Editor Remastered

Skip the learning curve of professional editing software. Describe what you want — upscale this old footage to 1080p and fix the color grading — and get rema...

Security Scan

The skill's behavior mostly matches a cloud video-remastering service, but there are internal inconsistencies around required credentials and storage that warrant caution before installing.

Purpose & Capability

The name, description, and in-SKILL.md endpoints all describe a cloud video remastering service and request only a service token (NEMO_TOKEN) and a local config path (~/.config/nemovideo/). That is coherent with the stated purpose. However, the registry metadata lists NEMO_TOKEN as a required env var while the SKILL.md explicitly documents an anonymous-token flow when NEMO_TOKEN is not present — this mismatch between declared requirements and runtime behavior is inconsistent.

Instruction Scope

The instructions focus on connecting to the remote nemovideo.ai API, uploading files, creating sessions, polling render status, and handling SSE. They do not instruct reading unrelated system files or other credentials, nor do they request broad agent permissions. They do direct storing session IDs/tokens (expected for session continuity) and instruct not to show raw tokens to users.

Install Mechanism

This is an instruction-only skill with no install spec and no code files, so nothing will be written to disk by an installer. That minimizes install-time risk.

Credentials

The skill declares a single primary credential (NEMO_TOKEN), which is appropriate for a cloud rendering service. But metadata marks NEMO_TOKEN as required while the runtime doc supports generating an anonymous token if none is supplied. Requiring an account token would grant the skill access to a user-bound account (and potentially billing/credits), so the inconsistency should be resolved before trusting a pre-provisioned NEMO_TOKEN. The declared config path (~/.config/nemovideo/) is plausible for storing session state, but storing tokens there means credential material may be persisted locally for the token lifetime (7 days).

Persistence & Privilege

always:false (not force-included) and normal autonomous invocation are used. The skill instructs storing session_id and possibly the anonymous token in the indicated config path for subsequent requests; this is reasonable for session continuity but does create local persistence of session/auth data. The skill does not request system-wide config changes or other skills' credentials.

What to consider before installing

This skill appears to be a cloud-based video remastering interface and will upload any video you send to mega-api-prod.nemovideo.ai. Two things to consider before installing: (1) Credential mismatch — the registry marks NEMO_TOKEN as required but the skill can also create a short-lived anonymous token; only provide a pre-made NEMO_TOKEN if you trust the service and understand which account/credits it unlocks. (2) Privacy/persistence — your video files and a session token may be uploaded/stored on nemovideo's servers and a token may be persisted under ~/.config/nemovideo/ for up to 7 days. If you need stronger guarantees, ask the skill author for the service's privacy/retention policy, test with non-sensitive files first, and prefer the anonymous-token flow (or avoid supplying a long-lived account token) unless you explicitly want account-linked features.

Getting Started

Send me your existing video files and I'll handle the AI video remastering. Or just describe what you're after.

Try saying:

• "remaster a 2-minute 480p interview recording into a 1080p MP4"
• "upscale this old footage to 1080p and fix the color grading"
• "upscaling and restoring low-quality or older video footage for content creators, archivists, YouTubers"

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.

Editor Remastered — Upscale and Restore Video Quality

Drop your existing video files in the chat and tell me what you need. I'll handle the AI video remastering on cloud GPUs — you don't need anything installed locally.

Here's a typical use: you send a a 2-minute 480p interview recording, ask for upscale this old footage to 1080p and fix the color grading, and about 1-2 minutes later you've got a MP4 file ready to download. The whole thing runs at 1080p by default.

One thing worth knowing — shorter clips under 60 seconds process significantly faster and use fewer credits.

Matching Input to Actions

User prompts referencing editor remastered, 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.

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

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.

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

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.

Backend Response Translation

The backend assumes a GUI exists. Translate these into API actions:

Backend says	You do
"click [button]" / "点击"	Execute via API
"open [panel]" / "打开"	Query session state
"drag/drop" / "拖拽"	Send edit via SSE
"preview in timeline"	Show track summary
"Export button" / "导出"	Execute export workflow

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 "upscale this old footage to 1080p and fix the color grading" — 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.

Common Workflows

Quick edit: Upload → "upscale this old footage to 1080p and fix the color grading" → 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.