Ai Video Maker Free Chinese

v1.0.0

Get Chinese-captioned videos ready to post, without touching a single slider. Upload your video clips or images (MP4, MOV, JPG, PNG, up to 500MB), say someth...

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Install

OpenClaw Prompt Flow

Install with OpenClaw

Best for remote or guided setup. Copy the exact prompt, then paste it into OpenClaw for dsewell-583h0/ai-video-maker-free-chinese.

Previewing Install & Setup.
Prompt PreviewInstall & Setup
Install the skill "Ai Video Maker Free Chinese" (dsewell-583h0/ai-video-maker-free-chinese) from ClawHub.
Skill page: https://clawhub.ai/dsewell-583h0/ai-video-maker-free-chinese
Keep the work scoped to this skill only.
After install, inspect the skill metadata and help me finish setup.
Required env vars: NEMO_TOKEN
Use only the metadata you can verify from ClawHub; do not invent missing requirements.
Ask before making any broader environment changes.

Command Line

CLI Commands

Use the direct CLI path if you want to install manually and keep every step visible.

OpenClaw CLI

Bare skill slug

openclaw skills install ai-video-maker-free-chinese

ClawHub CLI

Package manager switcher

npx clawhub@latest install ai-video-maker-free-chinese
Security Scan
VirusTotalVirusTotal
Benign
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OpenClawOpenClaw
Benign
medium confidence
Purpose & Capability
The skill is a cloud video creation tool and declares/uses a single service credential (NEMO_TOKEN) and network endpoints under mega-api-prod.nemovideo.ai, which aligns with the described functionality. It does not request unrelated credentials or binaries.
Instruction Scope
Runtime instructions direct the agent to upload user media to the remote API, create sessions, stream SSE responses, poll render status, and present results to the user — all consistent with a cloud render pipeline. The instructions also ask the agent to detect install path (to set X-Skill-Platform header) and include several attribution headers; detecting install path requires probing filesystem locations, which is not necessary for core functionality and is telemetry/attribution behavior to be aware of. The skill will transmit user files and descriptions to an external service — expected but privacy-relevant.
Install Mechanism
No install spec or code files are present; this is instruction-only, so nothing is written to disk by an installer. That minimizes supply-chain risk.
Credentials
Only a single credential (NEMO_TOKEN) is declared as required, which is proportionate for a hosted API. However, the SKILL.md metadata includes a configPaths entry (~/.config/nemovideo/) and instructions reference detecting install paths; the registry metadata shown earlier listed no required config paths — that mismatch is minor but worth noting because any config-path access could expose local state if implemented.
Persistence & Privilege
always:false (default) and no instructions to modify other skills or system-wide settings. The skill opens temporary sessions with the backend but does not request permanent elevated presence on the agent.
Assessment
This skill appears to do what it says: it uploads the media you provide to a nemovideo.ai backend and returns rendered videos. Before installing or using it, consider: (1) any files you upload (videos, images, audio) will be sent to an external service — avoid sending sensitive content; (2) the skill needs a NEMO_TOKEN (or will obtain an anonymous 7‑day token automatically), so treat that token like a credential; (3) the instructions ask the agent to detect install path and include attribution headers — this is telemetry and not essential to core functionality, so check what the implementation actually reads/writes if you care about privacy; (4) verify the service domain and its privacy/retention policy and prefer a disposable account or anonymous token if you are unsure. The overall footprint is coherent and low-risk from an install perspective, but network/file-upload and telemetry behaviors are the main privacy considerations.

Like a lobster shell, security has layers — review code before you run it.

Runtime requirements

🎬 Clawdis
EnvNEMO_TOKEN
Primary envNEMO_TOKEN
latestvk97f06v5g2p3qw6gnrztf4c91s84zpgb
71downloads
0stars
1versions
Updated 1w ago
v1.0.0
MIT-0

Getting Started

Share your video clips or images and I'll get started on AI Chinese video creation. Or just tell me what you're thinking.

Try saying:

  • "create my video clips or images"
  • "export 1080p MP4"
  • "create a short promotional video with"

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.

AI Video Maker Free Chinese — Create Videos with Chinese Text

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

Say you have three product photos and a logo file and want to create a short promotional video with Chinese text and subtitles — the backend processes it in about 1-2 minutes and hands you a 1080p MP4.

Tip: shorter clips under 60 seconds generate Chinese subtitles most accurately.

Matching Input to Actions

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

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 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

EndpointMethodPurpose
/api/tasks/me/with-session/nemo_agentPOSTStart a new editing session. Body: {"task_name":"project","language":"<lang>"}. Returns session_id.
/run_ssePOSTSend 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/<sid>POSTUpload a file (multipart) or URL.
/api/credits/balance/simpleGETCheck remaining credits (available, frozen, total).
/api/state/nemo_agent/me/<sid>/latestGETFetch current timeline state (draft, video_infos, generated_media).
/api/render/proxy/lambdaPOSTStart export. Body: {"id":"render_<ts>","sessionId":"<sid>","draft":<json>,"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.

Headers are derived from this file's YAML frontmatter. X-Skill-Source is ai-video-maker-free-chinese, X-Skill-Version comes from the version field, and X-Skill-Platform is detected from the install path (~/.clawhub/ = clawhub, ~/.cursor/skills/ = cursor, otherwise unknown).

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

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

Reading the SSE Stream

Text events go straight to the user (after GUI translation). Tool calls stay internal. Heartbeats and empty data: lines mean the backend is still working — show "⏳ Still working..." every 2 minutes.

About 30% of edit operations close the stream without any text. When that happens, poll /api/state to confirm the timeline changed, then tell the user what was updated.

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 "create a short promotional video with Chinese text and subtitles" — concrete instructions get better results.

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

Export as MP4 for widest compatibility across Chinese social platforms like Douyin and WeChat.

Common Workflows

Quick edit: Upload → "create a short promotional video with Chinese text and subtitles" → 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.

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