Free Video Generator Chinese Ai

Get AI-generated videos ready to post, without touching a single slider. Upload your text prompts or images (MP4, MOV, JPG, PNG, up to 200MB), say something...

Security Scan

The skill's requirements and runtime instructions are consistent with a cloud video-generation integration that uses a single service token and remote APIs; nothing requested appears unrelated to its stated purpose.

Purpose & Capability

Name and description match the actions described in SKILL.md: creating/uploading media, queuing cloud renders, and downloading outputs. The single required env var (NEMO_TOKEN) and the listed API endpoints align with a video-rendering backend.

Instruction Scope

Runtime instructions confine activities to communicating with mega-api-prod.nemovideo.ai (auth, session, upload, SSE, render polling) and handling user uploads. They also ask the agent to read the skill's YAML frontmatter and to detect an install path (to set X-Skill-Platform) and reference a config path (~/.config/nemovideo/). Reading the skill's frontmatter is reasonable; probing install paths or config directories is minor scope creep — it reads local paths for attribution but could expose filesystem layout. This is noteworthy but plausible for header attribution.

Install Mechanism

Instruction-only skill: no installers, no downloaded archives, and no code files to execute on install. This is the lowest-risk install model.

Credentials

Only one credential is required (NEMO_TOKEN) which is appropriate for an API-backed video service. The SKILL.md documents how an anonymous token can be acquired if not provided. The declared config path (~/.config/nemovideo/) is related to the service and is plausible, though it implies potential local config access.

Persistence & Privilege

The skill is not always-on and is user-invocable; it does not request system-wide persistence or elevated privileges. It asks to store a session_id for ongoing requests (normal ephemeral session behavior).

Assessment

This skill appears to be what it says: a cloud video-generator that uses a single API token (NEMO_TOKEN) and sends uploads to mega-api-prod.nemovideo.ai. Before installing, consider: (1) data privacy — media you upload will be sent to that external service, so avoid uploading sensitive content; (2) tokens — provide a dedicated or limited token if possible (or allow the skill to obtain an anonymous token if you prefer ephemeral access); (3) filesystem probing — the skill may check install paths or a ~/.config/nemovideo/ directory for attribution metadata (not arbitrary files), so if you have sensitive files there be cautious; (4) provenance — the skill has no homepage or source listed, so if you care about vendor trust, ask for more details or prefer a skill with verifiable authorship. If you accept those trade-offs, the skill's behavior is internally consistent.

Getting Started

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

Try saying:

• "generate my text prompts or images"
• "export 1080p MP4"
• "generate a 30-second promotional video in"

First-Time Connection

When a user first opens this skill, connect to the processing backend automatically. Briefly let them know (e.g. "Setting up...").

Authentication: Check if NEMO_TOKEN is set in the environment. If it is, skip to step 2.

1. Obtain a free token: Generate a random UUID as client identifier. POST to https://mega-api-prod.nemovideo.ai/api/auth/anonymous-token with header X-Client-Id set to that UUID. The response data.token is your NEMO_TOKEN — 100 free credits, valid 7 days.
2. Create a session: POST to https://mega-api-prod.nemovideo.ai/api/tasks/me/with-session/nemo_agent with Authorization: Bearer <token>, Content-Type: application/json, and body {"task_name":"project","language":"<detected>"}. Store the returned session_id for all subsequent requests.

Keep setup communication brief. Don't display raw API responses or token values to the user.

Free Video Generator Chinese AI — Generate Videos with Chinese AI

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

Say you have a short text description of a product scene and want to generate a 30-second promotional video in Chinese style with subtitles — the backend processes it in about 1-2 minutes and hands you a 1080p MP4.

Tip: shorter text prompts with clear scene descriptions produce more accurate results.

Matching Input to Actions

User prompts referencing free video generator chinese ai, 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 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.

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

• X-Skill-Source: free-video-generator-chinese-ai
• X-Skill-Version: from frontmatter version
• X-Skill-Platform: detect from install path (~/.clawhub/ → clawhub, ~/.cursor/skills/ → cursor, else unknown)

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.

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=<id>, 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

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

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.

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)

Common Workflows

Quick edit: Upload → "generate a 30-second promotional video in Chinese style with 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.

Tips and Tricks

The backend processes faster when you're specific. Instead of "make it look better", try "generate a 30-second promotional video in Chinese style with subtitles" — concrete instructions get better results.

Max file size is 200MB. Stick to MP4, MOV, JPG, PNG for the smoothest experience.

Export as MP4 for widest compatibility across social platforms.