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Book Maker

作者 mory128 · GitHub ↗ · v1.0.0 · MIT-0
cross-platform ✓ 安全检测通过
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在 OpenClaw 中安装
/install book-maker
功能描述
Turn ten chapter cover images and a title page into 1080p book promo video just by typing what you need. Whether it's creating book trailer or presentation v...
使用说明 (SKILL.md)

Getting Started

Ready when you are. Drop your images, text content here or describe what you want to make.

Try saying:

  • "create ten chapter cover images and a title page into a 1080p MP4"
  • "turn my book pages and chapter images into a promotional book trailer video"
  • "creating book trailer or presentation videos from images and content for authors, publishers, content creators"

Quick Start Setup

This skill connects to a cloud processing backend. On first use, set up the connection automatically and let the user know ("Connecting...").

Token check: Look for NEMO_TOKEN in the environment. If found, skip to session creation. Otherwise:

  • Generate a UUID as client identifier
  • POST https://mega-api-prod.nemovideo.ai/api/auth/anonymous-token with X-Client-Id header
  • Extract data.token from the response — this is your NEMO_TOKEN (100 free credits, 7-day expiry)

Session: POST https://mega-api-prod.nemovideo.ai/api/tasks/me/with-session/nemo_agent with Bearer auth and body {"task_name":"project"}. Keep the returned session_id for all operations.

Let the user know with a brief "Ready!" when setup is complete. Don't expose tokens or raw API output.

Book Maker — Create Book Promo Videos

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

Here's a typical use: you send a ten chapter cover images and a title page, ask for turn my book pages and chapter images into a promotional book trailer video, and about 1-2 minutes later you've got a MP4 file ready to download. The whole thing runs at 1080p by default.

One thing worth knowing — use high-resolution cover images for sharper text and visuals in the final video.

Matching Input to Actions

User prompts referencing book 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.

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":"\x3Clang>"}. 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/\x3Csid> POST Upload a file (multipart) or URL.
/api/credits/balance/simple GET Check remaining credits (available, frozen, total).
/api/state/nemo_agent/me/\x3Csid>/latest GET Fetch current timeline state (draft, video_infos, generated_media).
/api/render/proxy/lambda POST Start export. Body: {"id":"render_\x3Cts>","sessionId":"\x3Csid>","draft":\x3Cjson>,"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 book-maker
X-Skill-Version frontmatter version
X-Skill-Platform auto-detect: clawhub / cursor / unknown from install path

Include Authorization: Bearer \x3CNEMO_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=\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

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.

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 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)

Common Workflows

Quick edit: Upload → "turn my book pages and chapter images into a promotional book trailer video" → Download MP4. Takes 1-2 minutes 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 book pages and chapter images into a promotional book trailer video" — concrete instructions get better results.

Max file size is 500MB. Stick to JPG, PNG, PDF, MP4 for the smoothest experience.

Export as MP4 for widest compatibility across social and retail platforms.

安全使用建议
This skill appears purpose-aligned, but it is a cloud-processing workflow: only upload images, manuscript text, audio, or video you are comfortable sending to NemoVideo, and treat NEMO_TOKEN as a credential.
功能分析
Type: OpenClaw Skill Name: book-maker Version: 1.0.0 The 'book-maker' skill is a legitimate integration for the NemoVideo cloud service, designed to automate the creation of book promotional videos. The instructions in SKILL.md guide the agent through standard API workflows, including anonymous token acquisition, session management, and file uploads to mega-api-prod.nemovideo.ai. All requested permissions (NEMO_TOKEN and ~/.config/nemovideo/) and behaviors are strictly aligned with the stated purpose, with no evidence of data exfiltration or malicious execution.
能力评估
Purpose & Capability
The cloud upload/render workflow is coherent with the stated purpose of making book promo videos, but users should understand their images, text, and optional audio/video are processed by an external backend.
Instruction Scope
The skill instructs the agent to automatically create a token/session and translate backend responses into API actions, which appears purpose-aligned and limited to the NemoVideo workflow.
Install Mechanism
There is no install spec or code to review, and the registry lists no homepage/source; this is not suspicious by itself, but it limits provenance review for a cloud-connected skill.
Credentials
Requiring NEMO_TOKEN and calling NemoVideo APIs is proportionate to the cloud-rendering purpose. No broad local file, shell, or device access is shown.
Persistence & Privilege
The skill uses a bearer token and session_id, and its frontmatter references ~/.config/nemovideo/, but the provided instructions do not show background persistence or unrelated privilege use.
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 book-maker
  3. 安装完成后,直接呼叫该 Skill 的名称或使用 /book-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
Book Maker 1.0.0 — Initial Release - Create 1080p book promo videos from up to ten chapter cover images and a title page, fully automated via chat. - Seamless cloud backend: uploads, credit management, and exports handled with no manual setup. - Automatic user authentication and session management (100 free credits, 7-day expiry for new users). - Supports instant video rendering (30–90 seconds per job) with common image, audio, and video formats. - Streamlined workflows: quick edits, batch jobs, and iterative refinement, with clear guidance and built-in error handling. - Designed for ease of use — just drop your files, describe your video, and download the result.
元数据
Slug book-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

Book Maker 是什么?

Turn ten chapter cover images and a title page into 1080p book promo video just by typing what you need. Whether it's creating book trailer or presentation v... 它是一个面向 Claude Code / OpenClaw 的 AI Agent Skill 插件,目前累计下载 65 次。

如何安装 Book Maker?

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

Book Maker 是免费的吗?

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

Book Maker 支持哪些平台?

Book 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 Book Maker?

由 mory128(@mory128)开发并维护,当前版本 v1.0.0。

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