 Claude Code / OpenClaw 的 AI Agent Skill 插件,目前累计下载 66 次。

如何安装 Colab Text To Video?

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

Colab Text To Video 是免费的吗?

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

Colab Text To Video 支持哪些平台?

Colab Text To Video 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 Colab Text To Video?

由 mory128(@mory128)开发并维护,当前版本 v1.0.0。

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