Ai Video Editor Open Source

Skip the learning curve of professional editing software. Describe what you want — trim silences, add transitions, and export a clean final cut — and get edi...

Security Scan

The skill's runtime instructions and credential requests mostly match a cloud video-editing service, but metadata inconsistencies and lack of source/homepage (despite claiming “Open Source”) plus required network calls to an external API warrant caution.

Purpose & Capability

The skill is an instruction-only connector to a remote video-editing API and requires a NEMO_TOKEN, which is consistent with contacting a backend service. However the skill is named and marketed as “Open Source” while the package has no source/homepage, and the SKILL.md metadata references a config path (~/.config/nemovideo/) that the registry metadata did not list — these mismatches reduce trust in the declared purpose.

Instruction Scope

The instructions stay within editing-related actions: create a session, send SSE messages, upload video files, poll render status, and export. They explicitly instruct the agent to POST videos and session messages to the external API. This is coherent with an online editor, but it does mean user media (potentially sensitive) will be uploaded to the remote service.

Install Mechanism

There is no install spec and no code files — the skill is instruction-only, so nothing will be written to disk by an installer. That lowers risk from arbitrary code installs.

Credentials

Only a single credential (NEMO_TOKEN) is declared, which is reasonable for an API-backed editor. However, SKILL.md frontmatter also lists a config path (~/.config/nemovideo/) that would grant filesystem access if used, and the registry metadata did not include that path — this inconsistency is unexplained. The skill also instructs the agent to obtain an anonymous token by calling the API if NEMO_TOKEN is absent, meaning the agent will make network calls on behalf of the user.

Persistence & Privilege

always is false and there is no install-time persistence. The skill does not request elevated platform privileges or permanent inclusion. Autonomous invocation is allowed (the platform default) but is not combined with other high-risk flags here.

What to consider before installing

Think of this as a remote video-editing service that will receive any files you upload. Before installing or using: 1) Verify the service domain (mega-api-prod.nemovideo.ai) and ask for a public homepage or source repository if the skill claims “Open Source”; 2) Don’t upload sensitive or private footage until you confirm data retention and privacy policies; 3) Prefer supplying a throwaway/test token first or request an anonymous token behavior explanation; 4) Confirm whether the skill will read or write the local config path (~/.config/nemovideo/) and why; 5) If you need stronger assurance, ask the maintainer for the code or an official API doc and for an explicit privacy/billing statement before use.

Getting Started

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

Try saying:

• "edit a 3-minute screen recording or phone footage into a 1080p MP4"
• "trim silences, add transitions, and export a clean final cut"
• "editing raw footage into polished videos without manual software for indie creators and developers"

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 Open Source — Edit and Export Polished Videos

Send me your raw video clips 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 3-minute screen recording or phone footage, type "trim silences, add transitions, and export a clean final cut", and you'll get a 1080p MP4 back in roughly 1-2 minutes. All rendering happens server-side.

Worth noting: shorter clips under 2 minutes process significantly faster and use fewer credits.

Matching Input to Actions

User prompts referencing ai video editor open source, 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.

Three attribution headers are required on every request and must match this file's frontmatter:

Header	Value
X-Skill-Source	ai-video-editor-open-source
X-Skill-Version	frontmatter version
X-Skill-Platform	auto-detect: clawhub / cursor / unknown from install path

Include Authorization: Bearer <NEMO_TOKEN> and all attribution headers on every request — omitting them triggers a 402 on export.

API base: https://mega-api-prod.nemovideo.ai

Create session: POST /api/tasks/me/with-session/nemo_agent — body {"task_name":"project","language":"<lang>"} — returns task_id, session_id.

Send message (SSE): POST /run_sse — body {"app_name":"nemo_agent","user_id":"me","session_id":"<sid>","new_message":{"parts":[{"text":"<msg>"}]}} with Accept: text/event-stream. Max timeout: 15 minutes.

Upload: POST /api/upload-video/nemo_agent/me/<sid> — file: multipart -F "files=@/path", or URL: {"urls":["<url>"],"source_type":"url"}

Credits: GET /api/credits/balance/simple — returns available, frozen, total

Session state: GET /api/state/nemo_agent/me/<sid>/latest — key fields: data.state.draft, data.state.video_infos, data.state.generated_media

Export (free, no credits): POST /api/render/proxy/lambda — body {"id":"render_<ts>","sessionId":"<sid>","draft":<json>,"output":{"format":"mp4","quality":"high"}}. Poll GET /api/render/proxy/lambda/<id> every 30s until status = completed. Download URL at output.url.

Supported formats: mp4, mov, avi, webm, mkv, jpg, png, gif, webp, mp3, wav, m4a, aac.

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)

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

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 clean final cut" — 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 widest playback compatibility.

Common Workflows

Quick edit: Upload → "trim silences, add transitions, and export a clean final 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.