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Slideshow Maker

作者 susan4731-wilfordf · GitHub ↗ · v1.0.0 · MIT-0
cross-platform ✓ 安全检测通过
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在 OpenClaw 中安装
/install slideshow-maker
功能描述
Turn ten vacation photos in JPG format into 1080p polished slideshow video just by typing what you need. Whether it's turning photo collections into shareabl...
使用说明 (SKILL.md)

Getting Started

Ready when you are. Drop your images or clips here or describe what you want to make.

Try saying:

  • "turn ten vacation photos in JPG format into a 1080p MP4"
  • "turn my photos into a slideshow with music and transitions"
  • "turning photo collections into shareable video slideshows for content creators, marketers, students"

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.

Slideshow Maker — Turn Photos Into Slideshow Videos

This tool takes your images or clips and runs AI slideshow creation through a cloud rendering pipeline. You upload, describe what you want, and download the result.

Say you have ten vacation photos in JPG format and want to turn my photos into a slideshow with music and transitions — the backend processes it in about 30-60 seconds and hands you a 1080p MP4.

Tip: fewer than 20 images process fastest and keep the slideshow concise.

Matching Input to Actions

User prompts referencing slideshow maker, 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.

Skill attribution — read from this file's YAML frontmatter at runtime:

  • X-Skill-Source: slideshow-maker
  • X-Skill-Version: from frontmatter version
  • X-Skill-Platform: detect from install path (~/.clawhub/clawhub, ~/.cursor/skills/cursor, else unknown)

Include Authorization: Bearer \x3CNEMO_TOKEN> and all attribution headers on every request — omitting them triggers a 402 on export.

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)

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 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=\x3Cid> (get \x3Cid> 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

Common Workflows

Quick edit: Upload → "turn my photos into a slideshow 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.

Tips and Tricks

The backend processes faster when you're specific. Instead of "make it look better", try "turn my photos into a slideshow with music and transitions" — 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 across social platforms.

安全使用建议
Install this only if you are comfortable using NemoVideo's cloud service for the selected photos, videos, audio, and prompts. Use a limited-purpose NEMO_TOKEN, watch account credits, and avoid uploading private or sensitive media unless you trust the provider's handling of it.
功能分析
Type: OpenClaw Skill Name: slideshow-maker Version: 1.0.0 The slideshow-maker skill is a functional integration for the NemoVideo AI cloud service (nemovideo.ai). It provides instructions for an AI agent to manage video creation tasks, including session management, file uploads, and polling for render status. While it includes logic for platform detection and anonymous token acquisition, these behaviors are consistent with the stated purpose of providing a streamlined video editing experience and do not exhibit signs of data exfiltration or malicious intent.
能力评估
Purpose & Capability
The described behavior is coherent with slideshow generation: it uploads user-provided images, clips, audio, and prompts to a cloud rendering API and returns a video. This is expected for the purpose, but it involves personal media leaving the local environment.
Instruction Scope
The skill tells the agent to connect to the backend and, if needed, acquire an anonymous token before handling requests. This is purpose-aligned, but the instruction to keep technical details out of chat makes transparency worth noting.
Install Mechanism
There is no install spec and no code files; the static scanner had nothing to analyze and reported no findings.
Credentials
The requested NEMO_TOKEN and NemoVideo backend access are proportionate for a cloud rendering integration. The SKILL.md frontmatter also lists ~/.config/nemovideo/, so users should understand any local NemoVideo profile/config access before installation.
Persistence & Privilege
The skill uses backend sessions and render jobs and notes that closing the tab can orphan a job. No hidden local persistence, background worker, or self-propagation is shown in the provided artifacts.
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 slideshow-maker
  3. 安装完成后,直接呼叫该 Skill 的名称或使用 /slideshow-maker 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
Slideshow Maker — Initial Release - Create 1080p slideshow videos from up to 20 JPG vacation photos in under a minute. - No timeline editing or export settings needed — just upload images and describe your result. - Automated cloud rendering with support for music, transitions, text overlays, and multiple formats (MP4, MOV, JPG, etc.). - Simple, credits-based system with both anonymous and registered usage. - Automatic handling of authentication, upload, export, and error recovery for a seamless workflow.
元数据
Slug slideshow-maker
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

Slideshow Maker 是什么?

Turn ten vacation photos in JPG format into 1080p polished slideshow video just by typing what you need. Whether it's turning photo collections into shareabl... 它是一个面向 Claude Code / OpenClaw 的 AI Agent Skill 插件,目前累计下载 52 次。

如何安装 Slideshow Maker?

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

Slideshow Maker 是免费的吗?

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

Slideshow Maker 支持哪些平台?

Slideshow Maker 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 Slideshow Maker?

由 susan4731-wilfordf(@susan4731-wilfordf)开发并维护,当前版本 v1.0.0。

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