Highlight Editor Professional

Skip the learning curve of professional editing software. Describe what you want — extract the best moments and compile them into a 3-minute highlight reel —...

Security Scan

The skill's declared purpose (AI highlight editing) matches the single credential it asks for, but there are inconsistencies and hidden behaviors (automatic token creation, undisclosed config-path access, and instructions to hide token values) that warrant caution before installing.

Purpose & Capability

Name/description match a cloud video-processing service and the skill only declares a single service token (NEMO_TOKEN), which is proportionate. However, the SKILL.md frontmatter references a config path (~/.config/nemovideo/) that the registry metadata omitted—an inconsistency worth noting.

Instruction Scope

The runtime instructions instruct the agent to automatically obtain an anonymous token (POST to mega-api-prod.nemovideo.ai), create sessions, upload user video files to the remote GPU service, and store session IDs. They also direct the agent not to display raw API responses or token values. Uploading user media to a third-party server is expected for this skill, but the auto-token flow and explicit instruction to hide token values reduce transparency and could be abused to exfiltrate data or hide unexpected responses.

Install Mechanism

Instruction-only skill with no install spec and no code files — lowest install risk. Nothing is written to disk by an installer step in the package itself.

Credentials

The only declared credential is NEMO_TOKEN which is appropriate for a nemo video service. However, the frontmatter asks for a config path (~/.config/nemovideo/) that was not listed in the registry metadata; the SKILL.md also requires detecting the agent install path to set attribution headers. Both behaviors imply the skill may read local configuration or paths beyond the declared env var, which is disproportionate unless explicitly justified.

Persistence & Privilege

The skill does not request always:true and does not modify other skills. It stores session_id / token for its own calls (normal for a remote-api integration). Autonomous invocation is allowed by default for skills and is not by itself a red flag here.

What to consider before installing

This skill performs remote cloud rendering and will upload your videos to https://mega-api-prod.nemovideo.ai and either use a user-supplied NEMO_TOKEN or automatically obtain a short‑lived anonymous token. Before installing: 1) Be aware that your raw media will be transmitted to a third party — check their privacy/terms and do not send sensitive footage you cannot share. 2) The skill instructs the agent to auto-create and quietly store tokens and session IDs; if you prefer transparency, set NEMO_TOKEN yourself instead of allowing auto-provisioning. 3) There is an inconsistency: the SKILL.md mentions reading ~/.config/nemovideo/ and detecting install paths (not declared in registry metadata) — confirm whether the skill will read local config files. 4) The skill’s source/homepage is unknown; prefer skills with a verifiable publisher or public repository for higher trust. If you need higher assurance, ask the publisher for a privacy/security statement or avoid installing until source and config-read behaviors are clarified.

Getting Started

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

Try saying:

• "create my raw video footage"
• "export 1080p MP4"
• "extract the best moments and compile"

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.

Highlight Editor Professional — Create and Export Highlight Reels

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

A quick example: upload a 2-hour sports game recording, type "extract the best moments and compile them into a 3-minute highlight reel", and you'll get a 1080p MP4 back in roughly 1-3 minutes. All rendering happens server-side.

Worth noting: trimming your source footage to the relevant section before uploading speeds up highlight detection significantly.

Matching Input to Actions

User prompts referencing highlight editor professional, 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.

Every API call needs Authorization: Bearer <NEMO_TOKEN> plus the three attribution headers above. If any header is missing, exports return 402.

Skill attribution — read from this file's YAML frontmatter at runtime:

• X-Skill-Source: highlight-editor-professional
• X-Skill-Version: from frontmatter version
• X-Skill-Platform: detect from install path (~/.clawhub/ → clawhub, ~/.cursor/skills/ → cursor, else 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 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

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)

Common Workflows

Quick edit: Upload → "extract the best moments and compile them into a 3-minute highlight reel" → Download MP4. Takes 1-3 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 "extract the best moments and compile them into a 3-minute highlight reel" — concrete instructions get better results.

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

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