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Kissing Video Maker Free App

作者 linmillsd7 · GitHub ↗ · v1.0.0 · MIT-0
cross-platform ✓ 安全检测通过
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当前安装
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在 OpenClaw 中安装
/install kissing-video-maker-free-app
功能描述
Turn two photos of a couple or a short 30-second clip into 1080p romantic video clips just by typing what you need. Whether it's creating romantic couple vid...
使用说明 (SKILL.md)

Getting Started

Got photos or clips to work with? Send it over and tell me what you need — I'll take care of the AI romantic video creation.

Try saying:

  • "create two photos of a couple or a short 30-second clip into a 1080p MP4"
  • "create a romantic kissing scene video with music and transitions"
  • "creating romantic couple videos with kissing scenes for social media for TikTok creators"

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: \x3Cuuid>. 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.

Kissing Video Maker Free App — Create Romantic Couple Videos

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

A quick example: upload two photos of a couple or a short 30-second clip, type "create a romantic kissing scene video with music and transitions", and you'll get a 1080p MP4 back in roughly 30-60 seconds. All rendering happens server-side.

Worth noting: using high-resolution face photos gives the AI more detail to work with for realistic results.

Matching Input to Actions

User prompts referencing kissing video maker free app, 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.

All calls go to https://mega-api-prod.nemovideo.ai. The main endpoints:

  1. SessionPOST /api/tasks/me/with-session/nemo_agent with {"task_name":"project","language":"\x3Clang>"}. Gives you a session_id.
  2. Chat (SSE)POST /run_sse with session_id and your message in new_message.parts[0].text. Set Accept: text/event-stream. Up to 15 min.
  3. UploadPOST /api/upload-video/nemo_agent/me/\x3Csid> — multipart file or JSON with URLs.
  4. CreditsGET /api/credits/balance/simple — returns available, frozen, total.
  5. StateGET /api/state/nemo_agent/me/\x3Csid>/latest — current draft and media info.
  6. ExportPOST /api/render/proxy/lambda with render ID and draft JSON. Poll GET /api/render/proxy/lambda/\x3Cid> every 30s for completed status and download URL.

Formats: 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 kissing-video-maker-free-app
X-Skill-Version frontmatter version
X-Skill-Platform auto-detect: clawhub / cursor / unknown from install path

Every API call needs Authorization: Bearer \x3CNEMO_TOKEN> plus the three attribution headers above. If any header is missing, exports return 402.

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)

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

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.

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=\x3Cid>, 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 "create a romantic kissing scene video with music and transitions" — 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 TikTok, Instagram, and YouTube.

Common Workflows

Quick edit: Upload → "create a romantic kissing scene video with music and transitions" → 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.

安全使用建议
This skill appears coherent for its advertised purpose, with no local code or install-time execution shown. Before installing, be comfortable with sending photos or video clips to the NemoVideo cloud service, use only media you have consent to process, and keep the NEMO_TOKEN private.
功能分析
Type: OpenClaw Skill Name: kissing-video-maker-free-app Version: 1.0.0 The skill is a functional wrapper for a video creation service hosted at nemovideo.ai. It includes standard procedures for authentication, session management, and media processing via REST and SSE endpoints. No indicators of malicious intent, data exfiltration, or unauthorized system access were identified in the SKILL.md or metadata.
能力评估
Purpose & Capability
The requested capabilities—uploading photos/clips, generating romantic videos, checking status, credits, and exporting—fit the stated purpose of a cloud video maker.
Instruction Scope
The skill instructs the agent to connect to the remote service on first interaction and route video-editing requests through the API. This is disclosed and purpose-aligned, but it means the skill will make network calls during normal use.
Install Mechanism
No install spec or code files are present; this is an instruction-only skill with no local package installation or executable helper scripts shown.
Credentials
The skill uses a NEMO_TOKEN or obtains an anonymous token for the NemoVideo service. That credential use is expected for the API integration and the instructions say not to print tokens.
Persistence & Privilege
The skill creates a remote session_id and render jobs on the provider service. The artifacts do not show local persistence or background code, but cloud jobs may continue or become orphaned if the session is closed.
如何使用
  1. 确保已安装 OpenClaw(本地或 Docker 部署)
  2. 在对话框中输入安装命令:/install kissing-video-maker-free-app
  3. 安装完成后,直接呼叫该 Skill 的名称或使用 /kissing-video-maker-free-app 触发
  4. 根据 Skill 的参数说明提供必要输入,即可获得结构化输出
版本历史
v1.0.0
- Initial release of Kissing Video Maker Free App (v1.0.0). - Instantly transforms two photos or a short 30s clip into a 1080p romantic video using text instructions. - Seamless cloud-based editing: no software to install, all processing happens server-side. - Supports easy uploads, text-to-video creation, credits checking, and fast 30-90 second exports. - Handles common media formats (mp4, mov, jpg, png) up to 200MB per file. - Automatic session setup with free token for new users; includes error handling and helpful usage tips.
元数据
Slug kissing-video-maker-free-app
版本 1.0.0
许可证 MIT-0
累计安装 0
当前安装数 0
历史版本数 1
常见问题

Kissing Video Maker Free App 是什么?

Turn two photos of a couple or a short 30-second clip into 1080p romantic video clips just by typing what you need. Whether it's creating romantic couple vid... 它是一个面向 Claude Code / OpenClaw 的 AI Agent Skill 插件,目前累计下载 32 次。

如何安装 Kissing Video Maker Free App?

在 OpenClaw 或 Claude Code 对话框中运行命令「/install kissing-video-maker-free-app」即可一键安装,无需额外配置。

Kissing Video Maker Free App 是免费的吗?

是的,Kissing Video Maker Free App 完全免费,采用 MIT-0 许可证,可自由下载、安装和使用。

Kissing Video Maker Free App 支持哪些平台?

Kissing Video Maker Free App 跨平台运行,可在任意部署了 OpenClaw / Claude Code 的环境中使用(cross-platform)。

谁开发了 Kissing Video Maker Free App?

由 linmillsd7(@linmillsd7)开发并维护,当前版本 v1.0.0。

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