Video Editor Highlight

Turn a 10-minute gameplay or event recording into 1080p highlight reel clips just by typing what you need. Whether it's generating short highlight reels from...

Security Scan

The skill's declared purpose (cloud video highlight extraction) aligns with most of its instructions, but there are mismatches and a few scope signals you should review before installing: an inconsistent config-path declaration, automatic anonymous token creation, and an unknown external API domain that will receive user-uploaded video.

Purpose & Capability

Name/description (video highlight extraction) matches the runtime instructions: uploading videos, creating sessions, rendering and returning MP4s. The single declared credential (NEMO_TOKEN) is appropriate for a cloud processing backend.

Instruction Scope

Instructions stay largely within the stated purpose (upload files, stream SSE, poll status, start renders). They also include steps to auto-request an anonymous token if NEMO_TOKEN is absent and to keep a session_id for operations. Nothing in SKILL.md directs reading arbitrary system files, but the frontmatter asks for configPaths (~/.config/nemovideo/) which could imply local config access; this is inconsistent with the registry metadata that listed no required config paths.

Install Mechanism

No install spec and no code files (instruction-only). This is low-risk from a write-to-disk/install perspective.

Credentials

Only one env var is requested (NEMO_TOKEN), which matches the backend auth model. The skill also instructs how to obtain an anonymous token via the service's /api/auth/anonymous-token endpoint if the env var is missing — this is plausible but means the skill can operate without the user's own key. The SKILL.md frontmatter also mentions a config path (~/.config/nemovideo/), which increases the scope of required access if implemented; registry metadata did not declare this path, so this mismatch should be clarified.

Persistence & Privilege

always:false and user-invocable:true. The skill only keeps a per-session session_id in memory for operations; there is no install-time persistence declared. There is no indication it will modify other skills or system settings.

What to consider before installing

This skill appears to do what it says (upload your video to a cloud backend and return highlight reels), but review a few things before enabling it: 1) The service endpoint (mega-api-prod.nemovideo.ai) is an external domain — any video you upload will leave your machine and be processed there. Don’t upload sensitive footage without a privacy policy and terms you trust. 2) The skill will accept or create a NEMO_TOKEN (it can generate an anonymous token itself). Prefer providing an ephemeral or limited-scope token rather than a long-lived credential. 3) The SKILL.md frontmatter references a local config path (~/.config/nemovideo/) but the registry metadata did not — ask the author whether the skill will read/write that directory; do not grant file-access permissions you are uncomfortable with. 4) There is no source/homepage listed; request the skill’s source or documentation (and review the provider’s privacy/security policies) before installing. If you proceed, test with non-sensitive sample videos and a throwaway token first.

Getting Started

Got raw video footage to work with? Send it over and tell me what you need — I'll take care of the AI highlight extraction.

Try saying:

• "create a 10-minute gameplay or event recording into a 1080p MP4"
• "extract the best moments and compile them into a 60-second highlight reel"
• "generating short highlight reels from long video recordings for content creators, sports videographers, event recorders"

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.

Video Editor Highlight — Extract and Export Video Highlights

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

Say you have a 10-minute gameplay or event recording and want to extract the best moments and compile them into a 60-second highlight reel — the backend processes it in about 1-2 minutes and hands you a 1080p MP4.

Tip: shorter source clips under 5 minutes produce faster and more accurate highlights.

Matching Input to Actions

User prompts referencing video editor highlight, 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.

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

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

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

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

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.

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)

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 60-second 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 60-second 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.