Ai Video Ai

create raw video footage into AI-processed videos with this skill. Works with MP4, MOV, AVI, WebM files up to 500MB. content creators use it for automating v...

Security Scan

The skill's requirements and runtime instructions are consistent with a cloud video-processing integration, but there are a few small metadata inconsistencies and privacy considerations to review before installing.

Purpose & Capability

Name/description (AI video processing, upload/export) match the declared need for a single service token (NEMO_TOKEN) and the API endpoints documented in SKILL.md. The declared functionality (accepting video files, starting render jobs, returning download URLs) aligns with the required permission: access to the remote rendering backend.

Instruction Scope

SKILL.md instructs the agent to POST uploads and control commands to https://mega-api-prod.nemovideo.ai, generate an anonymous token if NEMO_TOKEN is not set, create and persist a session_id, stream SSE responses, and include attribution headers. These actions are expected for a remote video-processing service, but they do mean user media and derived data will be uploaded to an external service and a token will be created/stored automatically unless the environment already contains NEMO_TOKEN.

Install Mechanism

Instruction-only skill with no install spec or code to write to disk. Lowest-risk install mechanism; nothing is downloaded or extracted by the skill itself.

Credentials

Only one environment credential is declared (NEMO_TOKEN), which is appropriate for a single backend API. However, SKILL.md frontmatter references a config path (~/.config/nemovideo/) while the registry metadata lists no required config paths — a minor inconsistency. The skill will auto-generate and store an anonymous token if NEMO_TOKEN is absent, which is functionally reasonable but affects where and how long credentials are persisted.

Persistence & Privilege

always:false and default autonomous invocation are appropriate. The skill instructs storing a session token and session_id for subsequent requests (normal for remote service sessions) but does not request system-wide privileges or to modify other skills.

Assessment

This skill uploads your raw video files and session metadata to an external service (mega-api-prod.nemovideo.ai) and will create/store an anonymous token automatically if you don't provide NEMO_TOKEN. That behavior is consistent with a cloud video-processing tool, but you should: 1) avoid uploading sensitive or confidential footage to an unverified third-party service; 2) prefer setting NEMO_TOKEN yourself (from a trusted account) if you want control over credentials and retention; 3) ask where the token/session is stored (agent-local storage, config file, etc.) and how long it is kept; 4) note the minor metadata mismatch (SKILL.md lists ~/.config/nemovideo/ while registry metadata did not), and consider verifying the service provider or privacy policy before use. If you need higher assurance (who runs the backend, data retention, encryption), seek a skill with a known homepage / vendor or request additional provenance from the skill author.

Getting Started

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

Try saying:

• "create my raw video footage"
• "export 1080p MP4"
• "enhance, edit, and export my video"

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 Video AI — Process and Export AI Videos

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

Say you have a 2-minute raw video clip and want to enhance, edit, and export my video using AI — the backend processes it in about 30-90 seconds and hands you a 1080p MP4.

Tip: shorter clips under 60 seconds process significantly faster.

Matching Input to Actions

User prompts referencing ai video 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.

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-video-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.

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)

Tips and Tricks

The backend processes faster when you're specific. Instead of "make it look better", try "enhance, edit, and export my video using AI" — 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.

Common Workflows

Quick edit: Upload → "enhance, edit, and export my video using AI" → Download MP4. Takes 30-90 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.