Text To Video Chinese Ai

Get Chinese AI videos ready to post, without touching a single slider. Upload your text prompts (TXT, DOCX, PDF, SRT, up to 200MB), say something like "conve...

Security Scan

The skill's behavior mostly matches a text→video service (it uses a nemo API and a NEMO_TOKEN), but there are inconsistencies and privacy/transparency issues (an undocumented config-path request in the SKILL.md frontmatter, automatic anonymous-token generation, and unclear storage of session tokens) that warrant caution before installing.

Purpose & Capability

The declared primary credential (NEMO_TOKEN) and the API endpoints in the instructions line up with a cloud text→video service — this is expected. However, the SKILL.md frontmatter includes a configPaths entry (~/.config/nemovideo/) while the registry metadata shown earlier did not declare any required config paths; that mismatch is unexplained and suggests the skill may attempt to read user config files that are not documented in the registry.

Instruction Scope

Runtime instructions direct the agent to (a) automatically connect on first use, (b) POST to the nemovideo API to obtain an anonymous token when NEMO_TOKEN is not present, (c) store a session_id for subsequent calls, and (d) suppress display of raw API responses/tokens to users. Those behaviors are plausible for this service, but the instructions do not state where session tokens are stored or whether the skill will read local config files — and the directive to hide raw token/response data reduces transparency for users.

Install Mechanism

This is an instruction-only skill with no install spec and no bundled code. That minimizes disk-write and supply-chain risk.

Credentials

Requesting a single service token (NEMO_TOKEN) is proportional to the described functionality. However, the SKILL.md frontmatter's configPaths (~/.config/nemovideo/) would grant access to a user directory that could contain credentials or other data; this access is not declared in the registry metadata and has no justification in the prose, creating an inconsistency and privacy concern.

Persistence & Privilege

The skill does not request 'always: true' and is not asking for elevated platform privileges. Still, it instructs the agent to 'store' the session_id and to create an anonymous token when no NEMO_TOKEN is present — the storage location/mechanism is unspecified. Combined with the unexplained configPath in the frontmatter, this creates uncertainty about whether the skill will write persistent data or read existing local credentials.

What to consider before installing

This skill appears to implement a legitimate text→video workflow and only needs the service token (NEMO_TOKEN) to operate, but there are a few things to check before installing: 1) Clarify the config-path behavior: ask the publisher why the SKILL.md frontmatter references ~/.config/nemovideo/ and whether the skill will read or write files there; if you don't want local config read, deny that access. 2) Prefer to supply your own NEMO_TOKEN rather than allowing the skill to generate anonymous tokens automatically; anonymous-token creation means the skill will make outbound network calls without explicit user action. 3) Ask where session_id and tokens are stored and whether they persist across runs; persistent storage could expose credentials. 4) Because the skill hides raw API responses/tokens from the user, monitor network activity or audit logs if possible. If the publisher cannot clearly explain the config-path and storage behavior, treat the skill as higher risk and avoid installing it on sensitive accounts or machines.

Getting Started

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

Try saying:

• "generate my text prompts"
• "export 1080p MP4"
• "convert this Chinese text into a"

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.

Text to Video Chinese AI — Generate Videos from Chinese Text

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

Say you have a 50-word Chinese product description and want to convert this Chinese text into a 30-second promotional video with voiceover — the backend processes it in about 1-2 minutes and hands you a 1080p MP4.

Tip: shorter text inputs under 100 characters generate faster and more accurate visuals.

Matching Input to Actions

User prompts referencing text to video 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.

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

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

Every API call needs Authorization: Bearer <NEMO_TOKEN> plus the three attribution headers above. If any header is missing, exports return 402.

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.

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 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

Common Workflows

Quick edit: Upload → "convert this Chinese text into a 30-second promotional video with voiceover" → 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 "convert this Chinese text into a 30-second promotional video with voiceover" — concrete instructions get better results.

Max file size is 200MB. Stick to TXT, DOCX, PDF, SRT for the smoothest experience.

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