Best Video Compressor

Skip the learning curve of professional editing software. Describe what you want — compress this video to under 50MB without losing quality — and get compres...

Security Scan

The skill's cloud-based compressor behavior is plausible, but there are inconsistencies (declared requirements vs runtime instructions and embedded metadata) and privacy implications from uploading videos to an unknown third‑party API that you should review before installing.

Purpose & Capability

The skill claims to compress videos via a cloud backend and all API endpoints in SKILL.md point to a video processing service (mega-api-prod.nemovideo.ai), which is consistent with the stated purpose. However, the registry metadata says no config paths are required while the SKILL.md frontmatter includes a config path (~/.config/nemovideo/). Also the manifest declares NEMO_TOKEN as required, but the runtime instructions provide an anonymous-token fallback flow — these are inconsistent and may confuse permission expectations.

Instruction Scope

Instructions tell the agent to upload user videos to the remote service, create sessions, poll SSE, and include attribution headers. They also instruct reading the agent install path to set X-Skill-Platform, and to POST for an anonymous token if NEMO_TOKEN is absent. The file- and environment-access scope is limited to token handling and detecting install path, but the instructions will cause potentially sensitive user video files to be transmitted off-device to an external service; this is expected for a cloud compressor but requires explicit user consent and knowledge of the destination.

Install Mechanism

This is an instruction-only skill with no install spec and no code files. That lowers installation risk because nothing new is written to disk by an installer. Note: because there is no code to inspect, the static scanner had nothing to analyze.

Credentials

The skill declares a single primary credential (NEMO_TOKEN), which fits a cloud API. But the SKILL.md also implements an automatic anonymous-token acquisition flow when NEMO_TOKEN is missing, making the 'required env var' claim misleading. The frontmatter also references a config path (~/.config/nemovideo/), which the registry did not list — this mismatch raises questions about what credentials or config might actually be used or persisted.

Persistence & Privilege

The skill does not request always:true and does not ask to change other skills or system-wide settings. It only suggests reading the install path and possibly using/creating a token for its own session; this is within normal bounds for a cloud service integration.

What to consider before installing

This skill will upload your videos to a third-party cloud API (mega-api-prod.nemovideo.ai) for processing. Before installing or using it: 1) Confirm the service operator and read its privacy/terms (source/homepage are missing here). 2) Don't upload sensitive or private videos unless you trust the service. 3) Note the manifest inconsistencies: the skill claims NEMO_TOKEN is required but can auto-generate an anonymous token — decide whether you want the agent to obtain tokens automatically. 4) Because the skill is instruction-only, there is no code to inspect; consider testing with a non-sensitive sample file first or use a local compressor if you need guarantees about data retention. 5) If you proceed, prefer setting a dedicated NEMO_TOKEN with limited scope (not shared credentials), and ask the publisher for a privacy policy and service SLA. If you want, I can draft questions to ask the publisher or suggest a local ffmpeg-based compression workflow as an alternative.

Getting Started

Share your large video files and I'll get started on AI video compression. Or just tell me what you're thinking.

Try saying:

• "compress my large video files"
• "export 1080p MP4"
• "compress this video to under 50MB"

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.

Best 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 travel video, ask for compress this video to under 50MB without losing 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 more predictable file sizes.

Matching Input to Actions

User prompts referencing best video compressor, 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.

Skill attribution — read from this file's YAML frontmatter at runtime:

• X-Skill-Source: best-video-compressor
• X-Skill-Version: from frontmatter version
• X-Skill-Platform: detect from install path (~/.clawhub/ → clawhub, ~/.cursor/skills/ → cursor, else 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.

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.

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)

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

Common Workflows

Quick edit: Upload → "compress this video to under 50MB without losing 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.

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 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.