Video Invideo

create video clips into polished MP4 videos with this skill. Works with MP4, MOV, AVI, WebM files up to 500MB. content creators use it for creating edited vi...

Security Scan

The skill's instructions generally match a cloud video-upload/edit workflow, but there's an unexplained metadata discrepancy (declared config path in SKILL.md vs registry), and the runtime instructions direct the agent to read local files and to fetch/use tokens from an external API — things you should verify before installing.

Purpose & Capability

The skill's name/description (cloud video editing) aligns with the required credential (NEMO_TOKEN) and the listed API endpoints. However, SKILL.md frontmatter declares a config path (~/.config/nemovideo/) while the registry metadata lists no required config paths — this mismatch is unexplained and should be clarified.

Instruction Scope

SKILL.md instructs the agent to create sessions, send SSE messages, and upload user files (multipart upload or URLs) to https://mega-api-prod.nemovideo.ai, which is consistent with a remote render service. It also instructs that if no NEMO_TOKEN exists, the agent should POST to an anonymous-token endpoint to obtain one — again consistent but worth noting because it means the skill will perform network calls and potentially read local file paths provided by the user. The instructions do not request unrelated system data beyond the token and an optional config path, but the use of ~/.config/nemovideo/ in frontmatter expands the scope slightly.

Install Mechanism

No install spec and no code files — instruction-only. This is lower risk from an install perspective (nothing downloaded or written by an installer), but runtime network/file operations still occur per SKILL.md.

Credentials

The skill requests a single credential (NEMO_TOKEN), which is appropriate for a service-client integration. The SKILL.md also references a config path (~/.config/nemovideo/) where tokens/config might be read or stored; the registry metadata omitted this, creating an inconsistency worth confirming. No unrelated secrets are requested.

Persistence & Privilege

always:false and normal invocation settings. The skill does not ask for permanent agent-wide privileges in the provided instructions.

What to consider before installing

This skill appears to implement a cloud video-editing workflow and only needs a single token (NEMO_TOKEN), which is reasonable. Before installing, verify: (1) the source/trustworthiness of https://mega-api-prod.nemovideo.ai (uploads and your videos will be sent there); (2) why SKILL.md frontmatter lists ~/.config/nemovideo/ when the registry shows no config paths — confirm whether the skill will read or write files under that path; (3) whether your NEMO_TOKEN contains other privileges (don’t reuse high-privilege tokens); (4) that you are comfortable allowing the agent to read/upload local video files you provide. If you need more assurance, ask the publisher for a homepage or source repository, or request the skill be updated to remove the config-path discrepancy and to document precisely what is stored in any config directory and what data is sent to the backend.

Getting Started

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

Try saying:

• "create my video clips"
• "export 1080p MP4"
• "turn this footage into a polished"

Getting Connected

Before handling any user request, establish a connection to the backend API. Show a brief status like "Connecting...".

If NEMO_TOKEN is in the environment, use it directly and create a session. Otherwise, acquire a free starter token:

• Generate a UUID as client identifier
• POST to https://mega-api-prod.nemovideo.ai/api/auth/anonymous-token with the X-Client-Id header
• The response includes a token with 100 free credits valid for 7 days — use it as NEMO_TOKEN

Then create a session by POSTing to https://mega-api-prod.nemovideo.ai/api/tasks/me/with-session/nemo_agent with Bearer authorization and body {"task_name":"project","language":"en"}. The session_id in the response is needed for all following requests.

Tell the user you're ready. Keep the technical details out of the chat.

Video InVideo — Create and Export Edited Videos

Send me your video clips and describe the result you want. The AI video creation runs on remote GPU nodes — nothing to install on your machine.

A quick example: upload a 2-minute raw screen recording, type "turn this footage into a polished promo video with text overlays and music", and you'll get a 1080p MP4 back in roughly 1-2 minutes. All rendering happens server-side.

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

Matching Input to Actions

User prompts referencing video invideo, 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.

Three attribution headers are required on every request and must match this file's frontmatter:

Header	Value
X-Skill-Source	video-invideo
X-Skill-Version	frontmatter version
X-Skill-Platform	auto-detect: clawhub / cursor / unknown from install path

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.

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.

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 Codes

• 0 — success, continue normally
• 1001 — token expired or invalid; re-acquire via /api/auth/anonymous-token
• 1002 — session not found; create a new one
• 2001 — out of credits; anonymous users get a registration link with ?bind=<id>, registered users top up
• 4001 — unsupported file type; show accepted formats
• 4002 — file too large; suggest compressing or trimming
• 400 — missing X-Client-Id; generate one and retry
• 402 — free plan export blocked; not a credit issue, subscription tier
• 429 — rate limited; wait 30s and retry once

Tips and Tricks

The backend processes faster when you're specific. Instead of "make it look better", try "turn this footage into a polished promo video with text overlays and music" — 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 and devices.

Common Workflows

Quick edit: Upload → "turn this footage into a polished promo video with text overlays and music" → 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.