Video Compressor Bad Quality

Skip the learning curve of professional editing software. Describe what you want — fix the blocky artifacts and restore sharpness after compression — and get...

Security Scan

The skill's requirements and instructions are consistent with a cloud-hosted video restoration service: it uploads user video files to a remote API and uses a single service token (NEMO_TOKEN) to authenticate.

Purpose & Capability

Name/description (restore compressed video quality) matches the declared behavior: all actions in SKILL.md are calls to a remote 'nemovideo' API for session creation, upload, rendering, and export. The single required credential (NEMO_TOKEN) is appropriate for a cloud service.

Instruction Scope

Instructions direct the agent to upload user-supplied video files and exchange session tokens with https://mega-api-prod.nemovideo.ai, which is expected for remote processing. The skill also instructs detection of an install path (~/.clawhub/ or ~/.cursor/skills/) to populate an X-Skill-Platform header — this requires probing the agent's environment/install path but is narrowly scoped. There are no instructions to read unrelated user files or other environment variables.

Install Mechanism

Instruction-only skill with no install spec or code files — nothing is written to disk by an installer. This is the lowest-risk install model.

Credentials

Only one environment variable is required (NEMO_TOKEN) and it is the primary credential used to authenticate API calls. The SKILL.md provides a fallback to obtain an anonymous token from the service if NEMO_TOKEN is absent; this is proportionate to the described cloud use. No unrelated secrets or multiple credentials are requested.

Persistence & Privilege

always is false and the skill is user-invocable. It does not request permanent presence or modification of other skills or system-wide settings. Autonomous invocation remains possible (platform default) but is not combined with elevated privileges here.

Assessment

This skill uploads whatever video files you give it to an external service at mega-api-prod.nemovideo.ai and requires a NEMO_TOKEN (or will fetch an anonymous token for you). That behavior is consistent with its purpose but means your video content will leave your machine — do not upload sensitive or unreleased material unless you trust the service. The skill may probe common install paths to set an X-Skill-Platform header; this is limited and not a request to read arbitrary files. There is no installer or other credential request. If you have privacy or compliance concerns, verify the service domain and its privacy/billing policies before use, or avoid sending sensitive content. If you want stronger assurance, ask the maintainer for the service's privacy policy or run the skill in an environment with network monitoring to see outbound requests.

Getting Started

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

Try saying:

• "convert my compressed video files"
• "export 1080p MP4"
• "fix the blocky artifacts and restore"

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 Bad Quality Fix — Restore Quality From Compressed Videos

Send me your compressed video files and describe the result you want. The AI quality enhancement runs on remote GPU nodes — nothing to install on your machine.

A quick example: upload a 2-minute MP4 compressed to 50MB with visible artifacts, type "fix the blocky artifacts and restore sharpness after compression", and you'll get a 1080p MP4 back in roughly 1-2 minutes. All rendering happens server-side.

Worth noting: shorter clips process faster and give the AI more precision per frame.

Matching Input to Actions

User prompts referencing video compressor bad quality, 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.

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.

Headers are derived from this file's YAML frontmatter. X-Skill-Source is video-compressor-bad-quality, 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).

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.

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

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

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.

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)

Common Workflows

Quick edit: Upload → "fix the blocky artifacts and restore sharpness after compression" → 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.

Tips and Tricks

The backend processes faster when you're specific. Instead of "make it look better", try "fix the blocky artifacts and restore sharpness after compression" — 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 file size on export.