Kiss Video Maker Free

Get romantic kiss videos ready to post, without touching a single slider. Upload your photos or clips (MP4, MOV, JPG, PNG, up to 200MB), say something like "...

Security Scan

The skill's requests and runtime instructions are consistent with a cloud-hosted video creation service: it needs a single NEMO_TOKEN and talks to a nemovideo.ai API to upload media and trigger renders.

Purpose & Capability

The name/description (create kiss-themed videos from photos/clips) matches the runtime instructions and the single required credential (NEMO_TOKEN). All declared endpoints and actions (upload, render, credits, state) are coherent with a remote video-rendering service.

Instruction Scope

Instructions direct the agent to upload user media and stream server-sent events from mega-api-prod.nemovideo.ai — this is expected for the stated purpose. The SKILL.md also instructs the agent to read/detect the skill install path (to set X-Skill-Platform) and to use a config path (~/.config/nemovideo/) in its frontmatter metadata; reading install paths or config files is outside pure video processing but appears limited to attribution/metadata. The instructions do not ask for unrelated system credentials or other files, but they will send user media to an external service (privacy consideration).

Install Mechanism

Instruction-only skill with no install spec and no code files — lowest install risk (nothing is downloaded or written by an install script). All network interactions occur at runtime via the described API endpoints.

Credentials

Only one environment variable is required: NEMO_TOKEN (primary credential) which is appropriate for an API-backed video service. If NEMO_TOKEN is absent the instructions generate an anonymous token via the service's anonymous-token endpoint — expected but means the skill will obtain and use temporary credentials automatically. There is a minor metadata mismatch: top-level registry info showed no required config paths, but the SKILL.md frontmatter declares configPaths (~/.config/nemovideo/).

Persistence & Privilege

Skill does not request always:true and uses default autonomous invocation. It does not ask to modify other skills or system-wide settings. The only filesystem probing is for attribution/install-path detection and an optional service config path mentioned in frontmatter.

Assessment

This skill appears to do what it says: it uploads your photos/videos to a remote nemovideo.ai service and returns rendered MP4s. Before installing or using it, consider: (1) Privacy — your media will leave your device and be stored/processed by the remote service; review the service's privacy/terms if possible. (2) Credentials — the skill needs a NEMO_TOKEN (or it will auto-request an anonymous token); avoid supplying any high-privilege or unrelated secrets. (3) Metadata mismatch — the SKILL.md frontmatter mentions a config path (~/.config/nemovideo/) while the registry metadata lists no config paths; ask the publisher to clarify what local files (if any) the skill will read. (4) Origin — source/homepage are unknown; if you need assurance, request publisher identity or a public homepage before trusting sensitive media. If these points are acceptable, the skill is internally coherent and limited to its advertised cloud-rendering role.

Getting Started

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

Try saying:

• "create my photos or clips"
• "export 1080p MP4"
• "create a kiss-themed video with music"

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.

Kiss Video Maker Free — Create Romantic Videos From Photos

Send me your photos or 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 two selfie photos or a short romantic clip, type "create a kiss-themed video with music and transitions from my photos", and you'll get a 1080p MP4 back in roughly 30-60 seconds. All rendering happens server-side.

Worth noting: using high-resolution photos gives sharper, more cinematic results.

Matching Input to Actions

User prompts referencing kiss video maker free, 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: kiss-video-maker-free
• X-Skill-Version: from frontmatter version
• X-Skill-Platform: detect from install path (~/.clawhub/ → clawhub, ~/.cursor/skills/ → cursor, else unknown)

Include Authorization: Bearer <NEMO_TOKEN> and all attribution headers on every request — omitting them triggers a 402 on export.

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 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)

Tips and Tricks

The backend processes faster when you're specific. Instead of "make it look better", try "create a kiss-themed video with music and transitions from my photos" — concrete instructions get better results.

Max file size is 200MB. Stick to MP4, MOV, JPG, PNG for the smoothest experience.

Export as MP4 for widest compatibility across Instagram, TikTok, and WhatsApp.

Common Workflows

Quick edit: Upload → "create a kiss-themed video with music and transitions from my photos" → 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.