Ai Video Editing Tools

Drop a video and describe what you want — trim dead air, add captions, reframe for Reels, or punch up the pacing. This skill brings together ai-video-editing...

Security Scan

The skill is internally consistent with a cloud-based video editing tool: it only asks for a single service token (NEMO_TOKEN), routes edits to the described API, and is instruction-only, but it does include a few operational details you should review before installing (automatic token creation, local file uploads, and hidden token handling).

Purpose & Capability

Name/description (AI video editing) aligns with the declared requirement (NEMO_TOKEN) and the SKILL.md which describes uploading media, transcription, smart cuts, and exports to a cloud backend. The declared config path (~/.config/nemovideo/) and attribution headers are consistent with a remote processing service.

Instruction Scope

Instructions stay within video-editing scope (create session, upload video files, request renders, get credits/state). Two items to be aware of: (1) the skill instructs the agent to auto-obtain an anonymous token and to 'keep setup communication brief' and 'don't display raw API responses or token values to the user' — this is likely to avoid confusing UI output but could also obscure token values from users; (2) uploads are described using local file multipart syntax (files=@/path), which implies the agent will send user-supplied files or should be given explicit file data — ensure the agent only uploads files the user intentionally provides and not arbitrary local filesystem paths.

Install Mechanism

No install spec or remote downloads; this is instruction-only, so nothing is written to disk by an installer. Low install risk.

Credentials

Only one environment variable is required: NEMO_TOKEN (primaryEnv). That is proportionate for a cloud editing backend. The SKILL.md will auto-create an anonymous token if none is present and store it for requests — storing short-lived anonymous tokens is reasonable, but you should be aware a token is created and persisted.

Persistence & Privilege

always:false and no special system-wide privileges requested. The skill stores a session_id/token for use with the remote API (expected for a service session). It does not request persistent global installation privileges.

Assessment

This skill appears to do what it advertises, but review these operational details before installing: (1) Network calls go to https://mega-api-prod.nemovideo.ai — confirm you trust that service and its privacy policy because uploaded videos and transcripts will be sent there. (2) The skill will create and store an anonymous NEMO_TOKEN automatically if you don't provide one; if you prefer explicit consent, set your own token or decline automatic generation. (3) Ensure the agent only uploads files you explicitly provide (do not allow it to read arbitrary local paths). (4) Note the SKILL.md asks not to display raw API responses or tokens — this is reasonable for UX but means you should be deliberate about token handling and revocation. If you don't recognize or trust the skill owner or the API host, don't install or provide files/credentials.

Getting Started

Welcome to your AI video editing workspace — whether you're trimming a raw interview, building a highlight reel, or repurposing long content into social clips, I've got you covered. Drop your footage details or describe your project and let's start editing.

Try saying:

• "I have a 45-minute webinar recording. Help me identify the 5 best clips under 60 seconds each for LinkedIn and write captions for each one."
• "Here's a transcript from my talking-head YouTube video — rewrite the first 10 seconds to be a stronger hook and suggest where I should cut to keep viewers watching past 30 seconds."
• "I need to repurpose a horizontal brand video into a vertical format for Instagram Reels. Tell me what to reframe, where to add text overlays, and how to restructure the pacing."

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.

Edit Smarter: Let AI Handle the Heavy Cuts

Most video editing eats hours you don't have — scrubbing timelines, hunting for the right frame, rewriting captions three times. This skill changes that by letting you describe what you want in plain language and getting back actionable edits, structured timecodes, caption drafts, and scene-by-scene suggestions you can actually use.

Whether you're cleaning up a podcast recording, repurposing a webinar into short-form clips, or building a product demo from raw footage, the skill adapts to your format and goal. Describe your audience, your platform, and your vision — and it maps out an editing plan that fits.

It's not just about cutting — it's about shaping a story. You can ask for pacing feedback, hook rewrites for the first five seconds, lower-third text ideas, or a full edit brief your video editor can execute immediately. Think of it as a creative collaborator that knows the language of video.

Routing Edits to the Right Engine

Each request — whether you're triggering auto-captions, smart cuts, or style transfers — is parsed by intent and routed to the matching processing pipeline based on task type, media length, and output format.

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 API Reference Guide

All render jobs run on a distributed cloud backend that handles frame extraction, model inference, and re-encoding in parallel — so heavy tasks like scene detection or generative B-roll don't block your timeline. Transcription, caption styling, and cut-point analysis each hit dedicated microservices tuned for low-latency media workflows.

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

• X-Skill-Source: ai-video-editing-tools
• X-Skill-Version: from frontmatter version
• X-Skill-Platform: detect from install path (~/.clawhub/ → clawhub, ~/.cursor/skills/ → cursor, else unknown)

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.

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 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

Best Practices

Be specific about your platform first. A TikTok edit and a LinkedIn edit from the same footage need completely different pacing, hook styles, and text placement. Mention your target platform upfront so every suggestion is calibrated correctly.

Share context, not just footage. The more you describe — who's speaking, what the video is promoting, who the audience is — the sharper the edit recommendations. Vague inputs get generic outputs; specific inputs get a real editing roadmap.

Use transcripts whenever possible. If you can paste a transcript or even rough notes, the skill can work with exact language to find the strongest moments, rewrite weak hooks, and build captions that match your tone — rather than guessing from a description alone.

Iterate in rounds. Start with structure (what to cut and keep), then refine captions, then polish on-screen text. Trying to solve everything in one prompt often produces unfocused results. Treat it like a real edit session — pass by pass.

Common Workflows

Podcast-to-Clips Pipeline: Paste your episode transcript and ask for the top 3-5 quotable moments with suggested cut points, hook rewrites, and caption text. You'll get a ready-to-execute brief without scrubbing the timeline manually.

Talking-Head Cleanup: Describe your raw footage — length, topic, any filler or dead air — and the skill will suggest a tighter structure, flag where energy drops, and recommend B-roll prompts to cover jump cuts naturally.

Platform Reformatting: Tell the skill your original format (16:9 YouTube) and your target platform (9:16 TikTok or 1:1 Instagram). It will outline what to reframe, where to add text overlays to replace lost visual space, and how to adjust pacing for the new audience's scroll behavior.

Batch Social Content: Share one long video and a target post count. The skill maps out non-overlapping segments, writes unique captions for each, and suggests platform-specific tweaks so each clip feels native — not recycled.