Video Editing With Generative Ai

Get AI-edited videos ready to post, without touching a single slider. Upload your raw video footage (MP4, MOV, AVI, WebM, up to 500MB), say something like "r...

Security Scan

The skill's requirements and runtime instructions are consistent with a cloud-hosted AI video-editing service; nothing requested is disproportionate to its stated purpose, though you should be aware it uploads your video to an external API and the skill source is unknown.

Purpose & Capability

Name, description, and required credential (NEMO_TOKEN) align with a cloud video-editing backend. Minor mismatch: metadata lists a config path (~/.config/nemovideo/) that the SKILL.md does not explicitly read or write — likely harmless but unnecessary in this instruction-only skill.

Instruction Scope

SKILL.md stays within video-editing behavior: token check/creation, session creation, SSE messaging, file upload, render/poll, and credits checks. It instructs uploading user files to https://mega-api-prod.nemovideo.ai and to send multipart file paths (e.g., -F "files=@/path"). That assumes the agent/runtime can access files by path or handle attached uploads; confirm your client actually supplies uploaded file data rather than giving the skill arbitrary filesystem access. The instructions explicitly say not to expose tokens/raw API output, which is good.

Install Mechanism

No install spec and no code files — instruction-only skill. This minimizes on-disk code risk.

Credentials

Only one environment variable is required (NEMO_TOKEN) and it is directly relevant to the API. The skill can also obtain an anonymous token by calling the service if no NEMO_TOKEN is present; this behavior is documented in the instructions. There are no unrelated secrets requested.

Persistence & Privilege

always:false (normal). The skill is allowed to be invoked autonomously (platform default). That alone is not a red flag, but because this skill transmits user video/audio data to an external cloud API, you should be aware an autonomous agent could call the service and upload data without explicit further prompts if the agent were granted that flow.

Assessment

This skill appears coherent for a cloud-based AI video editor, but consider the following before installing: - Privacy: uploaded videos go to mega-api-prod.nemovideo.ai. Do not upload confidential or sensitive footage unless you trust that service and have reviewed its privacy/retention policy. - Token handling: if you provide a persistent NEMO_TOKEN, it grants access to the service; prefer a scoped/dedicated token or anonymous tokens for quick tests. The skill can also obtain an anonymous token automatically (100 free credits, 7-day expiry). - File access: the instructions assume the runtime can attach multipart file data. Confirm how your client supplies uploaded files (streamed attachments vs. filesystem paths) so the skill does not attempt to read arbitrary host filesystem paths. - Source provenance: the skill’s source/homepage is unknown. If you need stronger assurance, request a homepage, privacy policy, or repository from the publisher before using it with real or sensitive content. - Operational limits: the skill documents rate limits, error codes, and required attribution headers — ensure your deployment can send the headers and handle the SSE/polling model. If you accept these tradeoffs and the external service is acceptable for your data, the skill appears consistent with its stated purpose.

Getting Started

Ready when you are. Drop your raw video footage here or describe what you want to make.

Try saying:

• "edit a 3-minute unedited screen recording into a 1080p MP4"
• "remove silences, add b-roll transitions, and generate a title card"
• "automatically editing raw footage into polished videos using AI prompts for content creators and marketers"

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 with Generative AI — Edit and Export AI Videos

Drop your raw video footage in the chat and tell me what you need. I'll handle the AI-powered 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 remove silences, add b-roll transitions, and generate a title card, 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 give the AI more precise edit control.

Matching Input to Actions

User prompts referencing video editing with generative ai, 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.

Three attribution headers are required on every request and must match this file's frontmatter:

Header	Value
X-Skill-Source	video-editing-with-generative-ai
X-Skill-Version	frontmatter version
X-Skill-Platform	auto-detect: clawhub / cursor / unknown from install path

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

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

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.

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)

Tips and Tricks

The backend processes faster when you're specific. Instead of "make it look better", try "remove silences, add b-roll transitions, and generate a title card" — 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 best balance of quality and file size.

Common Workflows

Quick edit: Upload → "remove silences, add b-roll transitions, and generate a title card" → 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.