Ai Clip Editor

Turn a 2-minute raw screen recording into 1080p edited clip just by typing what you need. Whether it's trimming and polishing short clips for social media or...

Security Scan

The skill's requirements and runtime instructions are largely consistent with a cloud-based AI video editor, but there are a few small metadata inconsistencies and privacy implications (uploads and automatic anonymous token creation) you should understand before installing.

Purpose & Capability

The skill is an AI clip editor and only requests a service token (NEMO_TOKEN) and uses the nemovideo.ai API endpoints described — these are coherent with a cloud video-editing service. Small mismatch: the registry said no required config paths, but the SKILL.md frontmatter declares a config path (~/.config/nemovideo/). This is likely minor bookkeeping inconsistency but worth noting.

Instruction Scope

Instructions focus on uploading user-provided media to the nemovideo.ai backend, session management, SSE streaming, and render polling — which fits the stated purpose. The skill also instructs automatic anonymous-token creation (POST to mega-api-prod.nemovideo.ai) if NEMO_TOKEN is not set, and tells the agent to detect install path to build X-Skill-Platform header (implies reading agent install path). Those behaviors are plausible for this service but expand runtime actions beyond simple local edits: the agent will make outbound network requests and may read install-path information.

Install Mechanism

Instruction-only skill with no install spec or code files. No packages or downloads are installed by the skill itself, which minimizes install-time risk.

Credentials

The only declared credential is NEMO_TOKEN (primaryEnv), which matches the cloud API usage. The SKILL.md also defines an automatic flow to obtain an anonymous token if NEMO_TOKEN is missing (network call to obtain a 7-day token). This is proportionate for a cloud editing service, but you should be aware that the skill will create/store and use tokens if you don't supply one, and the frontmatter/config-path inconsistency was noted.

Persistence & Privilege

The skill does not request always:true and uses session tokens for per-session state (store session_id for requests). That is normal for a cloud service and does not request elevated or persistent platform-wide privileges.

Assessment

This skill will upload any media you give it to mega-api-prod.nemovideo.ai and will call the service to create an anonymous short-lived token if you don't provide NEMO_TOKEN. Before installing/relying on it: (1) confirm you trust the external domain and review its privacy/storage policy for uploaded videos, (2) avoid uploading sensitive or private recordings unless you are comfortable with remote processing and retention, (3) if you prefer not to have automatic token creation, supply a NEMO_TOKEN yourself or disable the skill, (4) note the small metadata inconsistency (config path in SKILL.md) and ask the author to clarify storage behavior for tokens/session data if you need stronger guarantees. If you want higher assurance, request source code or a known homepage/repository for review.

Getting Started

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

Try saying:

• "edit a 2-minute raw screen recording into a 1080p MP4"
• "trim the silences, cut to the best moments, and add smooth transitions"
• "trimming and polishing short clips for social media for content creators"

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.

AI Clip Editor — Edit and Export Polished Clips

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

Say you have a 2-minute raw screen recording and want to trim the silences, cut to the best moments, and add smooth transitions — the backend processes it in about 30-60 seconds and hands you a 1080p MP4.

Tip: clips under 60 seconds process the fastest and give the cleanest AI cuts.

Matching Input to Actions

User prompts referencing ai clip editor, 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.

Base URL: https://mega-api-prod.nemovideo.ai

Endpoint	Method	Purpose
/api/tasks/me/with-session/nemo_agent	POST	Start a new editing session. Body: {"task_name":"project","language":"<lang>"}. Returns session_id.
/run_sse	POST	Send a user message. Body includes app_name, session_id, new_message. Stream response with Accept: text/event-stream. Timeout: 15 min.
/api/upload-video/nemo_agent/me/<sid>	POST	Upload a file (multipart) or URL.
/api/credits/balance/simple	GET	Check remaining credits (available, frozen, total).
/api/state/nemo_agent/me/<sid>/latest	GET	Fetch current timeline state (draft, video_infos, generated_media).
/api/render/proxy/lambda	POST	Start export. Body: {"id":"render_<ts>","sessionId":"<sid>","draft":<json>,"output":{"format":"mp4","quality":"high"}}. Poll status every 30s.

Accepted file types: 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: ai-clip-editor
• 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.

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

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.

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)

Common Workflows

Quick edit: Upload → "trim the silences, cut to the best moments, and add smooth transitions" → Download MP4. Takes 30-60 seconds 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 silences, cut to the best moments, and add smooth transitions" — 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 all platforms.