Ai Video Editor Gaming

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

Security Scan

The skill's requirements and runtime instructions are coherent with a cloud video-editing service: it needs a service token, uploads user video to a remote API, and uses that service for rendering.

Purpose & Capability

The skill is a cloud-based gaming video editor and asks only for NEMO_TOKEN and a nemovideo config path which are directly related to authenticating and interacting with the remote nemo-video API. No unrelated credentials or binaries are requested.

Instruction Scope

The SKILL.md instructs the agent to upload user-provided video files and call the nemo API (session creation, SSE for generation, upload, render polling). That is expected for this purpose, but it does mean user video and metadata are transmitted to an external service (https://mega-api-prod.nemovideo.ai). The instructions also tell the agent to detect install paths to synthesize an X-Skill-Platform header and reference a local config path (~/.config/nemovideo/). These file/path checks are limited in scope but are additional local reads beyond only using an env var.

Install Mechanism

No install spec or code files are present (instruction-only skill), so nothing will be downloaded or written by the skill itself during install. This is the lowest-risk install profile.

Credentials

Only a single credential (NEMO_TOKEN) is declared as required and is appropriate for a third-party cloud editing API. The skill will create an anonymous token itself if none is present, which is consistent with its workflow. The declared config path (~/.config/nemovideo/) is relevant for storing/reading service config but does grant a small additional local read scope.

Persistence & Privilege

The skill is not force-enabled (always:false) and does not request elevated or persistent platform privileges. It does not include an install step that would alter other skills or system-wide settings.

Assessment

This skill will upload your raw video and related metadata to a third-party rendering service (mega-api-prod.nemovideo.ai). That is necessary for its stated functionality but means your content is processed off your machine — do not upload private or sensitive footage unless you trust the service. You can provide an existing NEMO_TOKEN (the skill will use it for authorization) or allow the skill to request an anonymous short-lived token; prefer temporary tokens if you are unsure. Note the skill may read ~/.config/nemovideo/ and check install paths to set a header; this is a small local read and not a broad filesystem sweep. If you need higher assurance, verify the service's privacy/terms, confirm the HTTPS endpoint and domain, or test with non-sensitive clips before using real content.

Getting Started

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

Try saying:

• "edit a 10-minute screen recording of a Fortnite session into a 1080p MP4"
• "cut the highlights, add kill cam transitions, and sync background music to the action"
• "turning long gaming sessions into highlight reels for YouTube or Twitch for gaming content creators"

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 Gaming — Edit Gaming Clips into Highlights

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

A quick example: upload a 10-minute screen recording of a Fortnite session, type "cut the highlights, add kill cam transitions, and sync background music to the action", and you'll get a 1080p MP4 back in roughly 1-2 minutes. All rendering happens server-side.

Worth noting: clip your best moments into segments under 2 minutes before uploading for faster AI processing.

Matching Input to Actions

User prompts referencing ai video editor gaming, 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.

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.

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

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.

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

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

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.

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)

Tips and Tricks

The backend processes faster when you're specific. Instead of "make it look better", try "cut the highlights, add kill cam transitions, and sync background music to the action" — 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 best compatibility across YouTube, Twitch, and Discord.

Common Workflows

Quick edit: Upload → "cut the highlights, add kill cam transitions, and sync background music to the action" → 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.