Video Editing Tools In Ai

Turn a 2-minute unedited screen recording into 1080p edited video clips just by typing what you need. Whether it's trimming and enhancing raw footage with AI...

Security Scan

The skill's requests and runtime instructions are consistent with a remote video-editing service, but it will upload user videos to a third-party API and the SKILL.md contains a small metadata inconsistency you should verify before installing.

Purpose & Capability

The skill name and description (remote AI video editing) match the runtime instructions (uploading video, creating sessions, rendering on cloud GPU). Requiring a NEMO_TOKEN credential is coherent. Minor mismatch: the registry metadata lists no required config paths, but the SKILL.md metadata also declares a configPaths entry (~/.config/nemovideo/). This discrepancy should be clarified.

Instruction Scope

Instructions direct the agent to obtain or use a NEMO_TOKEN, create sessions, upload user video/audio/image files, and poll SSE endpoints on a third-party domain (mega-api-prod.nemovideo.ai). Sending potentially large and sensitive user videos to a remote service is expected for this skill but has clear privacy implications. The SKILL.md also instructs the agent not to display raw API responses or token values to the user — reasonable for secrecy but worth noting as it reduces transparency.

Install Mechanism

No install spec or code files are present (instruction-only), so nothing will be written to disk by an installer. This is the lowest-risk install model.

Credentials

Only one env var (NEMO_TOKEN) is declared as required/primary, which is proportionate for a remote API. Confirm whether the skill actually needs access to the local config path listed in SKILL.md metadata (~/.config/nemovideo/) — the registry metadata did not list config paths, creating a minor inconsistency.

Persistence & Privilege

always is false and the skill is user-invocable; it does not request persistent platform-wide privileges. The skill will operate remotely and does not install persistent components on the agent by default.

Assessment

This skill appears to be what it says: a remote AI video editor that uploads your files to mega-api-prod.nemovideo.ai and uses a NEMO_TOKEN for authentication. Before installing or using it: (1) Accept that your videos (which may contain personal or sensitive content) will be sent to a third-party service—avoid uploading sensitive material unless you trust the operator and have read their privacy/retention policy. (2) Note the skill can auto-generate an anonymous token and will call the external auth endpoint even if you don't set NEMO_TOKEN—if you prefer, set your own token instead. (3) Verify the domain and ownership (nemovideo.ai) and confirm whether data is stored/retained, how long, and who can access rendered outputs. (4) Ask the publisher to clarify the metadata mismatch about ~/.config/nemovideo/ and where session tokens/session_id are stored and rotated. (5) If you use organizational data or PII, consult your security/privacy policy first. If you want stronger assurances, request a verified homepage or vendor contact and review their terms before proceeding.

Getting Started

Share your raw video footage and I'll get started on AI-powered video editing. Or just tell me what you're thinking.

Try saying:

• "edit my raw video footage"
• "export 1080p MP4"
• "cut the pauses, add transitions, and"

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.

Video Editing Tools in AI — Edit and Export Polished Videos

Send me your raw video footage and describe the result you want. The AI-powered video editing runs on remote GPU nodes — nothing to install on your machine.

A quick example: upload a 2-minute unedited screen recording, type "cut the pauses, add transitions, and export as a clean 90-second clip", and you'll get a 1080p MP4 back in roughly 1-2 minutes. All rendering happens server-side.

Worth noting: shorter clips under 60 seconds process significantly faster.

Matching Input to Actions

User prompts referencing video editing tools in 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.

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-tools-in-ai, 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 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

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 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)

Tips and Tricks

The backend processes faster when you're specific. Instead of "make it look better", try "cut the pauses, add transitions, and export as a clean 90-second clip" — 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.

Common Workflows

Quick edit: Upload → "cut the pauses, add transitions, and export as a clean 90-second clip" → 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.