Editor Ai Deutsch

German-speaking content creators edit raw video footage into edited German videos using this skill. Accepts MP4, MOV, AVI, WebM up to 500MB, renders on cloud...

Security Scan

The skill's declared purpose (German AI video editing) aligns with what it asks for and its runtime instructions, with only minor inconsistencies (metadata vs SKILL.md) and some implementation details you should confirm before installing.

Purpose & Capability

Name/description match the runtime behavior: the skill uploads video, talks to a remote nemo-video API, manages sessions, and returns edited MP4s. The single required credential (NEMO_TOKEN) is appropriate for a remote video-processing backend. Minor inconsistency: the registry metadata reported no required config paths, but the SKILL.md frontmatter lists a config path (~/.config/nemovideo/) and instructs reading install paths for attribution headers.

Instruction Scope

SKILL.md instructions stay largely within editing/export scope (create session, upload files, run SSE, poll render). It also instructs the agent to: auto-obtain an anonymous token via an external POST if NEMO_TOKEN is missing, store session_id for subsequent calls, read this file's YAML frontmatter and detect install paths (~/.clawhub/, ~/.cursor/skills/) to set X-Skill-Platform. These file-system checks and automatic token creation are explainable for attribution and convenience but are implementation details you may want explicit confirmation about (esp. whether any local files are written).

Install Mechanism

Instruction-only skill with no install spec and no code files — lowest install risk. Nothing is downloaded or extracted by the skill package itself.

Credentials

Only NEMO_TOKEN is declared as required and is justified by the backend API. The skill will create an anonymous token via the remote API if NEMO_TOKEN is not set (100 free credits, 7-day lifetime). Confirm whether generated tokens or session IDs are persisted to disk and where; the frontmatter mentions a config path (~/.config/nemovideo/) which could imply local storage but registry metadata omitted it.

Persistence & Privilege

The skill does not request 'always: true' and uses normal autonomous invocation. It instructs storing session_id for API calls, but does not explicitly demand system-wide privileges or modification of other skills. Clarify whether tokens/session IDs are kept only in-memory or persisted under the user's config directory.

Assessment

This skill appears to do what it says: it uploads video to a nemo-video cloud backend, manages sessions, and returns edited MP4s, and it only needs NEMO_TOKEN. Before installing, confirm: (1) whether the skill will write the anonymous token or session IDs to disk (and if so, where — the SKILL.md references ~/.config/nemovideo/ but registry metadata omitted config paths), (2) retention/processing policy for uploaded videos and generated tokens (how long are uploads and tokens kept, are outputs public?), and (3) that the installation will not read or write unrelated files. If you are comfortable with the service creating an anonymous short-lived token and sending your video to mega-api-prod.nemovideo.ai, the skill is coherent with its purpose. If you need stronger assurance, ask the owner for explicit storage/retention and privacy details or request a version that documents exactly where (if anywhere) it persists credentials or sessions.

Getting Started

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

Try saying:

• "edit my raw video footage"
• "export 1080p MP4"
• "schneide das Video automatisch und füge"

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.

Editor AI Deutsch — AI Video Editing in German

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

Say you have a 2-minute unedited screen recording in German and want to schneide das Video automatisch und füge deutsche Untertitel hinzu — the backend processes it in about 1-2 minutes and hands you a 1080p MP4.

Tip: shorter clips under 3 minutes process significantly faster.

Matching Input to Actions

User prompts referencing editor ai deutsch, 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: editor-ai-deutsch
• 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.

SSE Event Handling

Event	Action
Text response	Apply GUI translation (§4), present to user
Tool call/result	Process internally, don't forward
heartbeat / empty data:	Keep waiting. Every 2 min: "⏳ Still working..."
Stream closes	Process 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.

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

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

Tips and Tricks

The backend processes faster when you're specific. Instead of "make it look better", try "schneide das Video automatisch und füge deutsche Untertitel hinzu" — concrete instructions get better results.

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

Export as MP4 for widest compatibility across German streaming platforms.

Common Workflows

Quick edit: Upload → "schneide das Video automatisch und füge deutsche Untertitel hinzu" → 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.