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dsewell-583h0

Free Video Generation N8n

作者 dsewell-583h0 · GitHub ↗ · v1.0.0 · MIT-0
cross-platform ⚠ suspicious
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当前安装
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在 OpenClaw 中安装
/install free-video-generation-n8n
功能描述
Skip the learning curve of professional editing software. Describe what you want — generate a short explainer video from a text description using an n8n auto...
使用说明 (SKILL.md)

Getting Started

Share your workflow automation scripts and I'll get started on AI video generation. Or just tell me what you're thinking.

Try saying:

  • "generate my workflow automation scripts"
  • "export 1080p MP4"
  • "generate a short explainer video from"

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.

Free Video Generation n8n — Generate Videos via n8n Automation

Drop your workflow automation scripts in the chat and tell me what you need. I'll handle the AI video generation on cloud GPUs — you don't need anything installed locally.

Here's a typical use: you send a an n8n workflow trigger with a text prompt, ask for generate a short explainer video from a text description using an n8n automation flow, and about 1-2 minutes later you've got a MP4 file ready to download. The whole thing runs at 1080p by default.

One thing worth knowing — shorter text prompts produce more focused and faster video outputs.

Matching Input to Actions

User prompts referencing free video generation n8n, 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.

Base URL: https://mega-api-prod.nemovideo.ai

Endpoint Method Purpose
/api/tasks/me/with-session/nemo_agent POST Start a new editing session. Body: {"task_name":"project","language":"\x3Clang>"}. Returns session_id.
/run_sse POST Send a user message. Body includes app_name, session_id, new_message. Stream response with Accept: text/event-stream. Timeout: 15 min.
/api/upload-video/nemo_agent/me/\x3Csid> POST Upload a file (multipart) or URL.
/api/credits/balance/simple GET Check remaining credits (available, frozen, total).
/api/state/nemo_agent/me/\x3Csid>/latest GET Fetch current timeline state (draft, video_infos, generated_media).
/api/render/proxy/lambda POST Start export. Body: {"id":"render_\x3Cts>","sessionId":"\x3Csid>","draft":\x3Cjson>,"output":{"format":"mp4","quality":"high"}}. Poll status every 30s.

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

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

  • X-Skill-Source: free-video-generation-n8n
  • 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.

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

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.

Translating GUI Instructions

The backend responds as if there's a visual interface. Map its instructions to API calls:

  • "click" or "点击" → execute the action via the relevant endpoint
  • "open" or "打开" → query session state to get the data
  • "drag/drop" or "拖拽" → send the edit command through SSE
  • "preview in timeline" → show a text summary of current tracks
  • "Export" or "导出" → run the 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)

Tips and Tricks

The backend processes faster when you're specific. Instead of "make it look better", try "generate a short explainer video from a text description using an n8n automation flow" — concrete instructions get better results.

Max file size is 500MB. Stick to MP4, MOV, WebM, GIF for the smoothest experience.

Export as MP4 for widest compatibility.

Common Workflows

Quick edit: Upload → "generate a short explainer video from a text description using an n8n automation flow" → Download MP4. Takes 1-2 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 will upload files and use a token (NEMO_TOKEN or an anonymously minted token) to an external service (mega-api-prod.nemovideo.ai). Consider: 1) Do you trust that external domain with any media you upload (sensitive content could be exposed)? 2) The registry claims NEMO_TOKEN is required, but the instructions will create an anonymous token if it’s missing — decide whether you prefer to provide your own token or rely on an auto-generated one. 3) The skill asks the agent to read the skill frontmatter and detect its install path to populate attribution headers — if you’re uncomfortable with software discovering install paths or reading files, avoid installing. 4) Because this is instruction-only, I couldn't inspect runtime network traffic or server behavior; if you proceed, test with non-sensitive files and verify the service’s privacy/terms and the domain’s legitimacy before uploading real data.
功能分析
Type: OpenClaw Skill Name: free-video-generation-n8n Version: 1.0.0 The skill is a functional integration for an AI video generation service (nemovideo.ai). It provides detailed instructions for the agent to manage sessions, handle file uploads, and process video generation requests via a specific API. While it performs platform detection (checking install paths like ~/.clawhub) and requires an API token, these actions are consistent with the stated purpose of providing a managed service and attribution. No evidence of malicious intent, unauthorized data exfiltration, or harmful prompt injection was found in SKILL.md or _meta.json.
能力评估
Purpose & Capability
Name/description (video generation via n8n) align with the runtime instructions and endpoints (upload, render, credits). However the registry declares NEMO_TOKEN as a required env var while the SKILL.md explicitly provides an anonymous-token fallback flow when NEMO_TOKEN is absent — this is an incoherence between declared requirements and the runtime behavior.
Instruction Scope
Instructions direct the agent to call external APIs and upload user files (expected for rendering), but also instruct reading the skill's YAML frontmatter and 'detect from install path' to set X-Skill-Platform — which implies accessing the agent's filesystem/environment. The doc also instructs hiding technical details from the chat, giving the skill discretion to perform network operations out-of-band from the user-visible transcript. These broaden the scope beyond simple request/response.
Install Mechanism
No install spec and no code files — instruction-only skill. That minimizes disk writes and installer risk.
Credentials
Only one declared credential (NEMO_TOKEN), which is appropriate for a third-party video service. But the SKILL.md offers to generate and use anonymous tokens if NEMO_TOKEN is missing, and requires sending whichever token is used to the remote API. Requiring a token as 'required' in metadata while providing an anonymous fallback is inconsistent; the token (whether user-provided or anonymously minted) will be transmitted to the external service.
Persistence & Privilege
always: false and no requests to modify other skills or system-wide settings. The only filesystem access implied is reading its own frontmatter/agent install path to populate an attribution header.
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-video-generation-n8n
  3. 安装完成后,直接呼叫该 Skill 的名称或使用 /free-video-generation-n8n 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-video-generation-n8n — generate AI explainer videos from text or workflow prompts via n8n automation. - Instantly generate short explainer videos from a text description using an n8n automation flow; no manual editing or local software needed. - Supports uploads: MP4, MOV, WebM, GIF, and other common media types; max file size 500MB. - Automatic connection handling: uses NEMO_TOKEN if set, or retrieves a free temporary token with 100 credits. - Built-in actions for export, status, credit balance, and state management; export in 1080p by default. - Error handling for expired tokens, no credits, unsupported files, and more—guides users through all steps. - Designed for automation builders: easily integrate, preview, and export AI-generated videos without leaving n8n.
元数据
Slug free-video-generation-n8n
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 Video Generation N8n 是什么?

Skip the learning curve of professional editing software. Describe what you want — generate a short explainer video from a text description using an n8n auto... 它是一个面向 Claude Code / OpenClaw 的 AI Agent Skill 插件,目前累计下载 130 次。

如何安装 Free Video Generation N8n?

在 OpenClaw 或 Claude Code 对话框中运行命令「/install free-video-generation-n8n」即可一键安装,无需额外配置。

Free Video Generation N8n 是免费的吗?

是的,Free Video Generation N8n 完全免费,采用 MIT-0 许可证,可自由下载、安装和使用。

Free Video Generation N8n 支持哪些平台?

Free Video Generation N8n 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 Video Generation N8n?

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

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