Online Highlight Editor

Skip the learning curve of professional editing software. Describe what you want — extract the best moments and compile them into a 2-minute highlight reel —...

Security Scan

The skill's instructions generally match an online video highlight service, but inconsistencies in the metadata, lack of source/homepage, and the fact it will upload your videos to an external backend make this worth caution before installing.

Purpose & Capability

The declared primary credential (NEMO_TOKEN) and the SKILL.md endpoints are coherent with an online video-processing backend. However, the SKILL.md frontmatter lists a required config path (~/.config/nemovideo/) that is not reflected in the registry metadata summary, and there is no source URL or homepage to verify the provider—this mismatch and lack of provenance is unexplained.

Instruction Scope

Runtime instructions include uploading user video files (multipart or by URL) to https://mega-api-prod.nemovideo.ai, creating sessions, and streaming SSE responses. That is expected for the stated purpose, but it means full media files are transmitted to a third party. Instructions also describe creating anonymous tokens via an API if NEMO_TOKEN is absent. The skill does not explicitly instruct the agent to read unrelated local files, but the upload pattern expects reading local file paths supplied by the user.

Install Mechanism

No install spec and no code files — instruction-only. This minimizes on-disk code risk because nothing is downloaded or installed by the skill itself.

Credentials

Only NEMO_TOKEN is declared as required, which is appropriate for a hosted service. However the SKILL.md frontmatter references a config path (~/.config/nemovideo/) that could expose more local configuration if used; the registry metadata earlier listed no config paths, creating an unexplained inconsistency. Also, the skill will generate and use anonymous tokens if none are present, which is convenient but means the agent may obtain credentials on the user's behalf and use them to upload data.

Persistence & Privilege

always:false and no persistent installation. The skill keeps session_id state for interactions with the service (normal). It does not request system-wide privileges or declare modifications to other skills.

What to consider before installing

This skill appears to do what it says (remote highlight extraction) but exercises caution: 1) The provider is not verifiable (no homepage/source) — that increases privacy risk. 2) Using the skill will upload your raw videos to https://mega-api-prod.nemovideo.ai (a third party). Do not upload sensitive or private footage until you confirm the service and its privacy/security practices. 3) The SKILL.md mentions a config path (~/.config/nemovideo/) that isn't declared elsewhere — ask the author whether the skill will read local config files and why. 4) If you do try it, prefer providing a throwaway/limited token or use the anonymous flow and test with non-sensitive sample videos first. 5) If you need higher assurance, ask for the skill's source code or an official homepage and privacy policy before enabling it.

Getting Started

Ready when you are. Drop your raw video footage here or describe what you want to make.

Try saying:

• "create a 90-minute sports game recording into a 1080p MP4"
• "extract the best moments and compile them into a 2-minute highlight reel"
• "generating short highlight reels from long video recordings for sports creators, event videographers, content creators"

Quick Start Setup

This skill connects to a cloud processing backend. On first use, set up the connection automatically and let the user know ("Connecting...").

Token check: Look for NEMO_TOKEN in the environment. If found, skip to session creation. Otherwise:

• Generate a UUID as client identifier
• POST https://mega-api-prod.nemovideo.ai/api/auth/anonymous-token with X-Client-Id header
• Extract data.token from the response — this is your NEMO_TOKEN (100 free credits, 7-day expiry)

Session: POST https://mega-api-prod.nemovideo.ai/api/tasks/me/with-session/nemo_agent with Bearer auth and body {"task_name":"project"}. Keep the returned session_id for all operations.

Let the user know with a brief "Ready!" when setup is complete. Don't expose tokens or raw API output.

Online Highlight Editor — Extract and Export Video Highlights

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

A quick example: upload a 90-minute sports game recording, type "extract the best moments and compile them into a 2-minute highlight reel", and you'll get a 1080p MP4 back in roughly 1-2 minutes. All rendering happens server-side.

Worth noting: trimming your source video to the relevant section first speeds up highlight detection.

Matching Input to Actions

User prompts referencing online highlight editor, 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.

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

Header	Value
X-Skill-Source	online-highlight-editor
X-Skill-Version	frontmatter version
X-Skill-Platform	auto-detect: clawhub / cursor / unknown from install path

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

Reading the SSE Stream

Text events go straight to the user (after GUI translation). Tool calls stay internal. Heartbeats and empty data: lines mean the backend is still working — show "⏳ Still working..." every 2 minutes.

About 30% of edit operations close the stream without any text. When that happens, poll /api/state to confirm the timeline changed, then tell the user what was updated.

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 "extract the best moments and compile them into a 2-minute highlight reel" — 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 social platforms and devices.

Common Workflows

Quick edit: Upload → "extract the best moments and compile them into a 2-minute highlight reel" → 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.