Ai Video Editor List

edit video clips into edited MP4 clips with this skill. Works with MP4, MOV, AVI, WebM files up to 500MB. content creators use it for comparing and using AI...

Security Scan

The skill's requests and runtime instructions are coherent with an AI cloud video-editing tool: it only asks for a service token (NEMO_TOKEN), posts user video files to the nemo video backend, and has no installable code — nothing appears disproportionate to its stated purpose.

Purpose & Capability

Name/description (AI video editing) match the declared runtime actions: creating sessions, uploading videos, starting renders, checking credits. The single required credential (NEMO_TOKEN) and the listed config path (~/.config/nemovideo/) are consistent with a cloud video service.

Instruction Scope

The SKILL.md instructs the agent to upload user-provided media and metadata to https://mega-api-prod.nemovideo.ai, open SSE streams, poll render status, and include attribution headers. Those actions are expected for a cloud video editor but have privacy implications because user files are transmitted to an external service. The skill also instructs extracting attribution info from the skill frontmatter and detecting an install path — a minor filesystem/read action for header construction.

Install Mechanism

No install step or external downloads are present (instruction-only). That minimizes disk-write/execution risk.

Credentials

Only one env var (NEMO_TOKEN) is required and declared as primary. This aligns with the need to authenticate to the backend. The configPath referenced is service-specific. No unrelated credentials or broad system secrets are requested.

Persistence & Privilege

The skill is not forced-always and is user-invocable. It can be invoked autonomously by the agent (platform default). Because it can upload user media to an external service, allowlisting/autonomy decisions should consider privacy — autonomous invocation combined with data upload increases blast radius but is not itself unexpected for this skill type.

Assessment

This skill appears to be what it claims, but it will upload your video files to a third-party cloud service. Before installing or enabling it: (1) Only set NEMO_TOKEN in your environment if you trust nemo video — a stored token grants the skill access to your account/credits; (2) Do not upload sensitive or private footage unless you understand the service's retention and privacy policy; (3) If you prefer more control, omit NEMO_TOKEN and let the skill obtain an anonymous token for temporary use, or run the skill in a restricted/sandboxed agent environment; (4) Verify the API host (mega-api-prod.nemovideo.ai) and, if possible, test with non-sensitive sample videos first. If you need more assurance about data handling (encryption, retention, deletion), ask the skill author or service operator for their privacy/security docs before using with real content.

Getting Started

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

Try saying:

• "edit my video clips"
• "export 1080p MP4"
• "trim silences, add transitions, and export"

Getting Connected

Before handling any user request, establish a connection to the backend API. Show a brief status like "Connecting...".

If NEMO_TOKEN is in the environment, use it directly and create a session. Otherwise, acquire a free starter token:

• Generate a UUID as client identifier
• POST to https://mega-api-prod.nemovideo.ai/api/auth/anonymous-token with the X-Client-Id header
• The response includes a token with 100 free credits valid for 7 days — use it as NEMO_TOKEN

Then create a session by POSTing to https://mega-api-prod.nemovideo.ai/api/tasks/me/with-session/nemo_agent with Bearer authorization and body {"task_name":"project","language":"en"}. The session_id in the response is needed for all following requests.

Tell the user you're ready. Keep the technical details out of the chat.

AI Video Editor List — Edit and Export Videos with AI

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

Say you have a 2-minute raw screen recording and want to trim silences, add transitions, and export a polished cut — the backend processes it in about 1-2 minutes and hands you a 1080p MP4.

Tip: shorter clips under 3 minutes process significantly faster and use fewer credits.

Matching Input to Actions

User prompts referencing ai video editor list, 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-video-editor-list
• X-Skill-Version: from frontmatter version
• X-Skill-Platform: detect from install path (~/.clawhub/ → clawhub, ~/.cursor/skills/ → cursor, else unknown)

Every API call needs Authorization: Bearer <NEMO_TOKEN> plus the three attribution headers above. If any header is missing, exports return 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 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 → "trim silences, add transitions, and export a polished cut" → 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 "trim silences, add transitions, and export a polished cut" — 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 platforms and devices.