Best Rtk Compressor

Skip the learning curve of professional editing software. Describe what you want — compress this video using RTK settings to reduce file size without losing...

Security Scan

The skill's requirements and runtime instructions are generally consistent with a cloud-based video-compression service, but there are a few small metadata inconsistencies and expected privacy implications you should review before use.

Purpose & Capability

The skill claims to perform cloud RTK video compression and only requests a single service token (NEMO_TOKEN), which is proportionate. Minor inconsistency: registry metadata listed no config paths, but the SKILL.md frontmatter references a config path (~/.config/nemovideo/). That mismatch should be clarified (it may simply be informational).

Instruction Scope

The SKILL.md instructs the agent to create/use a session, upload videos, stream SSE responses, poll render status, and return download URLs from the named nemovideo API — all of which are consistent with the stated purpose. The instructions do require network calls and uploading user video files to the specified third-party domain, which is expected for a cloud compression service.

Install Mechanism

No install/spec files or downloads are present; this is instruction-only and therefore does not write code to disk or install binaries — lowest-risk install mechanism.

Credentials

Only NEMO_TOKEN is required (declared as primaryEnv), which matches the need to authenticate to the backend. The frontmatter also references a config path, but the registry metadata did not list config paths — this inconsistency should be resolved. No other unrelated credentials are requested.

Persistence & Privilege

The skill does not request always:true and does not ask to modify other skills or system-wide settings. It will create and store session IDs for jobs (expected behavior) and attempts to detect an install path for attribution headers (minor filesystem probe).

Assessment

This skill uploads your video files to a third-party API (https://mega-api-prod.nemovideo.ai) and uses a NEMO_TOKEN to authenticate. Before installing/using it: (1) Confirm you trust the nemovideo service and its privacy/retention policy — do not upload sensitive videos unless you accept that they leave your device. (2) If you don't already have a NEMO_TOKEN, the skill will request an anonymous token from the service (ephemeral); treat that token like any credential. (3) Ask the publisher to clarify the metadata mismatch about ~/.config/nemovideo/ vs. registry metadata (it may be harmless, but it's an inconsistency). (4) Prefer creating scoped/ephemeral API tokens for testing rather than reusing long-lived credentials. If you need higher assurance, request the vendor's privacy/terms links or run uploads through a monitored account first.

Getting Started

Ready when you are. Drop your raw video footage here or describe what you want to make.

Try saying:

• "compress a 2-minute 4K drone footage file at 800MB into a 4K MP4"
• "compress this video using RTK settings to reduce file size without losing quality"
• "compressing large video files with RTK hardware-accelerated encoding for video editors and content creators"

Automatic Setup

On first interaction, connect to the processing API before doing anything else. Show a brief status like "Setting things up...".

Token: If NEMO_TOKEN environment variable is already set, use it and skip to Session below.

Free token: Generate a UUID as client identifier, then POST to https://mega-api-prod.nemovideo.ai/api/auth/anonymous-token with header X-Client-Id: <uuid>. The response field data.token becomes your NEMO_TOKEN (100 credits, 7-day expiry).

Session: POST to https://mega-api-prod.nemovideo.ai/api/tasks/me/with-session/nemo_agent with Bearer auth and body {"task_name":"project"}. Save session_id from the response.

Confirm to the user you're connected and ready. Don't print tokens or raw JSON.

Best RTK Compressor — Compress and Export Optimized Videos

Drop your raw video footage 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 2-minute 4K drone footage file at 800MB, ask for compress this video using RTK settings to reduce file size without losing quality, and about 30-60 seconds later you've got a MP4 file ready to download. The whole thing runs at 4K by default.

One thing worth knowing — shorter clips and lower starting bitrates compress significantly faster.

Matching Input to Actions

User prompts referencing best rtk 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-rtk-compressor
• X-Skill-Version: from frontmatter version
• X-Skill-Platform: detect from install path (~/.clawhub/ → clawhub, ~/.cursor/skills/ → cursor, else unknown)

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

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

Tips and Tricks

The backend processes faster when you're specific. Instead of "make it look better", try "compress this video using RTK settings to reduce file size without losing quality" — concrete instructions get better results.

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

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

Common Workflows

Quick edit: Upload → "compress this video using RTK settings to reduce file size without losing quality" → Download MP4. Takes 30-60 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.