Video Editing Ai Name

Turn a 2-minute unedited screen recording into 1080p edited video clips just by typing what you need. Whether it's automatically editing raw footage into a p...

Security Scan

The skill's behavior mostly matches a cloud video-editing integration, but there are metadata inconsistencies and a few privacy-risk instructions (filesystem probing for install path, implicit local file uploads) that warrant caution before installing.

Purpose & Capability

The name/description (cloud video editing) aligns with the API calls and upload workflow described in SKILL.md — requiring a NEMO_TOKEN and offering file uploads is expected. However, the registry metadata and the skill's frontmatter disagree: the registry reported no required config paths, but the SKILL.md frontmatter declares a config path (~/.config/nemovideo/). Also the skill declares NEMO_TOKEN as required yet documents an anonymous-token flow when NEMO_TOKEN is absent. These mismatches reduce confidence that the declared requirements are accurate.

Instruction Scope

Runtime instructions are focused on sessions, uploads, SSE streams, and export polling — all appropriate for an editing service. The skill instructs using local file paths for multipart uploads (e.g., -F "files=@/path"), which is expected for video uploads but means the agent will read user-provided files. It also instructs detecting an install path (e.g., checking ~/.clawhub/ or ~/.cursor/skills/) to set an attribution header, which implies probing certain filesystem locations not declared in registry metadata. No instructions request unrelated secrets or broad system data.

Install Mechanism

There is no install spec and no code files — this is instruction-only. That minimizes install-time risk because nothing is downloaded or written by an installer.

Credentials

Only NEMO_TOKEN is declared as the primary credential, which is appropriate for a third-party API. However, the skill provides an anonymous-token endpoint and flow if NEMO_TOKEN is not set, making the 'required' designation inconsistent. No additional unrelated credentials are requested.

Persistence & Privilege

always:false and no instructions to modify other skills or system-wide configs. The skill asks to save session_id for the session workflow (expected) but does not request persistent elevated privileges.

What to consider before installing

This skill appears to do what it says (upload video, run cloud edits, return a download). Before installing, consider: (1) The skill will upload your video to a third-party API (mega-api-prod.nemovideo.ai). Only upload content you’re comfortable sharing with that service. (2) The SKILL.md instructs the agent to read local file paths for uploads and to probe install paths (e.g., ~/.clawhub/, ~/.cursor/skills/). If you want to avoid any filesystem probing, do not grant the agent file access or decline to let it auto-detect install paths. (3) There are metadata inconsistencies: registry metadata claimed no config paths but the skill's frontmatter references ~/.config/nemovideo/; and NEMO_TOKEN is marked required even though an anonymous-token flow exists. These could be sloppy packaging or an oversight — ask the publisher to clarify the intended auth model and why the skill probes install paths. (4) Verify the API hostname and the service's privacy/security policy before sending sensitive videos. No static-scan findings were present, but absence of matches isn’t a guarantee of safety.

Getting Started

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

Try saying:

• "edit my raw video footage"
• "export 1080p MP4"
• "trim the pauses, add transitions, and"

Automatic Setup

On first interaction, connect to the processing API before doing anything else. Show a brief status like "Setting things up...".

Token: If NEMO_TOKEN environment variable is already set, use it and skip to Session below.

Free token: Generate a UUID as client identifier, then POST to https://mega-api-prod.nemovideo.ai/api/auth/anonymous-token with header X-Client-Id: <uuid>. The response field data.token becomes your NEMO_TOKEN (100 credits, 7-day expiry).

Session: POST to https://mega-api-prod.nemovideo.ai/api/tasks/me/with-session/nemo_agent with Bearer auth and body {"task_name":"project"}. Save session_id from the response.

Confirm to the user you're connected and ready. Don't print tokens or raw JSON.

Video Editing AI — Edit and Export Polished Videos

Send me your raw video footage and describe the result you want. The AI-powered video editing runs on remote GPU nodes — nothing to install on your machine.

A quick example: upload a 2-minute unedited screen recording, type "trim the pauses, add transitions, and export with a title card", and you'll get a 1080p MP4 back in roughly 1-2 minutes. All rendering happens server-side.

Worth noting: shorter clips under 60 seconds process significantly faster.

Matching Input to Actions

User prompts referencing video editing ai name, 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-ai-name
• 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.

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 JSON uses short keys: t for tracks, tt for track type (0=video, 1=audio, 7=text), sg for segments, d for duration in ms, m for metadata.

Example timeline summary:

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

Common Workflows

Quick edit: Upload → "trim the pauses, add transitions, and export with 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.

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 with 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 for widest compatibility across platforms.