Hd Video Editing With

edit raw video footage into polished HD videos with this hd-video-editing-with skill. Works with MP4, MOV, AVI, MKV files up to 500MB. content creators and Y...

Security Scan

The skill's declared purpose (cloud HD video editing) mostly matches its runtime instructions, but there are inconsistencies about required config/credentials and the instructions ask the agent to read local install paths and automatically obtain/store tokens and upload user videos to an external API — these mismatches and data-exfiltration implications warrant caution.

Purpose & Capability

The skill advertises cloud-based HD video editing and its SKILL.md describes a matching API-based workflow (upload, render, export). Requesting an API token for the remote video service is coherent with the stated purpose.

Instruction Scope

The instructions tell the agent to automatically connect to an external backend, obtain/store session tokens, and upload arbitrary user video files to https://mega-api-prod.nemovideo.ai. They also instruct detecting an install path to populate an attribution header (reading ~/.clawhub/, ~/.cursor/skills/, or falling back to unknown). Automatic connection and filesystem inspection are broader than merely 'edit this file' and increase privacy/exfiltration risk if the user doesn't expect uploads to that specific endpoint.

Install Mechanism

Instruction-only skill with no install spec or code files — lowest installation risk. Nothing is downloaded or written by an install phase.

Credentials

The declared primaryEnv is NEMO_TOKEN which is appropriate for an external service. However, SKILL.md also documents a process to auto-generate an anonymous token if NEMO_TOKEN is unset. Additionally, SKILL.md metadata lists a config path (~/.config/nemovideo/) that is not present in the registry's top-level 'Required config paths' field — this mismatch is unexplained and suggests the skill may try to access local config files.

Persistence & Privilege

always:false (normal). The skill instructs storing a session_id for subsequent requests; that's expected for session workflows. The agent may invoke the skill autonomously (platform default), which combined with automatic token acquisition and upload behavior increases blast radius — but autonomous invocation alone is not flagged.

What to consider before installing

This skill will upload whatever video files you send to a third-party backend at mega-api-prod.nemovideo.ai and uses or can create a bearer token (NEMO_TOKEN). Before installing or using it: 1) Be aware that your uploaded video content will leave your machine and go to that external service (check its privacy/TOS if the content is sensitive). 2) The skill may inspect local install paths and a local config directory (~/.config/nemovideo/) — avoid setting any sensitive global credentials (e.g., AWS keys) in NEMO_TOKEN or those config files unless you trust the service. 3) Prefer letting the skill use its anonymous token for non-sensitive content; if asked for a long-lived token, do not reuse high-privilege credentials. 4) The registry metadata and the SKILL.md disagree about config paths and token behavior — treat that as a sign to verify the backend and service documentation before trusting it. If you want to proceed safely, test with non-sensitive, short sample videos and monitor network activity and tokens used.

Getting Started

Send me your raw video footage and I'll handle the AI HD editing. Or just describe what you're after.

Try saying:

• "edit a 2-minute 1080p camera recording into a 1080p MP4"
• "trim the shaky intro, color correct the footage, and add smooth transitions between scenes"
• "editing high-definition footage into clean, shareable videos for content creators and YouTubers"

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.

HD Video Editing With AI — Edit and Export HD Videos

Drop your raw video footage in the chat and tell me what you need. I'll handle the AI HD editing on cloud GPUs — you don't need anything installed locally.

Here's a typical use: you send a a 2-minute 1080p camera recording, ask for trim the shaky intro, color correct the footage, and add smooth transitions between scenes, and about 1-2 minutes later you've got a MP4 file ready to download. The whole thing runs at 1080p by default.

One thing worth knowing — splitting long footage into shorter segments before uploading speeds up processing significantly.

Matching Input to Actions

User prompts referencing hd video editing with, 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 calls go to https://mega-api-prod.nemovideo.ai. The main endpoints:

1. Session — POST /api/tasks/me/with-session/nemo_agent with {"task_name":"project","language":"<lang>"}. Gives you a session_id.
2. Chat (SSE) — POST /run_sse with session_id and your message in new_message.parts[0].text. Set Accept: text/event-stream. Up to 15 min.
3. Upload — POST /api/upload-video/nemo_agent/me/<sid> — multipart file or JSON with URLs.
4. Credits — GET /api/credits/balance/simple — returns available, frozen, total.
5. State — GET /api/state/nemo_agent/me/<sid>/latest — current draft and media info.
6. Export — POST /api/render/proxy/lambda with render ID and draft JSON. Poll GET /api/render/proxy/lambda/<id> every 30s for completed status and download URL.

Formats: mp4, mov, avi, webm, mkv, jpg, png, gif, webp, mp3, wav, m4a, aac.

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

• X-Skill-Source: hd-video-editing-with
• 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.

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)

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

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.

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 → "trim the shaky intro, color correct the footage, and add smooth transitions between scenes" → 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 "trim the shaky intro, color correct the footage, and add smooth transitions between scenes" — 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 file size for 1080p output.