Video Editing Making Ai

edit raw video footage into edited MP4 videos with this skill. Works with MP4, MOV, AVI, WebM files up to 500MB. content creators and marketers use it for tu...

Security Scan

The skill's requests and runtime instructions are coherent with a cloud video-editing integration, but there are a few small inconsistencies and privacy-relevant behaviors (token creation, local file access, install-path detection) you should be aware of before installing.

Purpose & Capability

The skill claims to perform cloud-based AI video editing and only requests a NEMO_TOKEN credential and (per SKILL.md) a config path under ~/.config/nemovideo/. That aligns with its described purpose. However there is an inconsistency: the registry summary listed no required config paths, while the SKILL.md frontmatter declares ~/.config/nemovideo/. This mismatch should be clarified.

Instruction Scope

The SKILL.md instructs the agent to obtain or use an API token, create sessions, upload local files (multipart form with files=@/path or by URL), stream SSE responses, poll render status, and include attribution headers inferred from the skill's frontmatter and install path. These actions are expected for a cloud editing workflow. Two points to note: (1) the agent is instructed to access local video file paths for upload (explicit file I/O), and (2) it is told to detect install path (~/.clawhub, ~/.cursor/skills/) to set X-Skill-Platform, which requires reading filesystem paths outside the immediate skill data. Neither is inherently malicious, but both affect privacy and require explicit user consent.

Install Mechanism

There is no install spec and no code files — instruction-only skill — so nothing is downloaded or written to disk by an installer. This is the lowest-risk install mechanism.

Credentials

Only one environment credential is declared (NEMO_TOKEN), which is appropriate for a third-party API. The skill also describes an anonymous-token flow that will POST to the vendor and store the returned token; that behavior is consistent with needing a token but means the skill may create and persist a credential if none is provided. The SKILL.md also references a config path (~/.config/nemovideo/) not listed in the registry metadata — another inconsistency to confirm.

Persistence & Privilege

always:false (no forced always-on). The skill will store session_id and use it for subsequent requests, which is normal for a session-based API. It does not request elevated system privileges or change other skills' configs in the instructions.

Assessment

This skill appears to be what it says: a cloud video-editing front end that needs an API token and access to your video files. Before installing or using it, consider: 1) Privacy: uploading videos sends your media to mega-api-prod.nemovideo.ai — confirm you trust that service and its privacy policy. 2) Local file access: the skill explicitly uploads local files (multipart files=@/path); only provide files you want to be uploaded. 3) Token handling: if NEMO_TOKEN is absent the skill will request an anonymous token from the vendor and store it for session use — you may want to pre-provide your own token or clear stored tokens after use. 4) Metadata/access: the skill reads install paths to set an X-Skill-Platform header (it will check common user paths), which involves inspecting filesystem locations — be comfortable with that behavior. 5) Clarify mismatches: the registry metadata did not list any config paths but the SKILL.md does (~/.config/nemovideo/); ask the publisher to confirm whether the skill will read/write that directory and where any tokens/session data are persisted. If any of these behaviors are unacceptable, avoid installation or ask the publisher for a version that only uses explicit user-supplied tokens and explicit file selection.

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"
• "cut the pauses, add background music,"

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.

Video Editing Making AI — Edit and Export AI-Made Videos

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

Say you have a 2-minute unedited screen recording and want to cut the pauses, add background music, and export as a clean highlight reel — the backend processes it in about 1-2 minutes and hands you a 1080p MP4.

Tip: shorter clips under 3 minutes process significantly faster.

Matching Input to Actions

User prompts referencing video editing making 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.

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

• X-Skill-Source: video-editing-making-ai
• 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.

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)

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 "cut the pauses, add background music, and export as a clean highlight reel" — 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.

Common Workflows

Quick edit: Upload → "cut the pauses, add background music, and export as a clean highlight reel" → 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.