Compressor Ai

v1.0.0

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

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Install

OpenClaw Prompt Flow

Install with OpenClaw

Best for remote or guided setup. Copy the exact prompt, then paste it into OpenClaw for susan4731-wilfordf/compressor-ai.

Previewing Install & Setup.
Prompt PreviewInstall & Setup
Install the skill "Compressor Ai" (susan4731-wilfordf/compressor-ai) from ClawHub.
Skill page: https://clawhub.ai/susan4731-wilfordf/compressor-ai
Keep the work scoped to this skill only.
After install, inspect the skill metadata and help me finish setup.
Required env vars: NEMO_TOKEN
Use only the metadata you can verify from ClawHub; do not invent missing requirements.
Ask before making any broader environment changes.

Command Line

CLI Commands

Use the direct CLI path if you want to install manually and keep every step visible.

OpenClaw CLI

Bare skill slug

openclaw skills install compressor-ai

ClawHub CLI

Package manager switcher

npx clawhub@latest install compressor-ai
Security Scan
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high confidence
Purpose & Capability
Name/description (compress/export videos) align with the runtime instructions: the SKILL.md describes uploading videos, creating a session, sending SSE messages, and requesting renders from https://mega-api-prod.nemovideo.ai. The only declared environment credential (NEMO_TOKEN) is appropriate for a remote API-backed compression service.
Instruction Scope
Instructions stay within the stated purpose (auth, session creation, upload, render, poll, download). They explicitly instruct uploading user files to the vendor's cloud endpoints and using SSE for interactive edits. Minor ambiguity: the doc says 'Store the returned session_id' but does not specify persistence location; the frontmatter mentions a config path (~/.config/nemovideo/) and the agent is told to detect install path for X-Skill-Platform headers — these imply reading/writing small local state, but the SKILL.md doesn't instruct arbitrary host-file access beyond user-supplied video paths. Users should expect their videos to be transmitted to an external service.
Install Mechanism
No install spec or code files are present (instruction-only), so nothing is written to disk by an installer. This is the lowest-risk install profile.
Credentials
Only NEMO_TOKEN is required which is proportionate for a remote API. Metadata also lists a config path (~/.config/nemovideo/) and primaryEnv NEMO_TOKEN — reasonable for persisting session tokens, though SKILL.md does not clearly state whether or where tokens/session IDs are persisted. That small mismatch (declared config path vs unspecified persistence) is worth noting.
Persistence & Privilege
The skill is not always-enabled and uses normal model invocation. It does not request elevated platform privileges. The only persistence implied is storing a session_id or token for API calls (normal for a client of a cloud service).
Assessment
This skill is coherent for cloud-based video compression, but it requires uploading your video files to nemovideo.ai and will use or obtain an API token (NEMO_TOKEN) to do so. Before installing: (1) Ensure you are comfortable with your videos being transmitted to and processed by that external service; avoid uploading sensitive content. (2) Ask how/where the anonymous token or session_id is stored (environment vs a local config file) if you care about persistence or revocation. (3) Verify the service domain (mega-api-prod.nemovideo.ai) and privacy terms if this is for confidential material. If you need offline/local-only compression, this skill is not suitable.

Like a lobster shell, security has layers — review code before you run it.

Runtime requirements

🗜️ Clawdis
EnvNEMO_TOKEN
Primary envNEMO_TOKEN
latestvk9788zhg04vvyajf5fvde9qgpn84qt19
81downloads
0stars
1versions
Updated 2w ago
v1.0.0
MIT-0

Getting Started

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

Try saying:

  • "compress my video files"
  • "export 1080p MP4"
  • "compress this video to under 100MB"

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.

Compressor AI — Compress and Export Smaller Videos

This tool takes your video files and runs AI video compression through a cloud rendering pipeline. You upload, describe what you want, and download the result.

Say you have a 500MB 4K travel vlog and want to compress this video to under 100MB without losing quality — the backend processes it in about 30-90 seconds and hands you a 1080p MP4.

Tip: shorter clips compress faster and give more predictable file sizes.

Matching Input to Actions

User prompts referencing compressor ai, aspect ratio, text overlays, or audio tracks get routed to the corresponding action via keyword and intent classification.

User says...ActionSkip 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.

Headers are derived from this file's YAML frontmatter. X-Skill-Source is compressor-ai, 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.

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.

SSE Event Handling

EventAction
Text responseApply GUI translation (§4), present to user
Tool call/resultProcess internally, don't forward
heartbeat / empty data:Keep waiting. Every 2 min: "⏳ Still working..."
Stream closesProcess 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)

Error Handling

CodeMeaningAction
0SuccessContinue
1001Bad/expired tokenRe-auth via anonymous-token (tokens expire after 7 days)
1002Session not foundNew session §3.0
2001No creditsAnonymous: show registration URL with ?bind=<id> (get <id> from create-session or state response when needed). Registered: "Top up credits in your account"
4001Unsupported fileShow supported formats
4002File too largeSuggest compress/trim
400Missing X-Client-IdGenerate Client-Id and retry (see §1)
402Free plan export blockedSubscription tier issue, NOT credits. "Register or upgrade your plan to unlock export."
429Rate limit (1 token/client/7 days)Retry in 30s once

Tips and Tricks

The backend processes faster when you're specific. Instead of "make it look better", try "compress this video to under 100MB 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.

Common Workflows

Quick edit: Upload → "compress this video to under 100MB 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.

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