Video Editing Ai Adobe

Get polished edited clips ready to post, without touching a single slider. Upload your raw video footage (MP4, MOV, AVI, MXF, up to 500MB), say something lik...

Security Scan

The skill appears to call a Nemovideo cloud API to edit uploaded videos (which matches the stated editing purpose), but it uses ambiguous branding ('Adobe' in the name), has no source/homepage, and declares access to a local config path—verify provenance and privacy before sending real footage or long-lived credentials.

Purpose & Capability

The runtime instructions and required NEMO_TOKEN align with a cloud video-editing service (endpoints, upload, SSE, render). However the skill name includes 'Adobe' while the implementation talks exclusively to mega-api-prod.nemovideo.ai (possible misbranding or misleading name). The frontmatter metadata also declares a config path (~/.config/nemovideo/) which is plausible for storing tokens but is not explained in the prose.

Instruction Scope

SKILL.md instructs the agent to obtain/use NEMO_TOKEN, create an anonymous token if absent, open sessions, upload user files, stream SSE responses, poll state, and request exports — all consistent with a cloud video-editing workflow. There are no instructions to read arbitrary local files beyond uploads, but metadata references a local config path (not explicitly used in the visible instructions). The skill explicitly tells the agent not to print tokens/raw JSON, which is good practice.

Install Mechanism

No install spec and no code files—this is instruction-only, so nothing is written to disk by an installer (lowest install risk).

Credentials

Only one required environment variable (NEMO_TOKEN) is declared, which is proportionate for authenticating to the Nemovideo API. The metadata's configPaths entry (~/.config/nemovideo/) could grant access to locally stored tokens/config and isn't justified in the SKILL.md content; confirm whether that path contains sensitive credentials before allowing the skill to read it.

Persistence & Privilege

always is false and the skill does not request elevated or permanent platform privileges. It does instruct saving a session_id for ongoing jobs (normal for session-based APIs) but does not ask to modify other skills or system-wide settings.

What to consider before installing

Before installing or invoking this skill: - Treat it as a cloud service: your videos are uploaded to mega-api-prod.nemovideo.ai for processing. Do not upload confidential or sensitive footage unless you trust the service and its privacy policy. - The skill name contains 'Adobe' but the API is Nemovideo; this may be misleading—verify the publisher, homepage, and reputation of the service before use. - The skill requests a NEMO_TOKEN (or can mint an anonymous short-lived token). Prefer using an anonymous token for testing and avoid placing long-lived credentials in shared environments. - The metadata lists a local config path (~/.config/nemovideo/). Check that folder for any sensitive files before granting the skill access. - There is no source code or homepage provided. If provenance matters, ask the publisher for documentation, a privacy policy, and evidence that the service is legitimate. - Start by testing with a short, non-sensitive clip to validate behavior and billing/credit effects, and monitor any created remote jobs or leftover data on the service.

Getting Started

Got raw video footage to work with? Send it over and tell me what you need — I'll take care of the AI-powered video editing.

Try saying:

• "edit a 3-minute screen recording or camera clip into a 1080p MP4"
• "cut the dead air, add transitions, and sync background music"
• "editing videos with AI instead of manually using Adobe Premiere for content creators and video editors"

Automatic Setup

On first interaction, connect to the processing API before doing anything else. Show a brief status like "Setting things up...".

Token: If NEMO_TOKEN environment variable is already set, use it and skip to Session below.

Free token: Generate a UUID as client identifier, then POST to https://mega-api-prod.nemovideo.ai/api/auth/anonymous-token with header X-Client-Id: <uuid>. The response field data.token becomes your NEMO_TOKEN (100 credits, 7-day expiry).

Session: POST to https://mega-api-prod.nemovideo.ai/api/tasks/me/with-session/nemo_agent with Bearer auth and body {"task_name":"project"}. Save session_id from the response.

Confirm to the user you're connected and ready. Don't print tokens or raw JSON.

Video Editing AI Adobe — Edit and Export Videos with AI

This tool takes your raw video footage and runs AI-powered video editing through a cloud rendering pipeline. You upload, describe what you want, and download the result.

Say you have a 3-minute screen recording or camera clip and want to cut the dead air, add transitions, and sync background music — the backend processes it in about 1-2 minutes and hands you a 1080p MP4.

Tip: shorter clips under 2 minutes process significantly faster and give more precise AI cut suggestions.

Matching Input to Actions

User prompts referencing video editing ai adobe, 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 video-editing-ai-adobe, 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

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.

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)

Common Workflows

Quick edit: Upload → "cut the dead air, add transitions, and sync background music" → 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 "cut the dead air, add transitions, and sync background music" — concrete instructions get better results.

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

Export as MP4 with H.264 codec for the best balance of quality and file size.