Video Compressor Github

Get compressed MP4 files ready to post, without touching a single slider. Upload your large video files (MP4, MOV, AVI, WebM, up to 500MB), say something lik...

Security Scan

The skill's requirements and runtime instructions match a cloud video-compression service (NEMO_TOKEN + API endpoints) and are generally coherent, but there are small metadata mismatches and privacy implications you should understand before using it.

Purpose & Capability

Name/description (compress/upload videos) align with the operations described in SKILL.md: creating sessions, uploading video files, starting renders, and returning download URLs. Requiring a NEMO_TOKEN is expected for a cloud backend that uses bearer auth.

Instruction Scope

Instructions are focused on the cloud render workflow (token acquisition, session creation, upload, render, polling). They explicitly instruct the agent to look for NEMO_TOKEN and, if missing, call an anonymous-token API to obtain one. The skill also expects the agent to derive X-Skill-Platform from an install path, which implies the agent may inspect its install environment — this is reasonable but worth noting because it touches local path detection. The instructions clearly send user videos to a remote service (data exfiltration is part of intended functionality).

Install Mechanism

No install spec or code files — instruction-only skill. No downloads or archive extraction. Low install risk.

Credentials

Only one credential is requested (NEMO_TOKEN), which is proportional to interacting with the described API. The SKILL.md can also obtain an anonymous token itself via the public anonymous-token endpoint; this is logical but means the skill can create short-lived credentials without the user providing one. There is a minor inconsistency: registry summary lists no required config paths, while the SKILL.md frontmatter includes a configPaths entry (~/.config/nemovideo/).

Persistence & Privilege

always:false and no install-time persistence. The skill does not request elevated or permanent platform presence. Autonomous invocation is allowed (default) but not, by itself, a red flag here.

Assessment

This skill is coherent with a cloud video-compression service: using it will upload any video you drop into the chat to mega-api-prod.nemovideo.ai and use a NEMO_TOKEN (either one you provide or a short-lived anonymous token the skill can obtain). Before installing or invoking: 1) confirm you trust nemovideo.ai with the videos you will upload (privacy/retention concerns); 2) if you prefer control, create and supply your own NEMO_TOKEN rather than relying on anonymous token issuance; 3) note the small metadata mismatch (SKILL.md mentions ~/.config/nemovideo/ while the registry summary did not) — ask the skill author where tokens/getting-stored and whether anything is written to disk; 4) be aware the agent may inspect install paths to set X-Skill-Platform header (this is benign but accesses local path info). If any of those behaviors are unacceptable, do not install or do not upload sensitive videos.

Getting Started

Got large video files to work with? Send it over and tell me what you need — I'll take care of the AI video compression.

Try saying:

• "compress a 500MB 1080p screen recording into a 1080p MP4"
• "compress this video to under 50MB without losing too much quality"
• "reducing video file size for sharing or uploading for developers, content creators, students"

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 Compressor — Compress and Export Smaller Videos

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

Here's a typical use: you send a a 500MB 1080p screen recording, ask for compress this video to under 50MB without losing too much quality, and about 30-90 seconds later you've got a MP4 file ready to download. The whole thing runs at 1080p by default.

One thing worth knowing — shorter clips compress faster and give you more control over output quality.

Matching Input to Actions

User prompts referencing video compressor github, 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 video-compressor-github, 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 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 "compress this video to under 50MB without losing too much quality" — concrete instructions get better results.

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

H.264 codec gives the best balance of quality and size.

Common Workflows

Quick edit: Upload → "compress this video to under 50MB without losing too much quality" → Download MP4. Takes 30-90 seconds 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.