Ai Video Generator Free Kiss

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

Security Scan

The skill's behavior (calling a third‑party video API and optionally creating anonymous tokens) is broadly consistent with its description, but there are internal inconsistencies about required credentials and config paths and no provenance/website for the backend — you should confirm those before trusting it with sensitive images or credentials.

Purpose & Capability

The skill declares NEMO_TOKEN as a required primary credential, but the runtime instructions explicitly describe obtaining an anonymous token if NEMO_TOKEN is not present. This mismatch (required vs optional-at-runtime) is incoherent. The skill also lists a config path (~/.config/nemovideo/) inside the SKILL.md metadata while registry metadata reported no required config paths — another inconsistency. Requesting a token to talk to a video-rendering API is expected, but the declarations about what is required are contradictory.

Instruction Scope

Instructions are focused on uploading media and calling nemovideo.ai endpoints (create session, upload, SSE streaming, render). They direct generating a UUID and POSTing for an anonymous token and instruct reading the skill's YAML frontmatter and detecting install path for attribution headers. Those actions are within the scope of operating a cloud render service, but reading install-paths/frontmatter to build X-Skill-Source headers is an extra capability the skill requires and should be justified.

Install Mechanism

No install spec and no code files — instruction-only. This minimizes install risk because nothing is fetched or written by an installer.

Credentials

Only one credential (NEMO_TOKEN) is declared, which fits an API-based renderer, but the SKILL.md flow allows creating an anonymous token if none exists — so requiring NEMO_TOKEN is inconsistent. The SKILL.md also references a config path (~/.config/nemovideo/) not declared elsewhere. Because this skill processes user photos (including faces), the sensitivity is high: the service URL and token handling need clearer justification and provenance before you upload private images or store tokens in your environment.

Persistence & Privilege

always is false and the skill does not request persistent system-wide privileges. It instructs saving session_id for the session lifecycle (normal). Autonomous invocation is allowed (default) but not combined with other high-risk flags.

Scan Findings in Context

[no_code_files] expected: The regex scanner found nothing to analyze because this is an instruction-only skill (only SKILL.md present). This means static rules produced no findings, but the runtime instructions are the primary surface to review.

What to consider before installing

Before installing or using this skill: 1) Confirm the backend domain (mega-api-prod.nemovideo.ai) and ask for a homepage, privacy policy, and terms of service — you will be uploading potentially sensitive face images. 2) Ask the author to clarify whether NEMO_TOKEN is actually required or optional and to reconcile the declared required env/config paths with the SKILL.md flow. 3) Prefer using ephemeral anonymous tokens (if they truly are anonymous) rather than your personal API keys; do not store sensitive credentials in plain environment variables unless you trust the service. 4) If you must upload private photos, verify retention and deletion policies with the service owner. 5) If anything about provenance or the service's reputation is unclear, do not upload sensitive media or credentials. If you want, I can draft questions to ask the skill author or check the endpoint's TLS certificate and WHOIS info for additional provenance.

Getting Started

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

Try saying:

• "generate my images or clips"
• "export 1080p MP4"
• "generate a free kiss scene video"

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.

AI Video Generator Free Kiss — Generate Kiss Videos from Photos

Drop your images or clips in the chat and tell me what you need. I'll handle the AI kiss video creation on cloud GPUs — you don't need anything installed locally.

Here's a typical use: you send a two portrait photos of people, ask for generate a free kiss scene video from these two photos, and about 30-60 seconds later you've got a MP4 file ready to download. The whole thing runs at 1080p by default.

One thing worth knowing — clear front-facing portraits with good lighting produce the most realistic results.

Matching Input to Actions

User prompts referencing ai video generator free kiss, 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-generator-free-kiss
• 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 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

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.

Backend Response Translation

The backend assumes a GUI exists. Translate these into API actions:

Backend says	You do
"click [button]" / "点击"	Execute via API
"open [panel]" / "打开"	Query session state
"drag/drop" / "拖拽"	Send edit via SSE
"preview in timeline"	Show track summary
"Export button" / "导出"	Execute 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 "generate a free kiss scene video from these two photos" — concrete instructions get better results.

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

Export as MP4 for widest compatibility.

Common Workflows

Quick edit: Upload → "generate a free kiss scene video from these two 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.