mirror of
https://github.com/JimLiu/baoyu-skills.git
synced 2026-07-12 22:09:48 +08:00
Compare commits
7 Commits
| Author | SHA1 | Date | |
|---|---|---|---|
 Jim Liu 宝玉
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776afba5d8 | ||
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Jim Liu 宝玉
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0d677ea171 | ||
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Jim Liu 宝玉
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e519fcdb27 | ||
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Jim Liu 宝玉
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ea14c42716 | ||
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Jim Liu 宝玉
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22d46f32f4 | ||
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Jim Liu 宝玉
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64726e9df1 | ||
 fkysly
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cdc5a9c41c |
@@ -6,7 +6,7 @@
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},
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"metadata": {
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||||
"description": "Skills shared by Baoyu for improving daily work efficiency",
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||||
"version": "1.9.0"
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"version": "1.11.0"
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},
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"plugins": [
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{
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@@ -31,7 +31,8 @@
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"source": "./",
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"strict": false,
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"skills": [
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"./skills/baoyu-danger-gemini-web"
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"./skills/baoyu-danger-gemini-web",
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"./skills/baoyu-image-gen"
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]
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},
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||||
{
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|
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@@ -1,18 +1,32 @@
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||||
---
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||||
name: release-skills
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||||
description: Release workflow for baoyu-skills plugin. This skill should be used when the user wants to create a new release version. It analyzes changes since the last version tag, updates changelogs (EN/CN), bumps the version in marketplace.json, commits changes, and creates a version tag. Supports dry-run mode and breaking change detection.
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description: Release workflow for baoyu-skills plugin. Use when user says "release", "发布", "push", "推送", "new version", "新版本", "bump version", "更新版本", or wants to publish changes to remote. Analyzes changes since last tag, updates CHANGELOG (EN/CN), bumps marketplace.json version, commits, and creates version tag. MUST be used before any git push with uncommitted skill changes.
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||||
---
|
||||
|
||||
# Release Skills
|
||||
|
||||
Automate the release process for baoyu-skills plugin: analyze changes, update changelogs, bump version, commit, and tag.
|
||||
|
||||
## CRITICAL: Mandatory Release Checklist
|
||||
|
||||
**NEVER skip these steps when releasing:**
|
||||
|
||||
1. ✅ Update `CHANGELOG.md` (English)
|
||||
2. ✅ Update `CHANGELOG.zh.md` (Chinese)
|
||||
3. ✅ Update `marketplace.json` version
|
||||
4. ✅ Update `README.md` / `README.zh.md` if needed
|
||||
5. ✅ Commit all changes together
|
||||
6. ✅ Create version tag
|
||||
|
||||
**If user says "直接 push" or "just push" - STILL follow all steps above first!**
|
||||
|
||||
## When to Use
|
||||
|
||||
Trigger this skill when user requests:
|
||||
- "release", "发布", "create release", "new version"
|
||||
- "bump version", "update version"
|
||||
- "prepare release"
|
||||
- "push to remote" (with uncommitted changes)
|
||||
|
||||
## Workflow
|
||||
|
||||
|
||||
@@ -2,6 +2,20 @@
|
||||
|
||||
English | [中文](./CHANGELOG.zh.md)
|
||||
|
||||
## 1.11.0 - 2026-01-21
|
||||
|
||||
### Features
|
||||
- `baoyu-image-gen`: new AI SDK-based image generation skill using official OpenAI and Google APIs. Supports text-to-image, reference images (Google multimodal), aspect ratios, and quality presets (`normal`, `2k`). Auto-detects provider based on available API keys.
|
||||
- `baoyu-slide-deck`: adds Layout Gallery with 24 layout types—10 slide-specific layouts (`title-hero`, `quote-callout`, `key-stat`, `split-screen`, `icon-grid`, `two-columns`, `three-columns`, `image-caption`, `agenda`, `bullet-list`) and 14 infographic-derived layouts (`linear-progression`, `binary-comparison`, `comparison-matrix`, `hierarchical-layers`, `hub-spoke`, `bento-grid`, `funnel`, `dashboard`, `venn-diagram`, `circular-flow`, `winding-roadmap`, `tree-branching`, `iceberg`, `bridge`).
|
||||
|
||||
### Documentation
|
||||
- `README.md`, `README.zh.md`: adds baoyu-image-gen documentation with usage examples, options table, and environment variables; adds Environment Configuration section for API key setup.
|
||||
|
||||
## 1.10.0 - 2026-01-21
|
||||
|
||||
### Features
|
||||
- `baoyu-post-to-x`: adds video posting support—new `x-video.ts` script for posting text with video files (MP4, MOV, WebM). Supports preview mode and handles video processing timeouts.
|
||||
|
||||
## 1.9.0 - 2026-01-20
|
||||
|
||||
### Features
|
||||
|
||||
@@ -2,6 +2,20 @@
|
||||
|
||||
[English](./CHANGELOG.md) | 中文
|
||||
|
||||
## 1.11.0 - 2026-01-21
|
||||
|
||||
### 新功能
|
||||
- `baoyu-image-gen`：新增基于 AI SDK 的图像生成技能，使用官方 OpenAI 和 Google API。支持文生图、参考图（Google 多模态）、宽高比和质量预设（`normal`、`2k`）。根据可用的 API 密钥自动选择服务商。
|
||||
- `baoyu-slide-deck`：新增布局库（Layout Gallery），包含 24 种布局类型——10 种幻灯片专用布局（`title-hero` 标题主图、`quote-callout` 引用突出、`key-stat` 关键数据、`split-screen` 分屏、`icon-grid` 图标网格、`two-columns` 双栏、`three-columns` 三栏、`image-caption` 图片说明、`agenda` 议程、`bullet-list` 要点列表）和 14 种信息图衍生布局（`linear-progression` 线性流程、`binary-comparison` 二元对比、`comparison-matrix` 对比矩阵、`hierarchical-layers` 层级、`hub-spoke` 中心辐射、`bento-grid` 便当盒、`funnel` 漏斗、`dashboard` 仪表盘、`venn-diagram` 韦恩图、`circular-flow` 循环流程、`winding-roadmap` 蜿蜒路线图、`tree-branching` 树状分支、`iceberg` 冰山、`bridge` 桥接）。
|
||||
|
||||
### 文档
|
||||
- `README.md`、`README.zh.md`：新增 baoyu-image-gen 文档，包含用法示例、选项表和环境变量说明；新增环境配置章节，介绍 API 密钥设置方法。
|
||||
|
||||
## 1.10.0 - 2026-01-21
|
||||
|
||||
### 新功能
|
||||
- `baoyu-post-to-x`：新增视频发布支持——新增 `x-video.ts` 脚本，支持发布带视频的推文（MP4、MOV、WebM 格式）。支持预览模式，自动处理视频上传等待。
|
||||
|
||||
## 1.9.0 - 2026-01-20
|
||||
|
||||
### 新功能
|
||||
|
||||
@@ -78,6 +78,16 @@ npx -y bun skills/baoyu-danger-gemini-web/scripts/main.ts --promptfiles system.m
|
||||
|
||||
`.claude-plugin/marketplace.json` defines plugin metadata and skill paths. Version follows semver.
|
||||
|
||||
## Release Process
|
||||
|
||||
**IMPORTANT**: When user requests release/发布/push, ALWAYS use `/release-skills` workflow.
|
||||
|
||||
**Never skip**:
|
||||
1. `CHANGELOG.md` + `CHANGELOG.zh.md` - Both must be updated
|
||||
2. `marketplace.json` version bump
|
||||
3. `README.md` + `README.zh.md` if applicable
|
||||
4. All files committed together before tag
|
||||
|
||||
## Adding New Skills
|
||||
|
||||
**IMPORTANT**: All skills MUST use `baoyu-` prefix to avoid conflicts when users import this plugin.
|
||||
|
||||
@@ -14,7 +14,7 @@ Skills shared by Baoyu for improving daily work efficiency with Claude Code.
|
||||
### Quick Install (Recommended)
|
||||
|
||||
```bash
|
||||
npx add-skill jimliu/baoyu-skills
|
||||
npx skills add jimliu/baoyu-skills
|
||||
```
|
||||
|
||||
### Register as Plugin Marketplace
|
||||
@@ -54,7 +54,7 @@ Simply tell Claude Code:
|
||||
| Plugin | Description | Skills |
|
||||
|--------|-------------|--------|
|
||||
| **content-skills** | Content generation and publishing | [xhs-images](#baoyu-xhs-images), [infographic](#baoyu-infographic), [cover-image](#baoyu-cover-image), [slide-deck](#baoyu-slide-deck), [comic](#baoyu-comic), [article-illustrator](#baoyu-article-illustrator), [post-to-x](#baoyu-post-to-x), [post-to-wechat](#baoyu-post-to-wechat) |
|
||||
| **ai-generation-skills** | AI-powered generation backends | [danger-gemini-web](#baoyu-danger-gemini-web) |
|
||||
| **ai-generation-skills** | AI-powered generation backends | [image-gen](#baoyu-image-gen), [danger-gemini-web](#baoyu-danger-gemini-web) |
|
||||
| **utility-skills** | Utility tools for content processing | [danger-x-to-markdown](#baoyu-danger-x-to-markdown), [compress-image](#baoyu-compress-image) |
|
||||
|
||||
## Update Skills
|
||||
@@ -515,6 +515,55 @@ Prerequisites: Google Chrome installed. First run requires QR code login (sessio
|
||||
|
||||
AI-powered generation backends.
|
||||
|
||||
#### baoyu-image-gen
|
||||
|
||||
AI SDK-based image generation using official OpenAI and Google APIs. Supports text-to-image, reference images, aspect ratios, and quality presets.
|
||||
|
||||
```bash
|
||||
# Basic generation (auto-detect provider)
|
||||
/baoyu-image-gen --prompt "A cute cat" --image cat.png
|
||||
|
||||
# With aspect ratio
|
||||
/baoyu-image-gen --prompt "A landscape" --image landscape.png --ar 16:9
|
||||
|
||||
# High quality (2k)
|
||||
/baoyu-image-gen --prompt "A banner" --image banner.png --quality 2k
|
||||
|
||||
# Specific provider
|
||||
/baoyu-image-gen --prompt "A cat" --image cat.png --provider openai
|
||||
|
||||
# With reference images (Google multimodal only)
|
||||
/baoyu-image-gen --prompt "Make it blue" --image out.png --ref source.png
|
||||
```
|
||||
|
||||
**Options**:
|
||||
| Option | Description |
|
||||
|--------|-------------|
|
||||
| `--prompt`, `-p` | Prompt text |
|
||||
| `--promptfiles` | Read prompt from files (concatenated) |
|
||||
| `--image` | Output image path (required) |
|
||||
| `--provider` | `google` or `openai` (default: google) |
|
||||
| `--model`, `-m` | Model ID |
|
||||
| `--ar` | Aspect ratio (e.g., `16:9`, `1:1`, `4:3`) |
|
||||
| `--size` | Size (e.g., `1024x1024`) |
|
||||
| `--quality` | `normal` or `2k` (default: normal) |
|
||||
| `--ref` | Reference images (Google multimodal only) |
|
||||
|
||||
**Environment Variables** (see [Environment Configuration](#environment-configuration) for setup):
|
||||
| Variable | Description | Default |
|
||||
|----------|-------------|---------|
|
||||
| `OPENAI_API_KEY` | OpenAI API key | - |
|
||||
| `GOOGLE_API_KEY` | Google API key | - |
|
||||
| `OPENAI_IMAGE_MODEL` | OpenAI model | `gpt-image-1.5` |
|
||||
| `GOOGLE_IMAGE_MODEL` | Google model | `gemini-3-pro-image-preview` |
|
||||
| `OPENAI_BASE_URL` | Custom OpenAI endpoint | - |
|
||||
| `GOOGLE_BASE_URL` | Custom Google endpoint | - |
|
||||
|
||||
**Provider Auto-Selection**:
|
||||
1. If `--provider` specified → use it
|
||||
2. If only one API key available → use that provider
|
||||
3. If both available → default to Google
|
||||
|
||||
#### baoyu-danger-gemini-web
|
||||
|
||||
Interacts with Gemini Web to generate text and images.
|
||||
@@ -568,6 +617,44 @@ Compress images to reduce file size while maintaining quality.
|
||||
/baoyu-compress-image path/to/images/ --quality 80
|
||||
```
|
||||
|
||||
## Environment Configuration
|
||||
|
||||
Some skills require API keys or custom configuration. Environment variables can be set in `.env` files:
|
||||
|
||||
**Load Priority** (higher priority overrides lower):
|
||||
1. CLI environment variables (e.g., `OPENAI_API_KEY=xxx /baoyu-image-gen ...`)
|
||||
2. `process.env` (system environment)
|
||||
3. `<cwd>/.baoyu-skills/.env` (project-level)
|
||||
4. `~/.baoyu-skills/.env` (user-level)
|
||||
|
||||
**Setup**:
|
||||
|
||||
```bash
|
||||
# Create user-level config directory
|
||||
mkdir -p ~/.baoyu-skills
|
||||
|
||||
# Create .env file
|
||||
cat > ~/.baoyu-skills/.env << 'EOF'
|
||||
# OpenAI
|
||||
OPENAI_API_KEY=sk-xxx
|
||||
OPENAI_IMAGE_MODEL=gpt-image-1.5
|
||||
# OPENAI_BASE_URL=https://api.openai.com/v1
|
||||
|
||||
# Google
|
||||
GOOGLE_API_KEY=xxx
|
||||
GOOGLE_IMAGE_MODEL=gemini-3-pro-image-preview
|
||||
# GOOGLE_BASE_URL=https://generativelanguage.googleapis.com/v1beta
|
||||
EOF
|
||||
```
|
||||
|
||||
**Project-level config** (for team sharing):
|
||||
|
||||
```bash
|
||||
mkdir -p .baoyu-skills
|
||||
# Add .baoyu-skills/.env to .gitignore to avoid committing secrets
|
||||
echo ".baoyu-skills/.env" >> .gitignore
|
||||
```
|
||||
|
||||
## Customization
|
||||
|
||||
All skills support customization via `EXTEND.md` files. Create an extension file to override default styles, add custom configurations, or define your own presets.
|
||||
|
||||
+89
-2
@@ -14,7 +14,7 @@
|
||||
### 快速安装（推荐）
|
||||
|
||||
```bash
|
||||
npx add-skill jimliu/baoyu-skills
|
||||
npx skills add jimliu/baoyu-skills
|
||||
```
|
||||
|
||||
### 注册插件市场
|
||||
@@ -54,7 +54,7 @@ npx add-skill jimliu/baoyu-skills
|
||||
| 插件 | 说明 | 包含技能 |
|
||||
|------|------|----------|
|
||||
| **content-skills** | 内容生成和发布 | [xhs-images](#baoyu-xhs-images), [infographic](#baoyu-infographic), [cover-image](#baoyu-cover-image), [slide-deck](#baoyu-slide-deck), [comic](#baoyu-comic), [article-illustrator](#baoyu-article-illustrator), [post-to-x](#baoyu-post-to-x), [post-to-wechat](#baoyu-post-to-wechat) |
|
||||
| **ai-generation-skills** | AI 生成后端 | [danger-gemini-web](#baoyu-danger-gemini-web) |
|
||||
| **ai-generation-skills** | AI 生成后端 | [image-gen](#baoyu-image-gen), [danger-gemini-web](#baoyu-danger-gemini-web) |
|
||||
| **utility-skills** | 内容处理工具 | [danger-x-to-markdown](#baoyu-danger-x-to-markdown), [compress-image](#baoyu-compress-image) |
|
||||
|
||||
## 更新技能
|
||||
@@ -515,6 +515,55 @@ npx add-skill jimliu/baoyu-skills
|
||||
|
||||
AI 驱动的生成后端。
|
||||
|
||||
#### baoyu-image-gen
|
||||
|
||||
基于 AI SDK 的图像生成，使用官方 OpenAI 和 Google API。支持文生图、参考图、宽高比和质量预设。
|
||||
|
||||
```bash
|
||||
# 基础生成（自动检测服务商）
|
||||
/baoyu-image-gen --prompt "一只可爱的猫" --image cat.png
|
||||
|
||||
# 指定宽高比
|
||||
/baoyu-image-gen --prompt "风景图" --image landscape.png --ar 16:9
|
||||
|
||||
# 高质量（2k 分辨率）
|
||||
/baoyu-image-gen --prompt "横幅图" --image banner.png --quality 2k
|
||||
|
||||
# 指定服务商
|
||||
/baoyu-image-gen --prompt "一只猫" --image cat.png --provider openai
|
||||
|
||||
# 带参考图（仅 Google 多模态支持）
|
||||
/baoyu-image-gen --prompt "把它变成蓝色" --image out.png --ref source.png
|
||||
```
|
||||
|
||||
**选项**：
|
||||
| 选项 | 说明 |
|
||||
|------|------|
|
||||
| `--prompt`, `-p` | 提示词文本 |
|
||||
| `--promptfiles` | 从文件读取提示词（多文件拼接） |
|
||||
| `--image` | 输出图片路径（必需） |
|
||||
| `--provider` | `google` 或 `openai`（默认：google） |
|
||||
| `--model`, `-m` | 模型 ID |
|
||||
| `--ar` | 宽高比（如 `16:9`、`1:1`、`4:3`） |
|
||||
| `--size` | 尺寸（如 `1024x1024`） |
|
||||
| `--quality` | `normal` 或 `2k`（默认：normal） |
|
||||
| `--ref` | 参考图片（仅 Google 多模态支持） |
|
||||
|
||||
**环境变量**（配置方法见[环境配置](#环境配置)）：
|
||||
| 变量 | 说明 | 默认值 |
|
||||
|------|------|--------|
|
||||
| `OPENAI_API_KEY` | OpenAI API 密钥 | - |
|
||||
| `GOOGLE_API_KEY` | Google API 密钥 | - |
|
||||
| `OPENAI_IMAGE_MODEL` | OpenAI 模型 | `gpt-image-1.5` |
|
||||
| `GOOGLE_IMAGE_MODEL` | Google 模型 | `gemini-3-pro-image-preview` |
|
||||
| `OPENAI_BASE_URL` | 自定义 OpenAI 端点 | - |
|
||||
| `GOOGLE_BASE_URL` | 自定义 Google 端点 | - |
|
||||
|
||||
**服务商自动选择**：
|
||||
1. 如果指定了 `--provider` → 使用指定的
|
||||
2. 如果只有一个 API 密钥 → 使用对应服务商
|
||||
3. 如果两个都有 → 默认使用 Google
|
||||
|
||||
#### baoyu-danger-gemini-web
|
||||
|
||||
与 Gemini Web 交互，生成文本和图片。
|
||||
@@ -568,6 +617,44 @@ AI 驱动的生成后端。
|
||||
/baoyu-compress-image path/to/images/ --quality 80
|
||||
```
|
||||
|
||||
## 环境配置
|
||||
|
||||
部分技能需要 API 密钥或自定义配置。环境变量可以在 `.env` 文件中设置：
|
||||
|
||||
**加载优先级**（高优先级覆盖低优先级）：
|
||||
1. 命令行环境变量（如 `OPENAI_API_KEY=xxx /baoyu-image-gen ...`）
|
||||
2. `process.env`（系统环境变量）
|
||||
3. `<cwd>/.baoyu-skills/.env`（项目级）
|
||||
4. `~/.baoyu-skills/.env`（用户级）
|
||||
|
||||
**配置方法**：
|
||||
|
||||
```bash
|
||||
# 创建用户级配置目录
|
||||
mkdir -p ~/.baoyu-skills
|
||||
|
||||
# 创建 .env 文件
|
||||
cat > ~/.baoyu-skills/.env << 'EOF'
|
||||
# OpenAI
|
||||
OPENAI_API_KEY=sk-xxx
|
||||
OPENAI_IMAGE_MODEL=gpt-image-1.5
|
||||
# OPENAI_BASE_URL=https://api.openai.com/v1
|
||||
|
||||
# Google
|
||||
GOOGLE_API_KEY=xxx
|
||||
GOOGLE_IMAGE_MODEL=gemini-3-pro-image-preview
|
||||
# GOOGLE_BASE_URL=https://generativelanguage.googleapis.com/v1beta
|
||||
EOF
|
||||
```
|
||||
|
||||
**项目级配置**（团队共享）：
|
||||
|
||||
```bash
|
||||
mkdir -p .baoyu-skills
|
||||
# 将 .baoyu-skills/.env 添加到 .gitignore 避免提交密钥
|
||||
echo ".baoyu-skills/.env" >> .gitignore
|
||||
```
|
||||
|
||||
## 自定义扩展
|
||||
|
||||
所有技能支持通过 `EXTEND.md` 文件自定义。创建扩展文件可覆盖默认样式、添加自定义配置或定义个人预设。
|
||||
|
||||
@@ -0,0 +1,219 @@
|
||||
---
|
||||
name: baoyu-image-gen
|
||||
description: AI SDK-based image generation using official OpenAI and Google APIs. Supports text-to-image, reference images, aspect ratios, and quality presets.
|
||||
---
|
||||
|
||||
# Image Generation (AI SDK)
|
||||
|
||||
Official API-based image generation via AI SDK. Supports OpenAI (DALL-E, GPT Image) and Google (Imagen, Gemini multimodal).
|
||||
|
||||
## Script Directory
|
||||
|
||||
**Important**: All scripts are located in the `scripts/` subdirectory of this skill.
|
||||
|
||||
**Agent Execution Instructions**:
|
||||
1. Determine this SKILL.md file's directory path as `SKILL_DIR`
|
||||
2. Script path = `${SKILL_DIR}/scripts/<script-name>.ts`
|
||||
3. Replace all `${SKILL_DIR}` in this document with the actual path
|
||||
|
||||
**Script Reference**:
|
||||
| Script | Purpose |
|
||||
|--------|---------|
|
||||
| `scripts/main.ts` | CLI entry point for image generation |
|
||||
|
||||
## Quick Start
|
||||
|
||||
```bash
|
||||
# Basic generation (auto-detect provider)
|
||||
npx -y bun ${SKILL_DIR}/scripts/main.ts --prompt "A cat" --image cat.png
|
||||
|
||||
# With aspect ratio
|
||||
npx -y bun ${SKILL_DIR}/scripts/main.ts --prompt "A landscape" --image landscape.png --ar 16:9
|
||||
|
||||
# High quality (2k)
|
||||
npx -y bun ${SKILL_DIR}/scripts/main.ts --prompt "A cat" --image cat.png --quality 2k
|
||||
|
||||
# Specific provider
|
||||
npx -y bun ${SKILL_DIR}/scripts/main.ts --prompt "A cat" --image cat.png --provider openai
|
||||
|
||||
# From prompt files
|
||||
npx -y bun ${SKILL_DIR}/scripts/main.ts --promptfiles system.md content.md --image out.png
|
||||
|
||||
# With reference images (Google multimodal only)
|
||||
npx -y bun ${SKILL_DIR}/scripts/main.ts --prompt "Make blue" --image out.png --ref source.png
|
||||
```
|
||||
|
||||
## Commands
|
||||
|
||||
### Basic Image Generation
|
||||
|
||||
```bash
|
||||
# Generate with prompt
|
||||
npx -y bun ${SKILL_DIR}/scripts/main.ts --prompt "A sunset over mountains" --image sunset.png
|
||||
|
||||
# Shorthand
|
||||
npx -y bun ${SKILL_DIR}/scripts/main.ts -p "A cute robot" --image robot.png
|
||||
```
|
||||
|
||||
### Aspect Ratios
|
||||
|
||||
```bash
|
||||
# Common ratios: 1:1, 16:9, 9:16, 4:3, 3:4, 2.35:1
|
||||
npx -y bun ${SKILL_DIR}/scripts/main.ts --prompt "A portrait" --image portrait.png --ar 3:4
|
||||
|
||||
# Or specify exact size
|
||||
npx -y bun ${SKILL_DIR}/scripts/main.ts --prompt "Banner" --image banner.png --size 1792x1024
|
||||
```
|
||||
|
||||
### Reference Images (Google Multimodal)
|
||||
|
||||
```bash
|
||||
# Image editing with reference
|
||||
npx -y bun ${SKILL_DIR}/scripts/main.ts --prompt "Make it blue" --image blue.png --ref original.png
|
||||
|
||||
# Multiple references
|
||||
npx -y bun ${SKILL_DIR}/scripts/main.ts --prompt "Combine these styles" --image out.png --ref a.png b.png
|
||||
```
|
||||
|
||||
### Quality Presets
|
||||
|
||||
```bash
|
||||
# Normal quality (default)
|
||||
npx -y bun ${SKILL_DIR}/scripts/main.ts --prompt "A cat" --image cat.png --quality normal
|
||||
|
||||
# High quality (2k resolution)
|
||||
npx -y bun ${SKILL_DIR}/scripts/main.ts --prompt "A cat" --image cat.png --quality 2k
|
||||
```
|
||||
|
||||
### Output Formats
|
||||
|
||||
```bash
|
||||
# Plain output (prints saved path)
|
||||
npx -y bun ${SKILL_DIR}/scripts/main.ts --prompt "A cat" --image cat.png
|
||||
|
||||
# JSON output
|
||||
npx -y bun ${SKILL_DIR}/scripts/main.ts --prompt "A cat" --image cat.png --json
|
||||
```
|
||||
|
||||
## Options
|
||||
|
||||
| Option | Description |
|
||||
|--------|-------------|
|
||||
| `--prompt <text>`, `-p` | Prompt text |
|
||||
| `--promptfiles <files...>` | Read prompt from files (concatenated) |
|
||||
| `--image <path>` | Output image path (required) |
|
||||
| `--provider google\|openai` | Force provider (default: google) |
|
||||
| `--model <id>`, `-m` | Model ID |
|
||||
| `--ar <ratio>` | Aspect ratio (e.g., `16:9`, `1:1`, `4:3`) |
|
||||
| `--size <WxH>` | Size (e.g., `1024x1024`) |
|
||||
| `--quality normal\|2k` | Quality preset (default: normal) |
|
||||
| `--ref <files...>` | Reference images (Google multimodal only) |
|
||||
| `--n <count>` | Number of images |
|
||||
| `--json` | JSON output |
|
||||
| `--help`, `-h` | Show help |
|
||||
|
||||
## Environment Variables
|
||||
|
||||
| Variable | Description | Default |
|
||||
|----------|-------------|---------|
|
||||
| `OPENAI_API_KEY` | OpenAI API key | - |
|
||||
| `GOOGLE_API_KEY` | Google API key | - |
|
||||
| `OPENAI_IMAGE_MODEL` | OpenAI model | `gpt-image-1.5` |
|
||||
| `GOOGLE_IMAGE_MODEL` | Google model | `gemini-3-pro-image-preview` |
|
||||
| `OPENAI_BASE_URL` | Custom OpenAI endpoint | - |
|
||||
| `GOOGLE_BASE_URL` | Custom Google endpoint | - |
|
||||
|
||||
**Load Priority**: CLI args > `process.env` > `<cwd>/.baoyu-skills/.env` > `~/.baoyu-skills/.env`
|
||||
|
||||
## Provider & Model Strategy
|
||||
|
||||
### Auto-Selection
|
||||
|
||||
1. If `--provider` specified → use it
|
||||
2. If only one API key available → use that provider
|
||||
3. If both available → default to Google (multimodal LLMs more versatile)
|
||||
|
||||
### API Selection by Model Type
|
||||
|
||||
| Model Category | API Function | Example Models |
|
||||
|----------------|--------------|----------------|
|
||||
| Google Multimodal | `generateText` | `gemini-2.0-flash-exp-image-generation` |
|
||||
| Google Imagen | `experimental_generateImage` | `imagen-3.0-generate-002` |
|
||||
| OpenAI | `experimental_generateImage` | `gpt-image-1`, `dall-e-3` |
|
||||
|
||||
### Available Models
|
||||
|
||||
**Google**:
|
||||
- `gemini-3-pro-image-preview` - Default, multimodal generation
|
||||
- `gemini-2.0-flash-exp-image-generation` - Gemini 2.0 Flash
|
||||
- `imagen-3.0-generate-002` - Imagen 3
|
||||
|
||||
**OpenAI**:
|
||||
- `gpt-image-1.5` - Default, GPT Image 1.5
|
||||
- `gpt-image-1` - GPT Image 1
|
||||
- `dall-e-3` - DALL-E 3
|
||||
|
||||
## Quality Presets
|
||||
|
||||
| Preset | OpenAI | Google | Use Case |
|
||||
|--------|--------|--------|----------|
|
||||
| `normal` | 1024x1024 | Default | Covers, illustrations |
|
||||
| `2k` | 2048x2048 | "2048px" in prompt | Infographics, slides |
|
||||
|
||||
## Aspect Ratio Handling
|
||||
|
||||
- **Multimodal LLMs**: Embedded in prompt (e.g., `"... aspect ratio 16:9"`)
|
||||
- **Image-only models**: Uses `aspectRatio` or `size` parameter
|
||||
- **Common ratios**: 1:1, 16:9, 9:16, 4:3, 3:4, 2.35:1
|
||||
|
||||
## Examples
|
||||
|
||||
### Generate Cover Image
|
||||
|
||||
```bash
|
||||
npx -y bun ${SKILL_DIR}/scripts/main.ts \
|
||||
--prompt "A minimalist tech illustration with blue gradients" \
|
||||
--image cover.png --ar 2.35:1 --quality 2k
|
||||
```
|
||||
|
||||
### Generate Social Media Post
|
||||
|
||||
```bash
|
||||
npx -y bun ${SKILL_DIR}/scripts/main.ts \
|
||||
--prompt "Instagram post about coffee" \
|
||||
--image post.png --ar 1:1
|
||||
```
|
||||
|
||||
### Edit Image with Reference
|
||||
|
||||
```bash
|
||||
npx -y bun ${SKILL_DIR}/scripts/main.ts \
|
||||
--prompt "Change the background to sunset" \
|
||||
--image edited.png --ref original.png --provider google
|
||||
```
|
||||
|
||||
### Batch Generation from Prompt File
|
||||
|
||||
```bash
|
||||
# Create prompt file with detailed instructions
|
||||
npx -y bun ${SKILL_DIR}/scripts/main.ts \
|
||||
--promptfiles style-guide.md scene-description.md \
|
||||
--image scene.png
|
||||
```
|
||||
|
||||
## Error Handling
|
||||
|
||||
- **Missing API key**: Clear error with setup instructions
|
||||
- **Generation failure**: Auto-retry once, then error
|
||||
- **Invalid aspect ratio**: Warning, proceed with default
|
||||
- **Reference images with image-only model**: Warning, ignore refs
|
||||
|
||||
## Extension Support
|
||||
|
||||
Custom configurations via EXTEND.md.
|
||||
|
||||
**Check paths** (priority order):
|
||||
1. `.baoyu-skills/baoyu-image-gen/EXTEND.md` (project)
|
||||
2. `~/.baoyu-skills/baoyu-image-gen/EXTEND.md` (user)
|
||||
|
||||
If found, load before workflow. Extension content overrides defaults.
|
||||
@@ -0,0 +1,576 @@
|
||||
import fs from "node:fs";
|
||||
import path from "node:path";
|
||||
import process from "node:process";
|
||||
import { homedir } from "node:os";
|
||||
import { mkdir, readFile, writeFile } from "node:fs/promises";
|
||||
|
||||
type Provider = "google" | "openai";
|
||||
type Quality = "normal" | "2k";
|
||||
|
||||
type CliArgs = {
|
||||
prompt: string | null;
|
||||
promptFiles: string[];
|
||||
imagePath: string | null;
|
||||
provider: Provider | null;
|
||||
model: string | null;
|
||||
aspectRatio: string | null;
|
||||
size: string | null;
|
||||
quality: Quality;
|
||||
referenceImages: string[];
|
||||
n: number;
|
||||
json: boolean;
|
||||
help: boolean;
|
||||
};
|
||||
|
||||
const GOOGLE_MULTIMODAL_MODELS = [
|
||||
"gemini-3-pro-image-preview",
|
||||
"gemini-2.0-flash-exp-image-generation",
|
||||
"gemini-2.5-flash-preview-native-audio-dialog",
|
||||
];
|
||||
|
||||
const GOOGLE_IMAGEN_MODELS = ["imagen-3.0-generate-002", "imagen-3.0-generate-001"];
|
||||
|
||||
const OPENAI_IMAGE_MODELS = ["gpt-image-1.5", "gpt-image-1", "dall-e-3", "dall-e-2"];
|
||||
|
||||
function printUsage(): void {
|
||||
console.log(`Usage:
|
||||
npx -y bun scripts/main.ts --prompt "A cat" --image cat.png
|
||||
npx -y bun scripts/main.ts --prompt "A landscape" --image landscape.png --ar 16:9
|
||||
npx -y bun scripts/main.ts --promptfiles system.md content.md --image out.png
|
||||
|
||||
Options:
|
||||
-p, --prompt <text> Prompt text
|
||||
--promptfiles <files...> Read prompt from files (concatenated)
|
||||
--image <path> Output image path (required)
|
||||
--provider google|openai Force provider (auto-detect by default)
|
||||
-m, --model <id> Model ID
|
||||
--ar <ratio> Aspect ratio (e.g., 16:9, 1:1, 4:3)
|
||||
--size <WxH> Size (e.g., 1024x1024)
|
||||
--quality normal|2k Quality preset (default: normal)
|
||||
--ref <files...> Reference images (Google multimodal only)
|
||||
--n <count> Number of images (default: 1)
|
||||
--json JSON output
|
||||
-h, --help Show help
|
||||
|
||||
Environment variables:
|
||||
OPENAI_API_KEY OpenAI API key
|
||||
GOOGLE_API_KEY Google API key
|
||||
OPENAI_IMAGE_MODEL Default OpenAI model (gpt-image-1.5)
|
||||
GOOGLE_IMAGE_MODEL Default Google model (gemini-3-pro-image-preview)
|
||||
OPENAI_BASE_URL Custom OpenAI endpoint
|
||||
GOOGLE_BASE_URL Custom Google endpoint
|
||||
|
||||
Env file load order: CLI args > process.env > <cwd>/.baoyu-skills/.env > ~/.baoyu-skills/.env`);
|
||||
}
|
||||
|
||||
function parseArgs(argv: string[]): CliArgs {
|
||||
const out: CliArgs = {
|
||||
prompt: null,
|
||||
promptFiles: [],
|
||||
imagePath: null,
|
||||
provider: null,
|
||||
model: null,
|
||||
aspectRatio: null,
|
||||
size: null,
|
||||
quality: "normal",
|
||||
referenceImages: [],
|
||||
n: 1,
|
||||
json: false,
|
||||
help: false,
|
||||
};
|
||||
|
||||
const positional: string[] = [];
|
||||
|
||||
const takeMany = (i: number): { items: string[]; next: number } => {
|
||||
const items: string[] = [];
|
||||
let j = i + 1;
|
||||
while (j < argv.length) {
|
||||
const v = argv[j]!;
|
||||
if (v.startsWith("-")) break;
|
||||
items.push(v);
|
||||
j++;
|
||||
}
|
||||
return { items, next: j - 1 };
|
||||
};
|
||||
|
||||
for (let i = 0; i < argv.length; i++) {
|
||||
const a = argv[i]!;
|
||||
|
||||
if (a === "--help" || a === "-h") {
|
||||
out.help = true;
|
||||
continue;
|
||||
}
|
||||
|
||||
if (a === "--json") {
|
||||
out.json = true;
|
||||
continue;
|
||||
}
|
||||
|
||||
if (a === "--prompt" || a === "-p") {
|
||||
const v = argv[++i];
|
||||
if (!v) throw new Error(`Missing value for ${a}`);
|
||||
out.prompt = v;
|
||||
continue;
|
||||
}
|
||||
|
||||
if (a === "--promptfiles") {
|
||||
const { items, next } = takeMany(i);
|
||||
if (items.length === 0) throw new Error("Missing files for --promptfiles");
|
||||
out.promptFiles.push(...items);
|
||||
i = next;
|
||||
continue;
|
||||
}
|
||||
|
||||
if (a === "--image") {
|
||||
const v = argv[++i];
|
||||
if (!v) throw new Error("Missing value for --image");
|
||||
out.imagePath = v;
|
||||
continue;
|
||||
}
|
||||
|
||||
if (a === "--provider") {
|
||||
const v = argv[++i];
|
||||
if (v !== "google" && v !== "openai") throw new Error(`Invalid provider: ${v}`);
|
||||
out.provider = v;
|
||||
continue;
|
||||
}
|
||||
|
||||
if (a === "--model" || a === "-m") {
|
||||
const v = argv[++i];
|
||||
if (!v) throw new Error(`Missing value for ${a}`);
|
||||
out.model = v;
|
||||
continue;
|
||||
}
|
||||
|
||||
if (a === "--ar") {
|
||||
const v = argv[++i];
|
||||
if (!v) throw new Error("Missing value for --ar");
|
||||
out.aspectRatio = v;
|
||||
continue;
|
||||
}
|
||||
|
||||
if (a === "--size") {
|
||||
const v = argv[++i];
|
||||
if (!v) throw new Error("Missing value for --size");
|
||||
out.size = v;
|
||||
continue;
|
||||
}
|
||||
|
||||
if (a === "--quality") {
|
||||
const v = argv[++i];
|
||||
if (v !== "normal" && v !== "2k") throw new Error(`Invalid quality: ${v}`);
|
||||
out.quality = v;
|
||||
continue;
|
||||
}
|
||||
|
||||
if (a === "--ref" || a === "--reference") {
|
||||
const { items, next } = takeMany(i);
|
||||
if (items.length === 0) throw new Error(`Missing files for ${a}`);
|
||||
out.referenceImages.push(...items);
|
||||
i = next;
|
||||
continue;
|
||||
}
|
||||
|
||||
if (a === "--n") {
|
||||
const v = argv[++i];
|
||||
if (!v) throw new Error("Missing value for --n");
|
||||
out.n = parseInt(v, 10);
|
||||
if (isNaN(out.n) || out.n < 1) throw new Error(`Invalid count: ${v}`);
|
||||
continue;
|
||||
}
|
||||
|
||||
if (a.startsWith("-")) {
|
||||
throw new Error(`Unknown option: ${a}`);
|
||||
}
|
||||
|
||||
positional.push(a);
|
||||
}
|
||||
|
||||
if (!out.prompt && out.promptFiles.length === 0 && positional.length > 0) {
|
||||
out.prompt = positional.join(" ");
|
||||
}
|
||||
|
||||
return out;
|
||||
}
|
||||
|
||||
async function loadEnvFile(p: string): Promise<Record<string, string>> {
|
||||
try {
|
||||
const content = await readFile(p, "utf8");
|
||||
const env: Record<string, string> = {};
|
||||
for (const line of content.split("\n")) {
|
||||
const trimmed = line.trim();
|
||||
if (!trimmed || trimmed.startsWith("#")) continue;
|
||||
const idx = trimmed.indexOf("=");
|
||||
if (idx === -1) continue;
|
||||
const key = trimmed.slice(0, idx).trim();
|
||||
let val = trimmed.slice(idx + 1).trim();
|
||||
if ((val.startsWith('"') && val.endsWith('"')) || (val.startsWith("'") && val.endsWith("'"))) {
|
||||
val = val.slice(1, -1);
|
||||
}
|
||||
env[key] = val;
|
||||
}
|
||||
return env;
|
||||
} catch {
|
||||
return {};
|
||||
}
|
||||
}
|
||||
|
||||
async function loadEnv(): Promise<void> {
|
||||
const home = homedir();
|
||||
const cwd = process.cwd();
|
||||
|
||||
const homeEnv = await loadEnvFile(path.join(home, ".baoyu-skills", ".env"));
|
||||
const cwdEnv = await loadEnvFile(path.join(cwd, ".baoyu-skills", ".env"));
|
||||
|
||||
for (const [k, v] of Object.entries(homeEnv)) {
|
||||
if (!process.env[k]) process.env[k] = v;
|
||||
}
|
||||
for (const [k, v] of Object.entries(cwdEnv)) {
|
||||
if (!process.env[k]) process.env[k] = v;
|
||||
}
|
||||
}
|
||||
|
||||
async function readPromptFromFiles(files: string[]): Promise<string> {
|
||||
const parts: string[] = [];
|
||||
for (const f of files) {
|
||||
parts.push(await readFile(f, "utf8"));
|
||||
}
|
||||
return parts.join("\n\n");
|
||||
}
|
||||
|
||||
async function readPromptFromStdin(): Promise<string | null> {
|
||||
if (process.stdin.isTTY) return null;
|
||||
try {
|
||||
const t = await Bun.stdin.text();
|
||||
const v = t.trim();
|
||||
return v.length > 0 ? v : null;
|
||||
} catch {
|
||||
return null;
|
||||
}
|
||||
}
|
||||
|
||||
function normalizeOutputImagePath(p: string): string {
|
||||
const full = path.resolve(p);
|
||||
const ext = path.extname(full);
|
||||
if (ext) return full;
|
||||
return `${full}.png`;
|
||||
}
|
||||
|
||||
function detectProvider(args: CliArgs): Provider {
|
||||
if (args.provider) return args.provider;
|
||||
|
||||
const hasGoogle = !!process.env.GOOGLE_API_KEY;
|
||||
const hasOpenai = !!process.env.OPENAI_API_KEY;
|
||||
|
||||
if (hasGoogle && !hasOpenai) return "google";
|
||||
if (hasOpenai && !hasGoogle) return "openai";
|
||||
if (hasGoogle && hasOpenai) return "google";
|
||||
|
||||
throw new Error(
|
||||
"No API key found. Set GOOGLE_API_KEY or OPENAI_API_KEY.\n" +
|
||||
"Create ~/.baoyu-skills/.env or <cwd>/.baoyu-skills/.env with your keys."
|
||||
);
|
||||
}
|
||||
|
||||
function getDefaultModel(provider: Provider): string {
|
||||
if (provider === "google") {
|
||||
return process.env.GOOGLE_IMAGE_MODEL || "gemini-3-pro-image-preview";
|
||||
}
|
||||
return process.env.OPENAI_IMAGE_MODEL || "gpt-image-1.5";
|
||||
}
|
||||
|
||||
function isGoogleMultimodal(model: string): boolean {
|
||||
return GOOGLE_MULTIMODAL_MODELS.some((m) => model.includes(m));
|
||||
}
|
||||
|
||||
function isGoogleImagen(model: string): boolean {
|
||||
return GOOGLE_IMAGEN_MODELS.some((m) => model.includes(m));
|
||||
}
|
||||
|
||||
function buildPromptWithAspect(prompt: string, ar: string | null, quality: Quality): string {
|
||||
let result = prompt;
|
||||
if (ar) {
|
||||
result += ` Aspect ratio: ${ar}.`;
|
||||
}
|
||||
if (quality === "2k") {
|
||||
result += " High resolution 2048px.";
|
||||
}
|
||||
return result;
|
||||
}
|
||||
|
||||
function parseAspectRatio(ar: string): { width: number; height: number } | null {
|
||||
const match = ar.match(/^(\d+(?:\.\d+)?):(\d+(?:\.\d+)?)$/);
|
||||
if (!match) return null;
|
||||
const w = parseFloat(match[1]!);
|
||||
const h = parseFloat(match[2]!);
|
||||
if (w <= 0 || h <= 0) return null;
|
||||
return { width: w, height: h };
|
||||
}
|
||||
|
||||
function getOpenAISize(ar: string | null, quality: Quality): string {
|
||||
const base = quality === "2k" ? 2048 : 1024;
|
||||
|
||||
if (!ar) return `${base}x${base}`;
|
||||
|
||||
const parsed = parseAspectRatio(ar);
|
||||
if (!parsed) return `${base}x${base}`;
|
||||
|
||||
const ratio = parsed.width / parsed.height;
|
||||
|
||||
if (Math.abs(ratio - 1) < 0.1) return `${base}x${base}`;
|
||||
if (ratio > 1.5) return quality === "2k" ? "2048x1024" : "1792x1024";
|
||||
if (ratio < 0.67) return quality === "2k" ? "1024x2048" : "1024x1792";
|
||||
return `${base}x${base}`;
|
||||
}
|
||||
|
||||
async function readImageAsBase64(p: string): Promise<{ data: string; mimeType: string }> {
|
||||
const buf = await readFile(p);
|
||||
const ext = path.extname(p).toLowerCase();
|
||||
let mimeType = "image/png";
|
||||
if (ext === ".jpg" || ext === ".jpeg") mimeType = "image/jpeg";
|
||||
else if (ext === ".gif") mimeType = "image/gif";
|
||||
else if (ext === ".webp") mimeType = "image/webp";
|
||||
return { data: buf.toString("base64"), mimeType };
|
||||
}
|
||||
|
||||
async function generateWithGoogleMultimodal(
|
||||
prompt: string,
|
||||
model: string,
|
||||
args: CliArgs
|
||||
): Promise<Uint8Array> {
|
||||
const { generateText } = await import("ai");
|
||||
const { createGoogleGenerativeAI } = await import("@ai-sdk/google");
|
||||
|
||||
const google = createGoogleGenerativeAI({
|
||||
apiKey: process.env.GOOGLE_API_KEY,
|
||||
baseURL: process.env.GOOGLE_BASE_URL,
|
||||
});
|
||||
|
||||
const fullPrompt = buildPromptWithAspect(prompt, args.aspectRatio, args.quality);
|
||||
|
||||
const messages: any[] = [];
|
||||
const content: any[] = [];
|
||||
|
||||
for (const refPath of args.referenceImages) {
|
||||
const { data, mimeType } = await readImageAsBase64(refPath);
|
||||
content.push({ type: "image", image: data, mimeType });
|
||||
}
|
||||
content.push({ type: "text", text: fullPrompt });
|
||||
|
||||
messages.push({ role: "user", content });
|
||||
|
||||
const result = await generateText({
|
||||
model: google(model, { useSearchGrounding: false }),
|
||||
messages,
|
||||
providerOptions: {
|
||||
google: {
|
||||
responseModalities: ["TEXT", "IMAGE"],
|
||||
},
|
||||
},
|
||||
});
|
||||
|
||||
const files = (result as any).files;
|
||||
if (!files || files.length === 0) {
|
||||
const expRes = (result as any).response?.body?.candidates?.[0]?.content?.parts;
|
||||
if (expRes) {
|
||||
for (const part of expRes) {
|
||||
if (part.inlineData?.data) {
|
||||
return Uint8Array.from(Buffer.from(part.inlineData.data, "base64"));
|
||||
}
|
||||
}
|
||||
}
|
||||
throw new Error("No image in response");
|
||||
}
|
||||
|
||||
const img = files[0];
|
||||
if (img.uint8Array) return img.uint8Array;
|
||||
if (img.base64) return Uint8Array.from(Buffer.from(img.base64, "base64"));
|
||||
|
||||
throw new Error("Cannot extract image data");
|
||||
}
|
||||
|
||||
async function generateWithGoogleImagen(
|
||||
prompt: string,
|
||||
model: string,
|
||||
args: CliArgs
|
||||
): Promise<Uint8Array> {
|
||||
const { experimental_generateImage: generateImage } = await import("ai");
|
||||
const { createGoogleGenerativeAI } = await import("@ai-sdk/google");
|
||||
|
||||
const google = createGoogleGenerativeAI({
|
||||
apiKey: process.env.GOOGLE_API_KEY,
|
||||
baseURL: process.env.GOOGLE_BASE_URL,
|
||||
});
|
||||
|
||||
const fullPrompt = buildPromptWithAspect(prompt, args.aspectRatio, args.quality);
|
||||
|
||||
const result = await generateImage({
|
||||
model: google.image(model),
|
||||
prompt: fullPrompt,
|
||||
n: args.n,
|
||||
aspectRatio: args.aspectRatio || undefined,
|
||||
});
|
||||
|
||||
const img = result.images[0];
|
||||
if (!img) throw new Error("No image in response");
|
||||
|
||||
if (img.uint8Array) return img.uint8Array;
|
||||
if (img.base64) return Uint8Array.from(Buffer.from(img.base64, "base64"));
|
||||
|
||||
throw new Error("Cannot extract image data");
|
||||
}
|
||||
|
||||
async function generateWithOpenAI(
|
||||
prompt: string,
|
||||
model: string,
|
||||
args: CliArgs
|
||||
): Promise<Uint8Array> {
|
||||
const baseURL = process.env.OPENAI_BASE_URL || "https://api.openai.com/v1";
|
||||
const apiKey = process.env.OPENAI_API_KEY;
|
||||
|
||||
if (!apiKey) throw new Error("OPENAI_API_KEY is required");
|
||||
|
||||
const size = args.size || getOpenAISize(args.aspectRatio, args.quality);
|
||||
|
||||
const body: Record<string, any> = {
|
||||
model,
|
||||
prompt,
|
||||
size,
|
||||
};
|
||||
|
||||
if (model.includes("dall-e-3")) {
|
||||
body.quality = args.quality === "2k" ? "hd" : "standard";
|
||||
}
|
||||
|
||||
const res = await fetch(`${baseURL}/images/generations`, {
|
||||
method: "POST",
|
||||
headers: {
|
||||
"Content-Type": "application/json",
|
||||
Authorization: `Bearer ${apiKey}`,
|
||||
},
|
||||
body: JSON.stringify(body),
|
||||
});
|
||||
|
||||
if (!res.ok) {
|
||||
const err = await res.text();
|
||||
throw new Error(`OpenAI API error: ${err}`);
|
||||
}
|
||||
|
||||
const result = (await res.json()) as { data: Array<{ url?: string; b64_json?: string }> };
|
||||
const img = result.data[0];
|
||||
|
||||
if (img?.b64_json) {
|
||||
return Uint8Array.from(Buffer.from(img.b64_json, "base64"));
|
||||
}
|
||||
|
||||
if (img?.url) {
|
||||
const imgRes = await fetch(img.url);
|
||||
if (!imgRes.ok) throw new Error("Failed to download image");
|
||||
const buf = await imgRes.arrayBuffer();
|
||||
return new Uint8Array(buf);
|
||||
}
|
||||
|
||||
throw new Error("No image in response");
|
||||
}
|
||||
|
||||
async function generate(
|
||||
provider: Provider,
|
||||
model: string,
|
||||
prompt: string,
|
||||
args: CliArgs
|
||||
): Promise<Uint8Array> {
|
||||
if (provider === "google") {
|
||||
if (isGoogleMultimodal(model)) {
|
||||
return generateWithGoogleMultimodal(prompt, model, args);
|
||||
}
|
||||
if (isGoogleImagen(model)) {
|
||||
if (args.referenceImages.length > 0) {
|
||||
console.error("Warning: Reference images not supported with Imagen models, ignoring.");
|
||||
}
|
||||
return generateWithGoogleImagen(prompt, model, args);
|
||||
}
|
||||
return generateWithGoogleMultimodal(prompt, model, args);
|
||||
}
|
||||
|
||||
if (args.referenceImages.length > 0) {
|
||||
console.error("Warning: Reference images not supported with OpenAI, ignoring.");
|
||||
}
|
||||
return generateWithOpenAI(prompt, model, args);
|
||||
}
|
||||
|
||||
async function main(): Promise<void> {
|
||||
const args = parseArgs(process.argv.slice(2));
|
||||
|
||||
if (args.help) {
|
||||
printUsage();
|
||||
return;
|
||||
}
|
||||
|
||||
await loadEnv();
|
||||
|
||||
let prompt: string | null = args.prompt;
|
||||
if (!prompt && args.promptFiles.length > 0) prompt = await readPromptFromFiles(args.promptFiles);
|
||||
if (!prompt) prompt = await readPromptFromStdin();
|
||||
|
||||
if (!prompt) {
|
||||
console.error("Error: Prompt is required");
|
||||
printUsage();
|
||||
process.exitCode = 1;
|
||||
return;
|
||||
}
|
||||
|
||||
if (!args.imagePath) {
|
||||
console.error("Error: --image is required");
|
||||
printUsage();
|
||||
process.exitCode = 1;
|
||||
return;
|
||||
}
|
||||
|
||||
const provider = detectProvider(args);
|
||||
const model = args.model || getDefaultModel(provider);
|
||||
const outputPath = normalizeOutputImagePath(args.imagePath);
|
||||
|
||||
let imageData: Uint8Array;
|
||||
let retried = false;
|
||||
|
||||
while (true) {
|
||||
try {
|
||||
imageData = await generate(provider, model, prompt, args);
|
||||
break;
|
||||
} catch (e) {
|
||||
if (!retried) {
|
||||
retried = true;
|
||||
console.error("Generation failed, retrying...");
|
||||
continue;
|
||||
}
|
||||
throw e;
|
||||
}
|
||||
}
|
||||
|
||||
const dir = path.dirname(outputPath);
|
||||
await mkdir(dir, { recursive: true });
|
||||
await writeFile(outputPath, imageData);
|
||||
|
||||
if (args.json) {
|
||||
console.log(
|
||||
JSON.stringify(
|
||||
{
|
||||
savedImage: outputPath,
|
||||
provider,
|
||||
model,
|
||||
prompt: prompt.slice(0, 200),
|
||||
},
|
||||
null,
|
||||
2
|
||||
)
|
||||
);
|
||||
} else {
|
||||
console.log(outputPath);
|
||||
}
|
||||
}
|
||||
|
||||
main().catch((e) => {
|
||||
const msg = e instanceof Error ? e.message : String(e);
|
||||
console.error(msg);
|
||||
process.exit(1);
|
||||
});
|
||||
@@ -1,11 +1,11 @@
|
||||
---
|
||||
name: baoyu-post-to-x
|
||||
description: Post content and articles to X (Twitter). Supports regular posts with images and X Articles (long-form Markdown). Uses real Chrome with CDP to bypass anti-automation.
|
||||
description: Post content and articles to X (Twitter). Supports regular posts with images/videos and X Articles (long-form Markdown). Uses real Chrome with CDP to bypass anti-automation.
|
||||
---
|
||||
|
||||
# Post to X (Twitter)
|
||||
|
||||
Post content, images, and long-form articles to X using real Chrome browser (bypasses anti-bot detection).
|
||||
Post content, images, videos, and long-form articles to X using real Chrome browser (bypasses anti-bot detection).
|
||||
|
||||
## Script Directory
|
||||
|
||||
@@ -20,6 +20,7 @@ Post content, images, and long-form articles to X using real Chrome browser (byp
|
||||
| Script | Purpose |
|
||||
|--------|---------|
|
||||
| `scripts/x-browser.ts` | Regular posts (text + images) |
|
||||
| `scripts/x-video.ts` | Video posts (text + video) |
|
||||
| `scripts/x-article.ts` | Long-form article publishing (Markdown) |
|
||||
| `scripts/md-to-html.ts` | Markdown → HTML conversion |
|
||||
| `scripts/copy-to-clipboard.ts` | Copy content to clipboard |
|
||||
@@ -62,6 +63,34 @@ npx -y bun ${SKILL_DIR}/scripts/x-browser.ts "Hello!" --image ./photo.png --subm
|
||||
|
||||
---
|
||||
|
||||
## Video Posts
|
||||
|
||||
Text + video file (MP4, MOV, WebM).
|
||||
|
||||
```bash
|
||||
# Preview mode (doesn't post)
|
||||
npx -y bun ${SKILL_DIR}/scripts/x-video.ts "Check out this video!" --video ./clip.mp4
|
||||
|
||||
# Actually post
|
||||
npx -y bun ${SKILL_DIR}/scripts/x-video.ts "Amazing content" --video ./demo.mp4 --submit
|
||||
```
|
||||
|
||||
**Parameters**:
|
||||
| Parameter | Description |
|
||||
|-----------|-------------|
|
||||
| `<text>` | Post content (positional argument) |
|
||||
| `--video <path>` | Video file path (required) |
|
||||
| `--submit` | Actually post (default: preview only) |
|
||||
| `--profile <dir>` | Custom Chrome profile directory |
|
||||
|
||||
**Video Limits**:
|
||||
- Regular accounts: 140 seconds max
|
||||
- X Premium: up to 60 minutes
|
||||
- Supported formats: MP4, MOV, WebM
|
||||
- Processing time: 30-60 seconds depending on file size
|
||||
|
||||
---
|
||||
|
||||
## X Articles
|
||||
|
||||
Long-form Markdown articles (requires X Premium).
|
||||
|
||||
@@ -0,0 +1,407 @@
|
||||
import { spawn } from 'node:child_process';
|
||||
import fs from 'node:fs';
|
||||
import { mkdir } from 'node:fs/promises';
|
||||
import net from 'node:net';
|
||||
import os from 'node:os';
|
||||
import path from 'node:path';
|
||||
import process from 'node:process';
|
||||
|
||||
const X_COMPOSE_URL = 'https://x.com/compose/post';
|
||||
|
||||
function sleep(ms: number): Promise<void> {
|
||||
return new Promise((resolve) => setTimeout(resolve, ms));
|
||||
}
|
||||
|
||||
async function getFreePort(): Promise<number> {
|
||||
return new Promise((resolve, reject) => {
|
||||
const server = net.createServer();
|
||||
server.unref();
|
||||
server.on('error', reject);
|
||||
server.listen(0, '127.0.0.1', () => {
|
||||
const address = server.address();
|
||||
if (!address || typeof address === 'string') {
|
||||
server.close(() => reject(new Error('Unable to allocate a free TCP port.')));
|
||||
return;
|
||||
}
|
||||
const port = address.port;
|
||||
server.close((err) => {
|
||||
if (err) reject(err);
|
||||
else resolve(port);
|
||||
});
|
||||
});
|
||||
});
|
||||
}
|
||||
|
||||
function findChromeExecutable(): string | undefined {
|
||||
const override = process.env.X_BROWSER_CHROME_PATH?.trim();
|
||||
if (override && fs.existsSync(override)) return override;
|
||||
|
||||
const candidates: string[] = [];
|
||||
switch (process.platform) {
|
||||
case 'darwin':
|
||||
candidates.push(
|
||||
'/Applications/Google Chrome.app/Contents/MacOS/Google Chrome',
|
||||
'/Applications/Google Chrome Canary.app/Contents/MacOS/Google Chrome Canary',
|
||||
'/Applications/Google Chrome Beta.app/Contents/MacOS/Google Chrome Beta',
|
||||
'/Applications/Chromium.app/Contents/MacOS/Chromium',
|
||||
'/Applications/Microsoft Edge.app/Contents/MacOS/Microsoft Edge',
|
||||
);
|
||||
break;
|
||||
case 'win32':
|
||||
candidates.push(
|
||||
'C:\\Program Files\\Google\\Chrome\\Application\\chrome.exe',
|
||||
'C:\\Program Files (x86)\\Google\\Chrome\\Application\\chrome.exe',
|
||||
'C:\\Program Files\\Microsoft\\Edge\\Application\\msedge.exe',
|
||||
'C:\\Program Files (x86)\\Microsoft\\Edge\\Application\\msedge.exe',
|
||||
);
|
||||
break;
|
||||
default:
|
||||
candidates.push(
|
||||
'/usr/bin/google-chrome',
|
||||
'/usr/bin/google-chrome-stable',
|
||||
'/usr/bin/chromium',
|
||||
'/usr/bin/chromium-browser',
|
||||
'/snap/bin/chromium',
|
||||
'/usr/bin/microsoft-edge',
|
||||
);
|
||||
break;
|
||||
}
|
||||
|
||||
for (const p of candidates) {
|
||||
if (fs.existsSync(p)) return p;
|
||||
}
|
||||
return undefined;
|
||||
}
|
||||
|
||||
function getDefaultProfileDir(): string {
|
||||
const base = process.env.XDG_DATA_HOME || path.join(os.homedir(), '.local', 'share');
|
||||
return path.join(base, 'x-browser-profile');
|
||||
}
|
||||
|
||||
async function fetchJson<T = unknown>(url: string): Promise<T> {
|
||||
const res = await fetch(url, { redirect: 'follow' });
|
||||
if (!res.ok) throw new Error(`Request failed: ${res.status} ${res.statusText}`);
|
||||
return (await res.json()) as T;
|
||||
}
|
||||
|
||||
async function waitForChromeDebugPort(port: number, timeoutMs: number): Promise<string> {
|
||||
const start = Date.now();
|
||||
let lastError: unknown = null;
|
||||
|
||||
while (Date.now() - start < timeoutMs) {
|
||||
try {
|
||||
const version = await fetchJson<{ webSocketDebuggerUrl?: string }>(`http://127.0.0.1:${port}/json/version`);
|
||||
if (version.webSocketDebuggerUrl) return version.webSocketDebuggerUrl;
|
||||
lastError = new Error('Missing webSocketDebuggerUrl');
|
||||
} catch (error) {
|
||||
lastError = error;
|
||||
}
|
||||
await sleep(200);
|
||||
}
|
||||
|
||||
throw new Error(`Chrome debug port not ready: ${lastError instanceof Error ? lastError.message : String(lastError)}`);
|
||||
}
|
||||
|
||||
class CdpConnection {
|
||||
private ws: WebSocket;
|
||||
private nextId = 0;
|
||||
private pending = new Map<number, { resolve: (v: unknown) => void; reject: (e: Error) => void; timer: ReturnType<typeof setTimeout> | null }>();
|
||||
|
||||
private constructor(ws: WebSocket) {
|
||||
this.ws = ws;
|
||||
this.ws.addEventListener('message', (event) => {
|
||||
try {
|
||||
const data = typeof event.data === 'string' ? event.data : new TextDecoder().decode(event.data as ArrayBuffer);
|
||||
const msg = JSON.parse(data) as { id?: number; result?: unknown; error?: { message?: string } };
|
||||
|
||||
if (msg.id) {
|
||||
const pending = this.pending.get(msg.id);
|
||||
if (pending) {
|
||||
this.pending.delete(msg.id);
|
||||
if (pending.timer) clearTimeout(pending.timer);
|
||||
if (msg.error?.message) pending.reject(new Error(msg.error.message));
|
||||
else pending.resolve(msg.result);
|
||||
}
|
||||
}
|
||||
} catch {}
|
||||
});
|
||||
|
||||
this.ws.addEventListener('close', () => {
|
||||
for (const [id, pending] of this.pending.entries()) {
|
||||
this.pending.delete(id);
|
||||
if (pending.timer) clearTimeout(pending.timer);
|
||||
pending.reject(new Error('CDP connection closed.'));
|
||||
}
|
||||
});
|
||||
}
|
||||
|
||||
static async connect(url: string, timeoutMs: number): Promise<CdpConnection> {
|
||||
const ws = new WebSocket(url);
|
||||
await new Promise<void>((resolve, reject) => {
|
||||
const timer = setTimeout(() => reject(new Error('CDP connection timeout.')), timeoutMs);
|
||||
ws.addEventListener('open', () => { clearTimeout(timer); resolve(); });
|
||||
ws.addEventListener('error', () => { clearTimeout(timer); reject(new Error('CDP connection failed.')); });
|
||||
});
|
||||
return new CdpConnection(ws);
|
||||
}
|
||||
|
||||
async send<T = unknown>(method: string, params?: Record<string, unknown>, options?: { sessionId?: string; timeoutMs?: number }): Promise<T> {
|
||||
const id = ++this.nextId;
|
||||
const message: Record<string, unknown> = { id, method };
|
||||
if (params) message.params = params;
|
||||
if (options?.sessionId) message.sessionId = options.sessionId;
|
||||
|
||||
const timeoutMs = options?.timeoutMs ?? 30_000;
|
||||
|
||||
const result = await new Promise<unknown>((resolve, reject) => {
|
||||
const timer = timeoutMs > 0 ? setTimeout(() => { this.pending.delete(id); reject(new Error(`CDP timeout: ${method}`)); }, timeoutMs) : null;
|
||||
this.pending.set(id, { resolve, reject, timer });
|
||||
this.ws.send(JSON.stringify(message));
|
||||
});
|
||||
|
||||
return result as T;
|
||||
}
|
||||
|
||||
close(): void {
|
||||
try { this.ws.close(); } catch {}
|
||||
}
|
||||
}
|
||||
|
||||
interface XVideoOptions {
|
||||
text?: string;
|
||||
videoPath: string;
|
||||
submit?: boolean;
|
||||
timeoutMs?: number;
|
||||
profileDir?: string;
|
||||
chromePath?: string;
|
||||
}
|
||||
|
||||
export async function postVideoToX(options: XVideoOptions): Promise<void> {
|
||||
const { text, videoPath, submit = false, timeoutMs = 120_000, profileDir = getDefaultProfileDir() } = options;
|
||||
|
||||
const chromePath = options.chromePath ?? findChromeExecutable();
|
||||
if (!chromePath) throw new Error('Chrome not found. Set X_BROWSER_CHROME_PATH env var.');
|
||||
|
||||
if (!fs.existsSync(videoPath)) throw new Error(`Video not found: ${videoPath}`);
|
||||
|
||||
const absVideoPath = path.resolve(videoPath);
|
||||
console.log(`[x-video] Video: ${absVideoPath}`);
|
||||
|
||||
await mkdir(profileDir, { recursive: true });
|
||||
|
||||
const port = await getFreePort();
|
||||
console.log(`[x-video] Launching Chrome (profile: ${profileDir})`);
|
||||
|
||||
const chrome = spawn(chromePath, [
|
||||
`--remote-debugging-port=${port}`,
|
||||
`--user-data-dir=${profileDir}`,
|
||||
'--no-first-run',
|
||||
'--no-default-browser-check',
|
||||
'--disable-blink-features=AutomationControlled',
|
||||
'--start-maximized',
|
||||
X_COMPOSE_URL,
|
||||
], { stdio: 'ignore' });
|
||||
|
||||
let cdp: CdpConnection | null = null;
|
||||
|
||||
try {
|
||||
const wsUrl = await waitForChromeDebugPort(port, 30_000);
|
||||
cdp = await CdpConnection.connect(wsUrl, 30_000);
|
||||
|
||||
const targets = await cdp.send<{ targetInfos: Array<{ targetId: string; url: string; type: string }> }>('Target.getTargets');
|
||||
let pageTarget = targets.targetInfos.find((t) => t.type === 'page' && t.url.includes('x.com'));
|
||||
|
||||
if (!pageTarget) {
|
||||
const { targetId } = await cdp.send<{ targetId: string }>('Target.createTarget', { url: X_COMPOSE_URL });
|
||||
pageTarget = { targetId, url: X_COMPOSE_URL, type: 'page' };
|
||||
}
|
||||
|
||||
const { sessionId } = await cdp.send<{ sessionId: string }>('Target.attachToTarget', { targetId: pageTarget.targetId, flatten: true });
|
||||
|
||||
await cdp.send('Page.enable', {}, { sessionId });
|
||||
await cdp.send('Runtime.enable', {}, { sessionId });
|
||||
await cdp.send('DOM.enable', {}, { sessionId });
|
||||
await cdp.send('Input.setIgnoreInputEvents', { ignore: false }, { sessionId });
|
||||
|
||||
console.log('[x-video] Waiting for X editor...');
|
||||
await sleep(3000);
|
||||
|
||||
const waitForEditor = async (): Promise<boolean> => {
|
||||
const start = Date.now();
|
||||
while (Date.now() - start < timeoutMs) {
|
||||
const result = await cdp!.send<{ result: { value: boolean } }>('Runtime.evaluate', {
|
||||
expression: `!!document.querySelector('[data-testid="tweetTextarea_0"]')`,
|
||||
returnByValue: true,
|
||||
}, { sessionId });
|
||||
if (result.result.value) return true;
|
||||
await sleep(1000);
|
||||
}
|
||||
return false;
|
||||
};
|
||||
|
||||
const editorFound = await waitForEditor();
|
||||
if (!editorFound) {
|
||||
console.log('[x-video] Editor not found. Please log in to X in the browser window.');
|
||||
console.log('[x-video] Waiting for login...');
|
||||
const loggedIn = await waitForEditor();
|
||||
if (!loggedIn) throw new Error('Timed out waiting for X editor. Please log in first.');
|
||||
}
|
||||
|
||||
// Upload video FIRST (before typing text to avoid text being cleared)
|
||||
console.log('[x-video] Uploading video...');
|
||||
|
||||
const { root } = await cdp.send<{ root: { nodeId: number } }>('DOM.getDocument', {}, { sessionId });
|
||||
const { nodeId } = await cdp.send<{ nodeId: number }>('DOM.querySelector', {
|
||||
nodeId: root.nodeId,
|
||||
selector: 'input[type="file"][accept*="video"], input[data-testid="fileInput"], input[type="file"]',
|
||||
}, { sessionId });
|
||||
|
||||
if (!nodeId || nodeId === 0) {
|
||||
throw new Error('Could not find file input for video upload.');
|
||||
}
|
||||
|
||||
await cdp.send('DOM.setFileInputFiles', {
|
||||
nodeId,
|
||||
files: [absVideoPath],
|
||||
}, { sessionId });
|
||||
console.log('[x-video] Video file set, waiting for processing...');
|
||||
|
||||
// Wait for video to process
|
||||
const waitForVideoReady = async (maxWaitMs = 180_000): Promise<boolean> => {
|
||||
const start = Date.now();
|
||||
let dots = 0;
|
||||
while (Date.now() - start < maxWaitMs) {
|
||||
const result = await cdp!.send<{ result: { value: { hasMedia: boolean; isProcessing: boolean } } }>('Runtime.evaluate', {
|
||||
expression: `(() => {
|
||||
const hasMedia = !!document.querySelector('[data-testid="attachments"] video, [data-testid="videoPlayer"], video');
|
||||
const isProcessing = !!document.querySelector('[role="progressbar"], [data-testid="progressBar"]');
|
||||
return { hasMedia, isProcessing };
|
||||
})()`,
|
||||
returnByValue: true,
|
||||
}, { sessionId });
|
||||
|
||||
const { hasMedia, isProcessing } = result.result.value;
|
||||
if (hasMedia && !isProcessing) {
|
||||
console.log('');
|
||||
return true;
|
||||
}
|
||||
|
||||
process.stdout.write('.');
|
||||
dots++;
|
||||
if (dots % 60 === 0) console.log(''); // New line every 60 dots
|
||||
await sleep(2000);
|
||||
}
|
||||
console.log('');
|
||||
return false;
|
||||
};
|
||||
|
||||
const videoReady = await waitForVideoReady();
|
||||
if (videoReady) {
|
||||
console.log('[x-video] Video ready!');
|
||||
} else {
|
||||
console.log('[x-video] Video may still be processing. Please check browser window.');
|
||||
}
|
||||
|
||||
// Type text AFTER video is uploaded
|
||||
if (text) {
|
||||
console.log('[x-video] Typing text...');
|
||||
await cdp.send('Runtime.evaluate', {
|
||||
expression: `
|
||||
const editor = document.querySelector('[data-testid="tweetTextarea_0"]');
|
||||
if (editor) {
|
||||
editor.focus();
|
||||
document.execCommand('insertText', false, ${JSON.stringify(text)});
|
||||
}
|
||||
`,
|
||||
}, { sessionId });
|
||||
await sleep(500);
|
||||
}
|
||||
|
||||
if (submit) {
|
||||
console.log('[x-video] Submitting post...');
|
||||
await cdp.send('Runtime.evaluate', {
|
||||
expression: `document.querySelector('[data-testid="tweetButton"]')?.click()`,
|
||||
}, { sessionId });
|
||||
await sleep(5000);
|
||||
console.log('[x-video] Post submitted!');
|
||||
} else {
|
||||
console.log('[x-video] Post composed (preview mode). Add --submit to post.');
|
||||
console.log('[x-video] Browser stays open for review.');
|
||||
}
|
||||
} finally {
|
||||
if (cdp) {
|
||||
cdp.close();
|
||||
}
|
||||
// Don't kill Chrome in preview mode, let user review
|
||||
if (submit) {
|
||||
setTimeout(() => {
|
||||
if (!chrome.killed) try { chrome.kill('SIGKILL'); } catch {}
|
||||
}, 2_000).unref?.();
|
||||
try { chrome.kill('SIGTERM'); } catch {}
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
function printUsage(): never {
|
||||
console.log(`Post video to X (Twitter) using real Chrome browser
|
||||
|
||||
Usage:
|
||||
npx -y bun x-video.ts [options] --video <path> [text]
|
||||
|
||||
Options:
|
||||
--video <path> Video file path (required, supports mp4/mov/webm)
|
||||
--submit Actually post (default: preview only)
|
||||
--profile <dir> Chrome profile directory
|
||||
--help Show this help
|
||||
|
||||
Examples:
|
||||
npx -y bun x-video.ts --video ./clip.mp4 "Check out this video!"
|
||||
npx -y bun x-video.ts --video ./demo.mp4 --submit
|
||||
npx -y bun x-video.ts --video ./video.mp4 "Multi-line text
|
||||
works too"
|
||||
|
||||
Notes:
|
||||
- Video is uploaded first, then text is added (to avoid text being cleared)
|
||||
- Video processing may take 30-60 seconds depending on file size
|
||||
- Maximum video length on X: 140 seconds (regular) or 60 min (Premium)
|
||||
- Supported formats: MP4, MOV, WebM
|
||||
`);
|
||||
process.exit(0);
|
||||
}
|
||||
|
||||
async function main(): Promise<void> {
|
||||
const args = process.argv.slice(2);
|
||||
if (args.includes('--help') || args.includes('-h')) printUsage();
|
||||
|
||||
let videoPath: string | undefined;
|
||||
let submit = false;
|
||||
let profileDir: string | undefined;
|
||||
const textParts: string[] = [];
|
||||
|
||||
for (let i = 0; i < args.length; i++) {
|
||||
const arg = args[i]!;
|
||||
if (arg === '--video' && args[i + 1]) {
|
||||
videoPath = args[++i]!;
|
||||
} else if (arg === '--submit') {
|
||||
submit = true;
|
||||
} else if (arg === '--profile' && args[i + 1]) {
|
||||
profileDir = args[++i];
|
||||
} else if (!arg.startsWith('-')) {
|
||||
textParts.push(arg);
|
||||
}
|
||||
}
|
||||
|
||||
const text = textParts.join(' ').trim() || undefined;
|
||||
|
||||
if (!videoPath) {
|
||||
console.error('Error: --video <path> is required.');
|
||||
printUsage();
|
||||
}
|
||||
|
||||
await postVideoToX({ text, videoPath, submit, profileDir });
|
||||
}
|
||||
|
||||
await main().catch((err) => {
|
||||
console.error(`Error: ${err instanceof Error ? err.message : String(err)}`);
|
||||
process.exit(1);
|
||||
});
|
||||
@@ -87,6 +87,46 @@ Transform content into professional slide deck images with flexible style option
|
||||
| lifestyle, wellness, travel, artistic, natural | `watercolor` |
|
||||
| Default | `blueprint` |
|
||||
|
||||
## Layout Gallery
|
||||
|
||||
Optional layout hints for individual slides. Specify in outline's `// LAYOUT` section.
|
||||
|
||||
### Slide-Specific Layouts
|
||||
|
||||
| Layout | Description | Best For |
|
||||
|--------|-------------|----------|
|
||||
| `title-hero` | Large centered title + subtitle | Cover slides, section breaks |
|
||||
| `quote-callout` | Featured quote with attribution | Testimonials, key insights |
|
||||
| `key-stat` | Single large number as focal point | Impact statistics, metrics |
|
||||
| `split-screen` | Half image, half text | Feature highlights, comparisons |
|
||||
| `icon-grid` | Grid of icons with labels | Features, capabilities, benefits |
|
||||
| `two-columns` | Content in balanced columns | Paired information, dual points |
|
||||
| `three-columns` | Content in three columns | Triple comparisons, categories |
|
||||
| `image-caption` | Full-bleed image + text overlay | Visual storytelling, emotional |
|
||||
| `agenda` | Numbered list with highlights | Session overview, roadmap |
|
||||
| `bullet-list` | Structured bullet points | Simple content, lists |
|
||||
|
||||
### Infographic-Derived Layouts
|
||||
|
||||
| Layout | Description | Best For |
|
||||
|--------|-------------|----------|
|
||||
| `linear-progression` | Sequential flow left-to-right | Timelines, step-by-step |
|
||||
| `binary-comparison` | Side-by-side A vs B | Before/after, pros-cons |
|
||||
| `comparison-matrix` | Multi-factor grid | Feature comparisons |
|
||||
| `hierarchical-layers` | Pyramid or stacked levels | Priority, importance |
|
||||
| `hub-spoke` | Central node with radiating items | Concept maps, ecosystems |
|
||||
| `bento-grid` | Varied-size tiles | Overview, summary |
|
||||
| `funnel` | Narrowing stages | Conversion, filtering |
|
||||
| `dashboard` | Metrics with charts/numbers | KPIs, data display |
|
||||
| `venn-diagram` | Overlapping circles | Relationships, intersections |
|
||||
| `circular-flow` | Continuous cycle | Recurring processes |
|
||||
| `winding-roadmap` | Curved path with milestones | Journey, timeline |
|
||||
| `tree-branching` | Parent-child hierarchy | Org charts, taxonomies |
|
||||
| `iceberg` | Visible vs hidden layers | Surface vs depth |
|
||||
| `bridge` | Gap with connection | Problem-solution |
|
||||
|
||||
**Usage**: Add `Layout: <name>` in slide's `// LAYOUT` section to guide visual composition.
|
||||
|
||||
## Design Philosophy
|
||||
|
||||
This deck is designed for **reading and sharing**, not live presentation:
|
||||
@@ -169,7 +209,10 @@ If `--outline-only`, stop here.
|
||||
1. Read `references/base-prompt.md`
|
||||
2. Combine with style instructions from outline
|
||||
3. Add slide-specific content
|
||||
4. Save to `prompts/` directory
|
||||
4. If `Layout:` specified in outline, include layout guidance in prompt:
|
||||
- Reference layout characteristics for image composition
|
||||
- Example: `Layout: hub-spoke` → "Central concept in middle with related items radiating outward"
|
||||
5. Save to `prompts/` directory
|
||||
|
||||
### Step 5: Generate Images
|
||||
|
||||
|
||||
@@ -67,6 +67,7 @@ Sub-headline: [supporting tagline]
|
||||
[Detailed visual description - specific elements, composition, mood]
|
||||
|
||||
// LAYOUT
|
||||
Layout: [optional: layout name from gallery, e.g., title-hero]
|
||||
[Composition, hierarchy, spatial arrangement]
|
||||
```
|
||||
|
||||
@@ -93,6 +94,7 @@ Body:
|
||||
[Detailed visual description]
|
||||
|
||||
// LAYOUT
|
||||
Layout: [optional: layout name from gallery]
|
||||
[Composition, hierarchy, spatial arrangement]
|
||||
```
|
||||
|
||||
@@ -115,6 +117,7 @@ Body: [optional summary points or next steps]
|
||||
[Visual that reinforces the core message]
|
||||
|
||||
// LAYOUT
|
||||
Layout: [optional: layout name from gallery]
|
||||
[Clean, impactful composition]
|
||||
```
|
||||
|
||||
|
||||
Reference in New Issue
Block a user