Video Best

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

Security Scan

The skill's requirements and runtime instructions are consistent with a cloud-based video-enhancement service; nothing in the package suggests hidden capabilities, but it will upload user videos and obtain/use an API token from an external backend — review privacy before sending sensitive footage.

Purpose & Capability

Name/description (cloud video enhancement) align with the declared primary credential (NEMO_TOKEN) and the documented API endpoints at mega-api-prod.nemovideo.ai. Minor inconsistency: metadata lists a config path (~/.config/nemovideo/) but the SKILL.md never instructs reading or writing that path, so the declared configPaths appears unnecessary or unused.

Instruction Scope

SKILL.md stays on-topic: it only describes authenticating, creating a session, uploading media, polling state, and starting renders against the vendor API. Important user-impacting behavior: the skill will transmit uploaded video/audio files to an external 3rd-party service (mega-api-prod.nemovideo.ai). It also instructs generating/storing a session_id and obtaining anonymous tokens if none are provided. It does not ask the agent to read unrelated system files or other environment variables.

Install Mechanism

Instruction-only skill with no install spec or code files — lowest-risk delivery mechanism; nothing is written to disk by an installer step.

Credentials

Only a single environment variable (NEMO_TOKEN) is required, which is proportional for an API-backed service. No unrelated credentials are requested. Note: metadata's configPaths entry is present but not used in the instructions.

Persistence & Privilege

Skill is not forced always-on and uses default autonomous invocation settings. It asks to store a session_id for ongoing requests (normal for session-based APIs) but does not request system-wide configuration changes or other skills' credentials.

Assessment

This skill is coherent for a cloud video-enhancement tool, but it will upload whatever media you give it to an external backend (mega-api-prod.nemovideo.ai) and will create or use an API token (NEMO_TOKEN). Before installing/using: 1) Do not upload sensitive or confidential footage unless you trust the service and have reviewed its privacy/security policy. 2) If you don't already have a NEMO_TOKEN, the skill will generate an anonymous token valid for 7 days — consider using a disposable account/token if you want separation from other services. 3) The metadata claims a config path (~/.config/nemovideo/) but the instructions don't use it — confirm where tokens/session IDs are stored (in-memory vs disk). 4) Verify the backend hostname and its TLS/certificate expectations if you need organizational compliance. 5) If you prefer tighter control, avoid granting long-lived credentials to the skill and consider using short-lived/disposable credentials or running uploads through an intermediary you control.

Getting Started

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

Try saying:

• "enhance my raw video footage"
• "export 1080p MP4"
• "make this video look its best"

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.

Video Best — Enhance and Export Quality Videos

Drop your raw video footage in the chat and tell me what you need. I'll handle the AI quality enhancement on cloud GPUs — you don't need anything installed locally.

Here's a typical use: you send a a 2-minute unedited phone recording, ask for make this video look its best with color correction and noise reduction, 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 video best, 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-best
X-Skill-Version	frontmatter version
X-Skill-Platform	auto-detect: clawhub / cursor / unknown from install path

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 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

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.

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 "make this video look its best with color correction and noise reduction" — 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 the best balance of quality and file size.

Common Workflows

Quick edit: Upload → "make this video look its best with color correction and noise reduction" → 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.