Video Editing Jobs

Turn a 3-minute unedited screen recording into 1080p polished edited clips just by typing what you need. Whether it's editing raw footage into finished video...

Security Scan

The skill mostly matches a cloud video-editing workflow, but there are small inconsistencies and a couple of file-system checks (and a metadata mismatch) that are not fully explained and deserve caution before use.

Purpose & Capability

The name/description (cloud video editing) aligns with the API endpoints and operations in SKILL.md (session creation, upload, render/export). However the SKILL.md frontmatter includes a configPaths entry (~/.config/nemovideo/) and runtime instructions say to detect installation paths (~/.clawhub/, ~/.cursor/skills/) to set an attribution header — these filesystem checks are not strictly necessary to provide core editing functionality and are inconsistent with the registry metadata that reported no required config paths.

Instruction Scope

Runtime instructions are concrete and scoped to the service: check NEMO_TOKEN, optionally obtain an anonymous token via the anonymouse auth endpoint, create a session, upload files, send SSE, poll for render results. Reasonable for a cloud editor. Concerning bits: instructions explicitly direct the agent to inspect local install paths and this file's YAML frontmatter to populate X-Skill-Platform and X-Skill-Version headers — those actions read local state outside the minimal need to upload a provided video and may be unnecessary. The SKILL.md also instructs use of local file paths for multipart uploads (expected) and to avoid exposing tokens (good).

Install Mechanism

No install spec and no code files — this is an instruction-only skill. That reduces risk because nothing is downloaded or written by an installer.

Credentials

The only required environment variable is NEMO_TOKEN, which is appropriate for a cloud API. The skill will also attempt to obtain an anonymous token if none is found. The frontmatter's mention of a config path (~/.config/nemovideo/) conflicts with the registry metadata (which showed none); requiring access to that config path would be broader than needed and should be justified.

Persistence & Privilege

always is false and there is no install that requests persistent system-level presence. The skill does ask to keep session_id for the duration of a session (normal) and can be invoked autonomously (platform default) — not a standalone concern here.

What to consider before installing

This skill appears to implement a legitimate cloud video-editing flow, but check the following before enabling it: (1) The skill will upload your raw video to mega-api-prod.nemovideo.ai and may create an anonymous token if you do not supply a NEMO_TOKEN — expect your footage to leave your device. (2) The SKILL.md asks the agent to inspect local install paths and references a config directory in its frontmatter; confirm whether you are comfortable with those filesystem reads or ask the author why they are needed. (3) Prefer giving no permanent NEMO_TOKEN (or give a limited/ephemeral API key) unless you trust the provider and have verified their privacy/retention policy. (4) If you need stronger assurance, request a published homepage, official vendor identity, or documentation about data retention and who has access to stored media before installing. If you want, I can draft questions to ask the skill author or help you redact/limit tokens before testing.

Getting Started

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

Try saying:

• "edit a 3-minute unedited screen recording into a 1080p MP4"
• "trim the pauses, add transitions, and export a clean final cut"
• "editing raw footage into finished video files without manual timeline work for freelance video editors"

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 Editing Jobs — Edit and Export Finished Videos

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

Here's a typical use: you send a a 3-minute unedited screen recording, ask for trim the pauses, add transitions, and export a clean final cut, 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 — shorter clips under 2 minutes process significantly faster and use fewer credits.

Matching Input to Actions

User prompts referencing video editing jobs, 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: video-editing-jobs
• 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.

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

Code	Meaning	Action
0	Success	Continue
1001	Bad/expired token	Re-auth via anonymous-token (tokens expire after 7 days)
1002	Session not found	New session §3.0
2001	No credits	Anonymous: show registration URL with ?bind=<id> (get <id> from create-session or state response when needed). Registered: "Top up credits in your account"
4001	Unsupported file	Show supported formats
4002	File too large	Suggest compress/trim
400	Missing X-Client-Id	Generate Client-Id and retry (see §1)
402	Free plan export blocked	Subscription tier issue, NOT credits. "Register or upgrade your plan to unlock export."
429	Rate 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 "trim the pauses, add transitions, and export a clean final cut" — concrete instructions get better results.

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

Export as MP4 with H.264 codec for the widest compatibility across platforms and clients.

Common Workflows

Quick edit: Upload → "trim the pauses, add transitions, and export a clean final cut" → 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.