Ai Voiceover Italiano

add video files into Italian voiceover video with this skill. Works with MP4, MOV, AVI, WebM files up to 500MB. content creators and marketers use it for add...

Security Scan

The skill's requests and runtime instructions are coherent with its stated purpose (adding Italian AI voiceovers to video) and it is instruction-only with no installers or unexpected credential requests.

Purpose & Capability

The skill claims to add Italian voiceovers and requires a single credential (NEMO_TOKEN) and a nemovideo config path in its frontmatter — these align with a cloud rendering backend. Minor inconsistency: registry metadata listed no required config paths, but the SKILL.md frontmatter includes ~/.config/nemovideo/ as a configPath. This is likely harmless but worth noting.

Instruction Scope

SKILL.md only instructs the agent to interact with the nemovideo cloud API: obtain an anonymous token (if NEMO_TOKEN not provided), create a session, upload files, poll state, and request exports. It does not instruct the agent to read unrelated local files or other credentials, nor to exfiltrate system data. Instructions to keep token values hidden from the user are present.

Install Mechanism

No install spec or code files — this is instruction-only. That minimizes disk-write/installation risk.

Credentials

The skill declares a single required env var (NEMO_TOKEN) which is appropriate for a third‑party API. The skill will also obtain an anonymous token itself if NEMO_TOKEN is not present; that behavior makes requiring NEMO_TOKEN somewhat optional/redundant but not disproportionate. No other secrets or unrelated credentials are requested.

Persistence & Privilege

always is false and the skill does not request elevated or cross-skill configuration changes. It asks that session_id be stored for the session, which is normal for a network-backed editing session.

Assessment

This skill appears to do what it says: it uploads videos to a nemovideo cloud service, creates or uses an API token (NEMO_TOKEN), and returns rendered MP4s. Before installing or using it: 1) Be aware that videos are uploaded to https://mega-api-prod.nemovideo.ai — don't send sensitive or private footage until you've verified the vendor/privacy policy. 2) You can supply your own NEMO_TOKEN (recommended) instead of letting the skill auto-create an anonymous token. 3) The skill is instruction-only (no local installers), so it won’t add executables, but it will perform network calls and store a session_id for processing. 4) Note the minor metadata inconsistency about a config path in SKILL.md; it likely only affects where the skill looks for local nemovideo config if present. If you need higher assurance, ask the publisher for a homepage or privacy details before sending production content.

Getting Started

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

Try saying:

• "add my video files"
• "export 1080p MP4"
• "add an Italian AI voiceover to"

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.

AI Voiceover Italiano — Generate Italian Voiceover for Videos

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

Say you have a 2-minute product demo video in English and want to add an Italian AI voiceover to my tutorial video — the backend processes it in about 1-2 minutes and hands you a 1080p MP4.

Tip: shorter video segments produce more natural-sounding Italian speech.

Matching Input to Actions

User prompts referencing ai voiceover italiano, 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":"<lang>"}. 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/<sid>	POST	Upload a file (multipart) or URL.
/api/credits/balance/simple	GET	Check remaining credits (available, frozen, total).
/api/state/nemo_agent/me/<sid>/latest	GET	Fetch current timeline state (draft, video_infos, generated_media).
/api/render/proxy/lambda	POST	Start 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.

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

• X-Skill-Source: ai-voiceover-italiano
• 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 <NEMO_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=<id> (get <id> 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 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 → "add an Italian AI voiceover to my tutorial video" → 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 "add an Italian AI voiceover to my tutorial video" — concrete instructions get better results.

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

Export as MP4 for widest compatibility across Italian streaming and social platforms.