[codex] Refactor skills into focused references (#135)

* docs: add runtime-neutral User Input Tools convention across skills

Introduce docs/user-input-tools.md as the author-side canonical source
and inline the tool-selection rule into every SKILL.md that prompts
the user. Also add Skill Self-Containment and User Input Tools sections
to CLAUDE.md and the copy-verbatim template to docs/creating-skills.md,
so skills stay portable across Claude Code, Codex, Hermes, and other
runtimes.

* feat: runtime-neutral image generation convention across skills

- Introduce inline `## Image Generation Tools` rule in every rendering SKILL.md so skills delegate backend choice instead of hard-coding one; author-side canonical copy lives in docs/image-generation-tools.md.
- Add `## Reference Images` support (`--ref`, frontmatter `references:` with direct/style/palette usage) to all seven image-rendering skills.
- Move build-batch.ts (with ref propagation into batch JSON) from baoyu-article-illustrator to baoyu-imagine so non-backend skills don't own backend-specific scripts; update baoyu-image-gen stub in sync and relax the CLAUDE.md deprecation note accordingly.

* refactor: slim heavy SKILL.md files and move detail to references/

Trim the four largest active skills and move presets, option tables, and
confirmation scripts into per-skill references/ so SKILL.md stays focused
on the decision flow.

- baoyu-slide-deck: 761→258, + styles-gallery.md, confirmation.md
- baoyu-image-cards: 657→280, + gallery.md, confirmation.md
- baoyu-post-to-wechat: 518→267, + multi-account.md, api-setup.md
- baoyu-imagine: 500→230, + providers/, usage-examples.md

Also un-deprecate baoyu-image-gen (drop stub warning) so it stays functional
alongside baoyu-imagine, and update CLAUDE.md to reflect that both
superseded skills are kept in sync rather than stubbed.

* refactor: slim four medium SKILL.md files into references/

Continue the P2 pattern on the next tier of skills — move option catalogs,
per-provider/adapter detail, and repeated EXTEND.md path boilerplate into
their own references so SKILL.md stays focused on the decision flow.

- baoyu-comic: 380→297 (art/tone/preset tables → auto-selection.md;
  Step 7 expanded detail → workflow.md)
- baoyu-infographic: 312→207 (layouts/styles/combinations/keywords →
  gallery.md; ASCII box tables → markdown tables)
- baoyu-format-markdown: 376→296 (title + summary generation →
  title-summary.md; ASCII box tables → markdown tables)
- baoyu-url-to-markdown: 334→169 (quality gate + recovery →
  quality-gate.md; adapters + media download → adapters.md)

* chore: sync deprecated skills with their replacements

Per project policy, baoyu-xhs-images and baoyu-image-gen are kept
functional alongside the active skills they were superseded by. Sync
their SKILL.md bodies and references/ to the slimmed baoyu-image-cards
and baoyu-imagine versions respectively, so cross-cutting fixes stay
consistent. Only the frontmatter (name, description, version, homepage)
differs — content is identical.

- baoyu-xhs-images: 657→281 (synced with baoyu-image-cards + new
  confirmation.md, gallery.md)
- baoyu-image-gen: 408→231 (synced with baoyu-imagine + new
  providers/, usage-examples.md)

* refactor: collapse EXTEND.md boilerplate into priority tables

Replace the dual bash/powershell existence-check blocks and ASCII box
art with a single markdown priority table across nine SKILL.md files.
The runtime-neutral phrasing removes shell-specific snippets without
losing the priority semantics.

* fix: address refactor-skills branch review findings

- image-gen: restore EXTEND.md paths to baoyu-image-gen (were pointing at
  baoyu-imagine) and mark descriptions of both deprecated skills as
  [Deprecated].
- xhs-images: sync neon/warm palettes with image-cards to add the
  "do not render color names/hex as visible text" safety sentence.
- infographic: restore Layout Gallery (21), Style Gallery (21),
  Recommended Combinations, and Keyword Shortcuts inline (previous
  refactor split them out but SKILL.md still depended on them), and add
  the missing references/config/first-time-setup.md + preferences-schema.md.
- image-cards / xhs-images / slide-deck / format-markdown: restore the
  sections that got over-slimmed into references/ (galleries, presets,
  dimensions, auto-selection, style x layout matrix, title/summary flow)
  and drop the now-empty shell files.
- docs/image-generation-tools.md: note that backend skills themselves
  (baoyu-imagine, baoyu-image-gen, baoyu-danger-gemini-web) are exempt
  from the ## Image Generation Tools section requirement.

* feat(image-gen): sync Z.AI GLM-Image provider from baoyu-imagine

Add Z.AI as a full provider in the deprecated baoyu-image-gen skill so
it stays in sync with baoyu-imagine's provider list.

- new scripts/providers/zai.ts + zai.test.ts (verbatim port; test
  factory trimmed to match image-gen's CliArgs shape).
- types.ts: "zai" added to Provider union and default_model.
- main.ts: rate-limit defaults, provider help text, env var help,
  --provider validation, loadProviderModule, detectProvider
  auto-detect chain, getModelForProvider, YAML parser allow-lists.
- references/config: Q2e Z.AI model question + zai slot in the
  preferences schema and batch.provider_limits.

Scope is intentionally limited to the Z.AI chain; unrelated drift
between image-gen and imagine (OpenAI image-API dialect,
aspectRatioSource, imageSizeSource) is left alone.

* docs: align inline-convention wording and note backend-skill exemption

- docs/user-input-tools.md: fix stale "links here" wording so it
  matches the inline convention already enforced everywhere else.
- CLAUDE.md §Image Generation Tools: inline the backend-skill
  exemption so readers don't need to cross-reference
  docs/image-generation-tools.md.
This commit is contained in:
Jim Liu 宝玉
2026-04-19 00:48:44 -05:00
committed by GitHub
parent 5b20f9a746
commit 2c800c670a
58 changed files with 3895 additions and 3269 deletions
+112 -291
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@@ -1,6 +1,6 @@
---
name: baoyu-image-gen
description: AI image generation with OpenAI, Azure OpenAI, Google, OpenRouter, DashScope, MiniMax, Jimeng, Seedream and Replicate APIs. Supports text-to-image, reference images, aspect ratios, and batch generation from saved prompt files. Sequential by default; use batch parallel generation when the user already has multiple prompts or wants stable multi-image throughput. Use when user asks to generate, create, or draw images.
description: "[Deprecated: use baoyu-imagine] AI image generation with OpenAI, Azure OpenAI, Google, OpenRouter, DashScope, Z.AI GLM-Image, MiniMax, Jimeng, Seedream and Replicate APIs. Supports text-to-image, reference images, aspect ratios, and batch generation from saved prompt files. Sequential by default; use batch parallel generation when the user already has multiple prompts or wants stable multi-image throughput. Use when user asks to generate, create, or draw images."
version: 1.56.4
metadata:
openclaw:
@@ -11,147 +11,66 @@ metadata:
- npx
---
> **⚠️ DEPRECATED**: This skill has been migrated to `baoyu-imagine`. Print a bold red warning to the user **in the user's language** (use ANSI escape `\033[1;31m`) stating that `baoyu-image-gen` has been migrated to `baoyu-imagine` and they should use `baoyu-imagine` instead. Then STOP — do NOT continue executing this skill.
# Image Generation (AI SDK)
Official API-based image generation. Supports OpenAI, Azure OpenAI, Google, OpenRouter, DashScope (阿里通义万象), MiniMax, Jimeng (即梦), Seedream (豆包) and Replicate providers.
Official API-based image generation. Supports OpenAI, Azure OpenAI, Google, OpenRouter, DashScope (阿里通义万象), Z.AI GLM-Image, MiniMax, Jimeng (即梦), Seedream (豆包) and Replicate.
## User Input Tools
When this skill prompts the user, follow this tool-selection rule (priority order):
1. **Prefer built-in user-input tools** exposed by the current agent runtime — e.g., `AskUserQuestion`, `request_user_input`, `clarify`, `ask_user`, or any equivalent.
2. **Fallback**: if no such tool exists, emit a numbered plain-text message and ask the user to reply with the chosen number/answer for each question.
3. **Batching**: if the tool supports multiple questions per call, combine all applicable questions into a single call; if only single-question, ask them one at a time in priority order.
Concrete `AskUserQuestion` references below are examples — substitute the local equivalent in other runtimes.
## Script Directory
**Agent Execution**:
1. `{baseDir}` = this SKILL.md file's directory
2. Script path = `{baseDir}/scripts/main.ts`
3. Resolve `${BUN_X}` runtime: if `bun` installed → `bun`; if `npx` available → `npx -y bun`; else suggest installing bun
`{baseDir}` = this SKILL.md's directory. Main script: `{baseDir}/scripts/main.ts`. Resolve `${BUN_X}`: prefer `bun`; else `npx -y bun`; else suggest `brew install oven-sh/bun/bun`.
## Step 0: Load Preferences ⛔ BLOCKING
**CRITICAL**: This step MUST complete BEFORE any image generation. Do NOT skip or defer.
This step MUST complete before any image generation — generation is blocked until EXTEND.md exists.
Check EXTEND.md existence (priority: project → user):
Check these paths in order; first hit wins:
```bash
# macOS, Linux, WSL, Git Bash
test -f .baoyu-skills/baoyu-image-gen/EXTEND.md && echo "project"
test -f "${XDG_CONFIG_HOME:-$HOME/.config}/baoyu-skills/baoyu-image-gen/EXTEND.md" && echo "xdg"
test -f "$HOME/.baoyu-skills/baoyu-image-gen/EXTEND.md" && echo "user"
```
```powershell
# PowerShell (Windows)
if (Test-Path .baoyu-skills/baoyu-image-gen/EXTEND.md) { "project" }
$xdg = if ($env:XDG_CONFIG_HOME) { $env:XDG_CONFIG_HOME } else { "$HOME/.config" }
if (Test-Path "$xdg/baoyu-skills/baoyu-image-gen/EXTEND.md") { "xdg" }
if (Test-Path "$HOME/.baoyu-skills/baoyu-image-gen/EXTEND.md") { "user" }
```
| Result | Action |
|--------|--------|
| Found | Load, parse, apply settings. If `default_model.[provider]` is null → ask model only (Flow 2) |
| Not found | ⛔ Run first-time setup ([references/config/first-time-setup.md](references/config/first-time-setup.md)) → Save EXTEND.md → Then continue |
**CRITICAL**: If not found, complete the full setup (provider + model + quality + save location) using AskUserQuestion BEFORE generating any images. Generation is BLOCKED until EXTEND.md is created.
| Path | Location |
|------|----------|
| `.baoyu-skills/baoyu-image-gen/EXTEND.md` | Project directory |
| Path | Scope |
|------|-------|
| `.baoyu-skills/baoyu-image-gen/EXTEND.md` | Project |
| `${XDG_CONFIG_HOME:-$HOME/.config}/baoyu-skills/baoyu-image-gen/EXTEND.md` | XDG |
| `$HOME/.baoyu-skills/baoyu-image-gen/EXTEND.md` | User home |
**EXTEND.md Supports**: Default provider | Default quality | Default aspect ratio | Default image size | Default models | Batch worker cap | Provider-specific batch limits
- **Found** → load, parse, apply. If `default_model.[provider]` is null → ask model only.
- **Not found** → run first-time setup (`references/config/first-time-setup.md`) using AskUserQuestion to collect provider + model + quality + save location. Save EXTEND.md, then continue. Do not generate images before this completes.
Schema: `references/config/preferences-schema.md`
**EXTEND.md keys**: default provider, default quality, default aspect ratio, default image size, OpenAI image API dialect, default models, batch worker cap, provider-specific batch limits. Schema: `references/config/preferences-schema.md`.
## Usage
Minimum working examples — see `references/usage-examples.md` for the full set including per-provider invocations and batch mode.
```bash
# Basic
${BUN_X} {baseDir}/scripts/main.ts --prompt "A cat" --image cat.png
# With aspect ratio
${BUN_X} {baseDir}/scripts/main.ts --prompt "A landscape" --image out.png --ar 16:9
# With aspect ratio and high quality
${BUN_X} {baseDir}/scripts/main.ts --prompt "A landscape" --image out.png --ar 16:9 --quality 2k
# High quality
${BUN_X} {baseDir}/scripts/main.ts --prompt "A cat" --image out.png --quality 2k
# From prompt files
# Prompt from files
${BUN_X} {baseDir}/scripts/main.ts --promptfiles system.md content.md --image out.png
# With reference images (Google, OpenAI, Azure OpenAI, OpenRouter, Replicate, MiniMax, or Seedream 4.0/4.5/5.0)
# With reference image
${BUN_X} {baseDir}/scripts/main.ts --prompt "Make blue" --image out.png --ref source.png
# With reference images (explicit provider/model)
${BUN_X} {baseDir}/scripts/main.ts --prompt "Make blue" --image out.png --provider google --model gemini-3-pro-image-preview --ref source.png
# Azure OpenAI (model means deployment name)
${BUN_X} {baseDir}/scripts/main.ts --prompt "A cat" --image out.png --provider azure --model gpt-image-1.5
# OpenRouter (recommended default model)
${BUN_X} {baseDir}/scripts/main.ts --prompt "A cat" --image out.png --provider openrouter
# OpenRouter with reference images
${BUN_X} {baseDir}/scripts/main.ts --prompt "Make blue" --image out.png --provider openrouter --model google/gemini-3.1-flash-image-preview --ref source.png
# Specific provider
${BUN_X} {baseDir}/scripts/main.ts --prompt "A cat" --image out.png --provider openai
${BUN_X} {baseDir}/scripts/main.ts --prompt "A cat" --image out.png --provider dashscope --model qwen-image-2.0-pro
# DashScope (阿里通义万象)
${BUN_X} {baseDir}/scripts/main.ts --prompt "一只可爱的猫" --image out.png --provider dashscope
# DashScope Qwen-Image 2.0 Pro (recommended for custom sizes and text rendering)
${BUN_X} {baseDir}/scripts/main.ts --prompt "为咖啡品牌设计一张 21:9 横幅海报,包含清晰中文标题" --image out.png --provider dashscope --model qwen-image-2.0-pro --size 2048x872
# DashScope legacy Qwen fixed-size model
${BUN_X} {baseDir}/scripts/main.ts --prompt "一张电影感海报" --image out.png --provider dashscope --model qwen-image-max --size 1664x928
# MiniMax
${BUN_X} {baseDir}/scripts/main.ts --prompt "A fashion editorial portrait by a bright studio window" --image out.jpg --provider minimax
# MiniMax with subject reference (best for character/portrait consistency)
${BUN_X} {baseDir}/scripts/main.ts --prompt "A girl stands by the library window, cinematic lighting" --image out.jpg --provider minimax --model image-01 --ref portrait.png --ar 16:9
# MiniMax with custom size (documented for image-01)
${BUN_X} {baseDir}/scripts/main.ts --prompt "A cinematic poster" --image out.jpg --provider minimax --model image-01 --size 1536x1024
# Replicate (google/nano-banana-pro)
${BUN_X} {baseDir}/scripts/main.ts --prompt "A cat" --image out.png --provider replicate
# Replicate with specific model
${BUN_X} {baseDir}/scripts/main.ts --prompt "A cat" --image out.png --provider replicate --model google/nano-banana
# Batch mode with saved prompt files
${BUN_X} {baseDir}/scripts/main.ts --batchfile batch.json
# Batch mode with explicit worker count
${BUN_X} {baseDir}/scripts/main.ts --batchfile batch.json --jobs 4 --json
# Batch mode
${BUN_X} {baseDir}/scripts/main.ts --batchfile batch.json --jobs 4
```
### Batch File Format
```json
{
"jobs": 4,
"tasks": [
{
"id": "hero",
"promptFiles": ["prompts/hero.md"],
"image": "out/hero.png",
"provider": "replicate",
"model": "google/nano-banana-pro",
"ar": "16:9",
"quality": "2k"
},
{
"id": "diagram",
"promptFiles": ["prompts/diagram.md"],
"image": "out/diagram.png",
"ref": ["references/original.png"]
}
]
}
```
Paths in `promptFiles`, `image`, and `ref` are resolved relative to the batch file's directory. `jobs` is optional (overridden by CLI `--jobs`). Top-level array format (without `jobs` wrapper) is also accepted.
## Options
| Option | Description |
@@ -161,14 +80,15 @@ Paths in `promptFiles`, `image`, and `ref` are resolved relative to the batch fi
| `--image <path>` | Output image path (required in single-image mode) |
| `--batchfile <path>` | JSON batch file for multi-image generation |
| `--jobs <count>` | Worker count for batch mode (default: auto, max from config, built-in default 10) |
| `--provider google\|openai\|azure\|openrouter\|dashscope\|minimax\|jimeng\|seedream\|replicate` | Force provider (default: auto-detect) |
| `--model <id>`, `-m` | Model ID (Google: `gemini-3-pro-image-preview`; OpenAI: `gpt-image-1.5`; Azure: deployment name such as `gpt-image-1.5` or `image-prod`; OpenRouter: `google/gemini-3.1-flash-image-preview`; DashScope: `qwen-image-2.0-pro`; MiniMax: `image-01`) |
| `--ar <ratio>` | Aspect ratio (e.g., `16:9`, `1:1`, `4:3`) |
| `--size <WxH>` | Size (e.g., `1024x1024`) |
| `--provider google\|openai\|azure\|openrouter\|dashscope\|zai\|minimax\|jimeng\|seedream\|replicate` | Force provider (default: auto-detect) |
| `--model <id>`, `-m` | Model ID — see provider references for defaults and allowed values |
| `--ar <ratio>` | Aspect ratio (`16:9`, `1:1`, `4:3`, …) |
| `--size <WxH>` | Explicit size (e.g., `1024x1024`) |
| `--quality normal\|2k` | Quality preset (default: `2k`) |
| `--imageSize 1K\|2K\|4K` | Image size for Google/OpenRouter (default: from quality) |
| `--ref <files...>` | Reference images. Supported by Google multimodal, OpenAI GPT Image edits, Azure OpenAI edits (PNG/JPG only), OpenRouter multimodal models, Replicate, MiniMax subject-reference, and Seedream 5.0/4.5/4.0. Not supported by Jimeng, Seedream 3.0, or removed SeedEdit 3.0 |
| `--n <count>` | Number of images |
| `--imageApiDialect openai-native\|ratio-metadata` | OpenAI-compatible endpoint dialect — use `ratio-metadata` for gateways that expect aspect-ratio `size` plus `metadata.resolution` |
| `--ref <files...>` | Reference images. Supported by Google multimodal, OpenAI GPT Image edits, Azure OpenAI edits (PNG/JPG only), OpenRouter multimodal models, Replicate supported families, MiniMax subject-reference, Seedream 5.0/4.5/4.0. Not supported by Jimeng, Seedream 3.0, SeedEdit 3.0 |
| `--n <count>` | Number of images. Replicate requires `--n 1` (single-output save semantics) |
| `--json` | JSON output |
## Environment Variables
@@ -179,221 +99,109 @@ Paths in `promptFiles`, `image`, and `ref` are resolved relative to the batch fi
| `AZURE_OPENAI_API_KEY` | Azure OpenAI API key |
| `OPENROUTER_API_KEY` | OpenRouter API key |
| `GOOGLE_API_KEY` | Google API key |
| `DASHSCOPE_API_KEY` | DashScope API key (阿里云) |
| `DASHSCOPE_API_KEY` | DashScope API key |
| `ZAI_API_KEY` (alias `BIGMODEL_API_KEY`) | Z.AI API key |
| `MINIMAX_API_KEY` | MiniMax API key |
| `REPLICATE_API_TOKEN` | Replicate API token |
| `JIMENG_ACCESS_KEY_ID` | Jimeng (即梦) Volcengine access key |
| `JIMENG_SECRET_ACCESS_KEY` | Jimeng (即梦) Volcengine secret key |
| `JIMENG_ACCESS_KEY_ID`, `JIMENG_SECRET_ACCESS_KEY` | Jimeng (即梦) Volcengine credentials |
| `ARK_API_KEY` | Seedream (豆包) Volcengine ARK API key |
| `OPENAI_IMAGE_MODEL` | OpenAI model override |
| `AZURE_OPENAI_DEPLOYMENT` | Azure default deployment name |
| `AZURE_OPENAI_IMAGE_MODEL` | Backward-compatible alias for Azure default deployment/model name |
| `OPENROUTER_IMAGE_MODEL` | OpenRouter model override (default: `google/gemini-3.1-flash-image-preview`) |
| `GOOGLE_IMAGE_MODEL` | Google model override |
| `DASHSCOPE_IMAGE_MODEL` | DashScope model override (default: `qwen-image-2.0-pro`) |
| `MINIMAX_IMAGE_MODEL` | MiniMax model override (default: `image-01`) |
| `REPLICATE_IMAGE_MODEL` | Replicate model override (default: google/nano-banana-pro) |
| `JIMENG_IMAGE_MODEL` | Jimeng model override (default: jimeng_t2i_v40) |
| `SEEDREAM_IMAGE_MODEL` | Seedream model override (default: doubao-seedream-5-0-260128) |
| `OPENAI_BASE_URL` | Custom OpenAI endpoint |
| `AZURE_OPENAI_BASE_URL` | Azure resource endpoint or deployment endpoint |
| `AZURE_API_VERSION` | Azure image API version (default: `2025-04-01-preview`) |
| `OPENROUTER_BASE_URL` | Custom OpenRouter endpoint (default: `https://openrouter.ai/api/v1`) |
| `OPENROUTER_HTTP_REFERER` | Optional app/site URL for OpenRouter attribution |
| `OPENROUTER_TITLE` | Optional app name for OpenRouter attribution |
| `GOOGLE_BASE_URL` | Custom Google endpoint |
| `DASHSCOPE_BASE_URL` | Custom DashScope endpoint |
| `MINIMAX_BASE_URL` | Custom MiniMax endpoint (default: `https://api.minimax.io`) |
| `REPLICATE_BASE_URL` | Custom Replicate endpoint |
| `JIMENG_BASE_URL` | Custom Jimeng endpoint (default: `https://visual.volcengineapi.com`) |
| `JIMENG_REGION` | Jimeng region (default: `cn-north-1`) |
| `SEEDREAM_BASE_URL` | Custom Seedream endpoint (default: `https://ark.cn-beijing.volces.com/api/v3`) |
| `<PROVIDER>_IMAGE_MODEL` | Per-provider model override (`OPENAI_IMAGE_MODEL`, `GOOGLE_IMAGE_MODEL`, `DASHSCOPE_IMAGE_MODEL`, `ZAI_IMAGE_MODEL`/`BIGMODEL_IMAGE_MODEL`, `MINIMAX_IMAGE_MODEL`, `OPENROUTER_IMAGE_MODEL`, `REPLICATE_IMAGE_MODEL`, `JIMENG_IMAGE_MODEL`, `SEEDREAM_IMAGE_MODEL`) |
| `AZURE_OPENAI_DEPLOYMENT` (alias `AZURE_OPENAI_IMAGE_MODEL`) | Azure default deployment |
| `<PROVIDER>_BASE_URL` | Per-provider endpoint override |
| `AZURE_API_VERSION` | Azure image API version (default `2025-04-01-preview`) |
| `JIMENG_REGION` | Jimeng region (default `cn-north-1`) |
| `OPENAI_IMAGE_API_DIALECT` | `openai-native` \| `ratio-metadata` |
| `OPENROUTER_HTTP_REFERER`, `OPENROUTER_TITLE` | Optional OpenRouter attribution |
| `BAOYU_IMAGE_GEN_MAX_WORKERS` | Override batch worker cap |
| `BAOYU_IMAGE_GEN_<PROVIDER>_CONCURRENCY` | Override provider concurrency, e.g. `BAOYU_IMAGE_GEN_REPLICATE_CONCURRENCY` |
| `BAOYU_IMAGE_GEN_<PROVIDER>_START_INTERVAL_MS` | Override provider start gap, e.g. `BAOYU_IMAGE_GEN_REPLICATE_START_INTERVAL_MS` |
| `BAOYU_IMAGE_GEN_<PROVIDER>_CONCURRENCY` | Per-provider concurrency (e.g., `BAOYU_IMAGE_GEN_REPLICATE_CONCURRENCY`) |
| `BAOYU_IMAGE_GEN_<PROVIDER>_START_INTERVAL_MS` | Per-provider start-gap |
**Load Priority**: CLI args > EXTEND.md > env vars > `<cwd>/.baoyu-skills/.env` > `~/.baoyu-skills/.env`
**Load priority**: CLI args > EXTEND.md > env vars > `<cwd>/.baoyu-skills/.env` > `~/.baoyu-skills/.env`
## Model Resolution
Model priority (highest → lowest), applies to all providers:
Priority (highest → lowest) applies to every provider:
1. CLI flag: `--model <id>`
2. EXTEND.md: `default_model.[provider]`
3. Env var: `<PROVIDER>_IMAGE_MODEL` (e.g., `GOOGLE_IMAGE_MODEL`)
1. CLI flag `--model <id>`
2. EXTEND.md `default_model.[provider]`
3. Env var `<PROVIDER>_IMAGE_MODEL`
4. Built-in default
For Azure, `--model` / `default_model.azure` should be the Azure deployment name. `AZURE_OPENAI_DEPLOYMENT` is the preferred env var, and `AZURE_OPENAI_IMAGE_MODEL` remains as a backward-compatible alias.
For Azure, `--model` / `default_model.azure` is the Azure deployment name. `AZURE_OPENAI_DEPLOYMENT` is the preferred env var; `AZURE_OPENAI_IMAGE_MODEL` is kept as a backward-compatible alias.
**EXTEND.md overrides env vars**. If both EXTEND.md `default_model.google: "gemini-3-pro-image-preview"` and env var `GOOGLE_IMAGE_MODEL=gemini-3.1-flash-image-preview` exist, EXTEND.md wins.
EXTEND.md overrides env vars: if EXTEND.md sets `default_model.google: "gemini-3-pro-image-preview"` and the env var sets `GOOGLE_IMAGE_MODEL=gemini-3.1-flash-image-preview`, EXTEND.md wins.
**Agent MUST display model info** before each generation:
- Show: `Using [provider] / [model]`
- Show switch hint: `Switch model: --model <id> | EXTEND.md default_model.[provider] | env <PROVIDER>_IMAGE_MODEL`
**Display model info before each generation**:
### DashScope Models
- `Using [provider] / [model]`
- `Switch model: --model <id> | EXTEND.md default_model.[provider] | env <PROVIDER>_IMAGE_MODEL`
Use `--model qwen-image-2.0-pro` or set `default_model.dashscope` / `DASHSCOPE_IMAGE_MODEL` when the user wants official Qwen-Image behavior.
## OpenAI-Compatible Gateway Dialects
Official DashScope model families:
`provider=openai` means the auth and routing entrypoint is OpenAI-compatible. It does **not** guarantee the upstream image API uses OpenAI native semantics. When a gateway expects a different wire format, set `default_image_api_dialect` in EXTEND.md, `OPENAI_IMAGE_API_DIALECT`, or `--imageApiDialect`:
- `qwen-image-2.0-pro`, `qwen-image-2.0-pro-2026-03-03`, `qwen-image-2.0`, `qwen-image-2.0-2026-03-03`
- Free-form `size` in `宽*高` format
- Total pixels must stay between `512*512` and `2048*2048`
- Default size is approximately `1024*1024`
- Best choice for custom ratios such as `21:9` and text-heavy Chinese/English layouts
- `qwen-image-max`, `qwen-image-max-2025-12-30`, `qwen-image-plus`, `qwen-image-plus-2026-01-09`, `qwen-image`
- Fixed sizes only: `1664*928`, `1472*1104`, `1328*1328`, `1104*1472`, `928*1664`
- Default size is `1664*928`
- `qwen-image` currently has the same capability as `qwen-image-plus`
- Legacy DashScope models such as `z-image-turbo`, `z-image-ultra`, `wanx-v1`
- Keep using them only when the user explicitly asks for legacy behavior or compatibility
- `openai-native`: pixel `size` (`1536x1024`) and native OpenAI quality fields
- `ratio-metadata`: aspect-ratio `size` (`16:9`) plus `metadata.resolution` (`1K|2K|4K`) and `metadata.orientation`
When translating CLI args into DashScope behavior:
Use `openai-native` for the OpenAI native API or strict clones; try `ratio-metadata` for compatibility gateways in front of Gemini or similar models. Current limitation: `ratio-metadata` applies only to text-to-image; reference-image edits still need `openai-native` or a provider with first-class edit support.
- `--size` wins over `--ar`
- For `qwen-image-2.0*`, prefer explicit `--size`; otherwise infer from `--ar` and use the official recommended resolutions below
- For `qwen-image-max/plus/image`, only use the five official fixed sizes; if the requested ratio is not covered, switch to `qwen-image-2.0-pro`
- `--quality` is a baoyu-image-gen compatibility preset, not a native DashScope API field. Mapping `normal` / `2k` onto the `qwen-image-2.0*` table below is an implementation inference, not an official API guarantee
## Provider-Specific Guides
Recommended `qwen-image-2.0*` sizes for common aspect ratios:
Each provider has its own quirks (model families, size rules, ref support, limits). Read these when the user picks that provider or asks for non-default behavior:
| Ratio | `normal` | `2k` |
|-------|----------|------|
| `1:1` | `1024*1024` | `1536*1536` |
| `2:3` | `768*1152` | `1024*1536` |
| `3:2` | `1152*768` | `1536*1024` |
| `3:4` | `960*1280` | `1080*1440` |
| `4:3` | `1280*960` | `1440*1080` |
| `9:16` | `720*1280` | `1080*1920` |
| `16:9` | `1280*720` | `1920*1080` |
| `21:9` | `1344*576` | `2048*872` |
DashScope official APIs also expose `negative_prompt`, `prompt_extend`, and `watermark`, but `baoyu-image-gen` does not expose them as dedicated CLI flags today.
Official references:
- [Qwen-Image API](https://help.aliyun.com/zh/model-studio/qwen-image-api)
- [Text-to-image guide](https://help.aliyun.com/zh/model-studio/text-to-image)
- [Qwen-Image Edit API](https://help.aliyun.com/zh/model-studio/qwen-image-edit-api)
### MiniMax Models
Use `--model image-01` or set `default_model.minimax` / `MINIMAX_IMAGE_MODEL` when the user wants MiniMax image generation.
Official MiniMax image model options currently documented in the API reference:
- `image-01` (recommended default)
- Supports text-to-image and subject-reference image generation
- Supports official `aspect_ratio` values: `1:1`, `16:9`, `4:3`, `3:2`, `2:3`, `3:4`, `9:16`, `21:9`
- Supports documented custom `width` / `height` output sizes when using `--size <WxH>`
- `width` and `height` must both be between `512` and `2048`, and both must be divisible by `8`
- `image-01-live`
- Lower-latency variant
- Use `--ar` for sizing; MiniMax documents custom `width` / `height` as only effective for `image-01`
MiniMax subject reference notes:
- `--ref` files are sent as MiniMax `subject_reference`
- MiniMax docs currently describe `subject_reference[].type` as `character`
- Official docs say `image_file` supports public URLs or Base64 Data URLs; `baoyu-image-gen` sends local refs as Data URLs
- Official docs recommend front-facing portrait references in JPG/JPEG/PNG under 10MB
Official references:
- [MiniMax Image Generation Guide](https://platform.minimax.io/docs/guides/image-generation)
- [MiniMax Text-to-Image API](https://platform.minimax.io/docs/api-reference/image-generation-t2i)
- [MiniMax Image-to-Image API](https://platform.minimax.io/docs/api-reference/image-generation-i2i)
### OpenRouter Models
Use full OpenRouter model IDs, e.g.:
- `google/gemini-3.1-flash-image-preview` (recommended, supports image output and reference-image workflows)
- `google/gemini-2.5-flash-image-preview`
- `black-forest-labs/flux.2-pro`
- Other OpenRouter image-capable model IDs
Notes:
- OpenRouter image generation uses `/chat/completions`, not the OpenAI `/images` endpoints
- If `--ref` is used, choose a multimodal model that supports image input and image output
- `--imageSize` maps to OpenRouter `imageGenerationOptions.size`; `--size <WxH>` is converted to the nearest OpenRouter size and inferred aspect ratio when possible
### Replicate Models
Supported model formats:
- `owner/name` (recommended for official models), e.g. `google/nano-banana-pro`
- `owner/name:version` (community models by version), e.g. `stability-ai/sdxl:<version>`
Examples:
```bash
# Use Replicate default model
${BUN_X} {baseDir}/scripts/main.ts --prompt "A cat" --image out.png --provider replicate
# Override model explicitly
${BUN_X} {baseDir}/scripts/main.ts --prompt "A cat" --image out.png --provider replicate --model google/nano-banana
```
| Provider | Reference |
|----------|-----------|
| DashScope (Qwen-Image families, custom sizes) | `references/providers/dashscope.md` |
| Z.AI (GLM-Image, cogview-4) | `references/providers/zai.md` |
| MiniMax (image-01, subject-reference) | `references/providers/minimax.md` |
| OpenRouter (multimodal models, `/chat/completions` flow) | `references/providers/openrouter.md` |
| Replicate (nano-banana, Seedream, Wan) | `references/providers/replicate.md` |
## Provider Selection
1. `--ref` provided + no `--provider` → auto-select Google first, then OpenAI, then Azure, then OpenRouter, then Replicate, then Seedream, then MiniMax (MiniMax subject reference is more specialized toward character/portrait consistency)
2. `--provider` specified → use it (if `--ref`, must be `google`, `openai`, `azure`, `openrouter`, `replicate`, `seedream`, or `minimax`)
3. Only one API key available → use that provider
4. Multiple available → default to Google
1. `--ref` provided + no `--provider` → auto-select Google → OpenAI → Azure → OpenRouter Replicate Seedream MiniMax (MiniMax's subject reference is more specialized toward character/portrait consistency)
2. `--provider` specified → use it (if `--ref`, must be google/openai/azure/openrouter/replicate/seedream/minimax)
3. Only one API key present → use that provider
4. Multiple keys → default priority: Google → OpenAI → Azure → OpenRouter → DashScope → Z.AI → MiniMax → Replicate → Jimeng → Seedream
## Quality Presets
| Preset | Google imageSize | OpenAI Size | OpenRouter size | Replicate resolution | Use Case |
| Preset | Google imageSize | OpenAI size | OpenRouter size | Replicate resolution | Use case |
|--------|------------------|-------------|-----------------|----------------------|----------|
| `normal` | 1K | 1024px | 1K | 1K | Quick previews |
| `2k` (default) | 2K | 2048px | 2K | 2K | Covers, illustrations, infographics |
**Google/OpenRouter imageSize**: Can be overridden with `--imageSize 1K|2K|4K`
Google/OpenRouter `imageSize` can be overridden with `--imageSize 1K|2K|4K`.
## Aspect Ratios
Supported: `1:1`, `16:9`, `9:16`, `4:3`, `3:4`, `2.35:1`
Supported: `1:1`, `16:9`, `9:16`, `4:3`, `3:4`, `2.35:1`.
- Google multimodal: uses `imageConfig.aspectRatio`
- OpenAI: maps to closest supported size
- OpenRouter: sends `imageGenerationOptions.aspect_ratio`; if only `--size <WxH>` is given, aspect ratio is inferred automatically
- Replicate: passes `aspect_ratio` to model; when `--ref` is provided without `--ar`, defaults to `match_input_image`
- MiniMax: sends official `aspect_ratio` values directly; if `--size <WxH>` is given without `--ar`, `width` / `height` are sent for `image-01`
- Google multimodal: `imageConfig.aspectRatio`
- OpenAI: closest supported size
- OpenRouter: `imageGenerationOptions.aspect_ratio`; if only `--size <WxH>` is given, the ratio is inferred
- Replicate: behavior is model-specific — `google/nano-banana*` uses `aspect_ratio`, `bytedance/seedream-*` uses documented Replicate ratios, Wan 2.7 maps `--ar` to a concrete `size`
- MiniMax: official `aspect_ratio` values; if `--size <WxH>` is given without `--ar`, sends `width`/`height` for `image-01`
## Generation Mode
**Default**: Sequential generation.
**Default**: sequential. **Batch parallel**: enabled automatically when `--batchfile` contains 2+ pending tasks.
**Batch Parallel Generation**: When `--batchfile` contains 2 or more pending tasks, the script automatically enables parallel generation.
| Situation | Prefer | Why |
|-----------|--------|-----|
| One image, or 1-2 simple images | Sequential | Lower coordination overhead, easier debugging |
| Multiple images with saved prompt files | Batch (`--batchfile`) | Reuses finalized prompts, applies shared throttling/retries, predictable throughput |
| Each image still needs its own reasoning / prompt writing / style exploration | Subagents | Work is still exploratory, each needs independent analysis |
| Input is `outline.md` + `prompts/` (e.g. from `baoyu-article-illustrator`) | Batch — use `scripts/build-batch.ts` to assemble the payload | The outline + prompt files already contain everything needed |
| Mode | When to Use |
|------|-------------|
| Sequential (default) | Normal usage, single images, small batches |
| Parallel batch | Batch mode with 2+ tasks |
Rule of thumb: once prompt files are saved and the task is "generate all of these", prefer batch over subagents. Use subagents only when generation is coupled with per-image thinking or divergent creative exploration.
Execution choice:
| Situation | Preferred approach | Why |
|-----------|--------------------|-----|
| One image, or 1-2 simple images | Sequential | Lower coordination overhead and easier debugging |
| Multiple images already have saved prompt files | Batch (`--batchfile`) | Reuses finalized prompts, applies shared throttling/retries, and gives predictable throughput |
| Each image still needs separate reasoning, prompt writing, or style exploration | Subagents | The work is still exploratory, so each image may need independent analysis before generation |
| Output comes from `baoyu-article-illustrator` with `outline.md` + `prompts/` | Batch (`build-batch.ts` -> `--batchfile`) | That workflow already produces prompt files, so direct batch execution is the intended path |
Rule of thumb:
- Prefer batch over subagents once prompt files are already saved and the task is "generate all of these"
- Use subagents only when generation is coupled with per-image thinking, rewriting, or divergent creative exploration
Parallel behavior:
**Parallel behavior**:
- Default worker count is automatic, capped by config, built-in default 10
- Provider-specific throttling is applied only in batch mode, and the built-in defaults are tuned for faster throughput while still avoiding obvious RPM bursts
- You can override worker count with `--jobs <count>`
- Each image retries automatically up to 3 attempts
- Provider-specific throttling applies only in batch mode; defaults are tuned for throughput while avoiding RPM bursts
- Override with `--jobs <count>`
- Each image retries up to 3 attempts
- Final output includes success count, failure count, and per-image failure reasons
## Error Handling
@@ -403,6 +211,19 @@ Parallel behavior:
- Invalid aspect ratio → warning, proceed with default
- Reference images with unsupported provider/model → error with fix hint
## References
| File | Content |
|------|---------|
| `references/usage-examples.md` | Extended CLI examples across providers and batch mode |
| `references/providers/dashscope.md` | DashScope families, sizes, limits |
| `references/providers/zai.md` | Z.AI GLM-image / cogview-4 |
| `references/providers/minimax.md` | MiniMax image-01 + subject reference |
| `references/providers/openrouter.md` | OpenRouter multimodal flow |
| `references/providers/replicate.md` | Replicate supported families + guardrails |
| `references/config/preferences-schema.md` | EXTEND.md schema |
| `references/config/first-time-setup.md` | First-time setup flow |
## Extension Support
Custom configurations via EXTEND.md. See **Preferences** section for paths and supported options.
Custom configurations via EXTEND.md. See Step 0 for paths and schema.