Ai Image To Video Kissing

Skip the learning curve of professional editing software. Describe what you want — animate this image into a short kissing scene video clip — and get animate...

Security Scan

The skill's runtime instructions and requested NEMO_TOKEN largely match its stated purpose (cloud image→video), but there are inconsistent metadata claims about config paths and some ambiguous instructions (platform auto-detection, required headers) and privacy implications from uploading intimate images to an external API that you should review before installing.

Purpose & Capability

The skill is described as a cloud-based image→video service and it requires a single credential (NEMO_TOKEN), which is coherent. However the SKILL.md frontmatter lists a configPaths value (~/.config/nemovideo/) while the registry metadata reported 'required config paths: none' — this mismatch is unexplained and could imply the skill expects local config access that isn't declared.

Instruction Scope

Instructions focus on authenticating, creating a session, uploading user images, streaming SSE for generation, and exporting results — all consistent with the stated purpose. They require insertion of three custom headers on every request and ask the agent to 'auto-detect' an install path/platform for X-Skill-Platform, which is vague and could imply reading the agent's environment or paths. There are no explicit instructions to read arbitrary user files or secrets, but the auto-detect guidance and the undeclared config path are ambiguous.

Install Mechanism

No install spec and no code files (instruction-only). This minimizes local persistence and disk writes; the skill will make network calls to the external API only when invoked.

Credentials

Only one required env var (NEMO_TOKEN) is declared, which is appropriate for a cloud service. However the frontmatter's mention of ~/.config/nemovideo/ (not declared elsewhere in the registry metadata) raises concern: if the skill expects to read that path it could access stored credentials or configuration. Confirm whether the skill will read any local config files before installing.

Persistence & Privilege

always:false and no install behavior means the skill does not request persistent, always-on privileges. It does instruct saving a session_id for the session lifetime (expected) and does not ask to modify other skills or system-wide settings.

What to consider before installing

What to check before installing: - Confirm the NEMO_TOKEN purpose: only supply a token you trust for this service; avoid using a token that grants access to other systems. - Ask the author why the frontmatter lists ~/.config/nemovideo/ (the registry metadata said none). Do they intend to read local config files? If so, which files and why? - Remember this skill uploads user images (often sensitive/intimate) to mega-api-prod.nemovideo.ai — review that service's privacy policy and retention practices before sending personal photos. - The skill uses streaming SSE and requires custom headers; these are reasonable for a cloud API but verify the header values and that nothing else (like other secrets) will be transmitted. - Because this is instruction-only, no local binaries are installed, but network exposure is real: only proceed if you trust the remote service and are comfortable with images being processed off-device. If you can get answers about the configPath usage and confirm the service domain and privacy terms, that information would likely raise confidence to 'high' or allow a benign classification.

Getting Started

Send me your still images and I'll handle the AI video generation. Or just describe what you're after.

Try saying:

• "convert a single portrait photo of two people close together into a 1080p MP4"
• "animate this image into a short kissing scene video clip"
• "animating romantic portrait photos into short video moments for couples, content creators, social media users"

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 Image to Video Kissing — Animate Photos into Video Clips

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

Say you have a single portrait photo of two people close together and want to animate this image into a short kissing scene video clip — the backend processes it in about 30-60 seconds and hands you a 1080p MP4.

Tip: high-resolution face photos with clear lighting produce the most realistic animation results.

Matching Input to Actions

User prompts referencing ai image to video kissing, 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.

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

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

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

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 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 "animate this image into a short kissing scene video clip" — concrete instructions get better results.

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

Export as MP4 for widest compatibility across social platforms.

Common Workflows

Quick edit: Upload → "animate this image into a short kissing scene video clip" → 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.