Editor Ai Arabic

Cloud-based editor-ai-arabic tool that handles editing Arabic-language videos with AI-generated Arabic subtitles. Upload MP4, MOV, AVI, WebM files (up to 500...

Security Scan

The skill's requirements and runtime instructions generally match a cloud Arabic video editor: it needs a NEMO_TOKEN and talks to a nemo video API to upload/process videos, but there are a few small metadata inconsistencies and behavior choices you should be aware of before installing.

Purpose & Capability

Name/description (cloud AI Arabic video editing) align with the declared primary credential (NEMO_TOKEN) and the SKILL.md's API endpoints for uploading, rendering, and checking credits. Requesting a service token for the backend is appropriate for this functionality.

Instruction Scope

SKILL.md instructs the agent to automatically connect to the backend on first open and to POST to https://mega-api-prod.nemovideo.ai to obtain an anonymous token if NEMO_TOKEN is not set, then create a session. That is coherent for a cloud editor, but it means the skill will make network calls and create tokens/sessions before the user explicitly uploads video — consider whether you want that automatic behavior. The instructions do not ask to read unrelated local files, but they do reference detecting an install path to set X-Skill-Platform which is brittle for an instruction-only skill with no install.

Install Mechanism

No install spec and no code files — instruction-only. This is the lowest-risk install posture: nothing is written to disk by an installer. Runtime network activity is specified in SKILL.md.

Credentials

Only one credential is declared (NEMO_TOKEN) which is appropriate. SKILL.md will accept an existing NEMO_TOKEN or create an anonymous one. Minor inconsistency: the skill registry summary lists no required config paths, but SKILL.md frontmatter mentions a config path (~/.config/nemovideo/). The skill also instructs storing session_id for subsequent requests but does not specify storage location — this is expected but worth confirming (ephemeral vs persistent).

Persistence & Privilege

always:false and no install behavior means the skill does not request elevated persistence or automatic inclusion. It does instruct creating/storing a session token for the backend, which is normal for a cloud service; it does not request to modify other skills or system-wide settings.

Assessment

This skill appears to do what it says: it uploads user videos to mega-api-prod.nemovideo.ai and uses a NEMO_TOKEN (or will obtain an anonymous token) to create a session and render outputs. Before installing, consider: (1) the skill will make network calls automatically on first open to obtain a token/session unless you pre-set NEMO_TOKEN — if you prefer explicit consent, set your own token or avoid auto-connection; (2) uploaded videos and any content you send will go to the nemo backend — verify the service's privacy/retention policy and whether you trust that domain with your files; (3) check where session tokens/session_id are stored (ephemeral memory vs on-disk config) if you care about local persistence; (4) note the small metadata inconsistency about a config path in SKILL.md — ask the publisher which path (if any) will be read/written; and (5) if you have sensitive content, avoid using the anonymous-token flow and instead use an account token or a service you control. If any of these points are unacceptable, do not install or ask the publisher for clarification.

Getting Started

Send me your raw video footage and I'll handle the AI Arabic video editing. Or just describe what you're after.

Try saying:

• "edit a 2-minute talking-head video in Arabic into a 1080p MP4"
• "edit this Arabic video, add Arabic subtitles and trim pauses"
• "editing Arabic-language videos with AI-generated Arabic subtitles for Arabic content creators"

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 Editor Arabic — Edit and Caption Arabic Videos

Drop your raw video footage in the chat and tell me what you need. I'll handle the AI Arabic video editing on cloud GPUs — you don't need anything installed locally.

Here's a typical use: you send a a 2-minute talking-head video in Arabic, ask for edit this Arabic video, add Arabic subtitles and trim pauses, 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 clips under 3 minutes process significantly faster and yield more accurate Arabic transcription.

Matching Input to Actions

User prompts referencing editor ai arabic, 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.

Headers are derived from this file's YAML frontmatter. X-Skill-Source is editor-ai-arabic, 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).

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

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.

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 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 → "edit this Arabic video, add Arabic subtitles and trim pauses" → 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 "edit this Arabic video, add Arabic subtitles and trim pauses" — concrete instructions get better results.

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

Export as MP4 with H.264 codec for the best compatibility across Arabic social media platforms.