Image Generation (AI SDK)

Official API-based image generation. Supports OpenAI GPT Image 2.5, Azure OpenAI, Google, OpenRouter, DashScope (阿里通义万象), Z.AI GLM-Image, MiniMax, Jimeng (即梦), Seedream (豆包), Replicate and Agnes.

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

{baseDir} = this SKILL.md's directory. All scripts/... paths below are relative to {baseDir}. Main script: {baseDir}/scripts/main.ts. Batch payload helper: {baseDir}/scripts/build-batch.ts. Resolve ${BUN_X}: prefer bun; else npx -y bun; else suggest brew install oven-sh/bun/bun.

Step 0: Load Preferences ⛔ BLOCKING

This step MUST complete before any image generation — generation is blocked until EXTEND.md exists.

Check these paths in order; first hit wins:

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

• 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.

Legacy compatibility: if .baoyu-skills/baoyu-imagine/EXTEND.md exists and the new path doesn't, the runtime renames it to baoyu-image-gen. If both exist, the runtime leaves them alone and uses the new path.

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.

Identity-preserving reference prompts

When the user wants a real person/character/object preserved from reference images, do not replace the reference with a long generic description. Prefer short, hard identity-preservation language:

• "Use the person/object in the reference image(s) as the same identity. Do not redesign it or create a similar-looking new subject."
• "Only change scene, clothing, pose, lighting, rendering style, and composition. Keep the face/proportions/hair/key accessories/overall identity from the references."
• If using multiple references, state that they are the same subject and should jointly define identity.

Pitfall: long descriptions like "young East Asian woman, oval face, clear eyes..." can cause the model to synthesize a new person matching the description instead of preserving the referenced person.

# Basic
${BUN_X} {baseDir}/scripts/main.ts --prompt "A cat" --image cat.png

# With aspect ratio and high quality
${BUN_X} {baseDir}/scripts/main.ts --prompt "A landscape" --image out.png --ar 16:9 --quality 2k

# Prompt from files
${BUN_X} {baseDir}/scripts/main.ts --promptfiles system.md content.md --image out.png

# With reference image
${BUN_X} {baseDir}/scripts/main.ts --prompt "Make blue" --image out.png --ref source.png

# Specific provider
${BUN_X} {baseDir}/scripts/main.ts --prompt "A cat" --image out.png --provider dashscope --model qwen-image-2.0-pro

# OpenAI GPT Image 2
${BUN_X} {baseDir}/scripts/main.ts --prompt "A cat" --image out.png --provider openai --model gpt-image-2.5-flare

# Codex CLI (uses logged-in Codex subscription — no OPENAI_API_KEY required; requires `codex` on PATH)
${BUN_X} {baseDir}/scripts/main.ts --prompt "A cat" --image out.png --provider codex-cli --ar 16:9

# Batch mode
${BUN_X} {baseDir}/scripts/main.ts --batchfile batch.json --jobs 4

# Build a batch file from outline.md + prompts/ (e.g. baoyu-article-illustrator output)
${BUN_X} {baseDir}/scripts/build-batch.ts --outline outline.md --prompts prompts --output batch.json --images-dir attachments
${BUN_X} {baseDir}/scripts/main.ts --batchfile batch.json --jobs 4

Reference-Image Identity Preservation

When the user wants a person/object preserved from reference images:

• Prefer a small curated set of existing source references (usually 2–4) over many images; large multi-megabyte refs can destabilize streaming providers.
• Make the prompt say the references are the same subject and the output must use that identity. Avoid long generic facial-feature descriptions that can cause the model to synthesize a new similar-looking person.
• Do not use newly generated outputs as references unless the user explicitly asks; generated refs compound drift.
• If results become too polished or influencer-like, reduce stylized refs and add explicit anti-beautification constraints (no face slimming, eye enlargement, heavy makeup, commercial travel shoot, over-smoothing).
• If the subject should look younger/older, preserve the face and express age through clothing, posture, scene, and styling; do not ask the model to change facial identity.

Options

Option	Description
--prompt <text>, -p	Prompt text
--promptfiles <files...>	Read prompt from files (concatenated)
--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|zai|minimax|jimeng|seedream|replicate|codex-cli|agnes	Force provider (default: auto-detect; codex-cli is never auto-selected — must be pinned via CLI or EXTEND.md)
--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; for gpt-image-2.5-* and gpt-image-2, width/height must be multiples of 16, max edge 3840px, ratio no wider than 3:1)
--quality normal|2k	Quality preset (default: 2k)
--imageSize 1K|2K|4K	Image size for Google/OpenRouter (default: from quality)
--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, DashScope wan2.7-image-pro/wan2.7-image. Not supported by Jimeng, Seedream 3.0, SeedEdit 3.0, or any DashScope model outside the wan2.7-image* family
--n <count>	Number of images. Replicate requires --n 1 (single-output save semantics)

Environment Variables

Variable	Description
OPENAI_API_KEY	OpenAI API key
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
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_SECRET_ACCESS_KEY	Jimeng (即梦) Volcengine credentials
ARK_API_KEY	Seedream (豆包) Volcengine ARK API key
<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, AGNES_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

Load priority: CLI args > EXTEND.md > env vars > <cwd>/.baoyu-skills/.env > ~/.baoyu-skills/.env

Codex/ChatGPT OAuth is not an OpenAI API key

--provider openai --model gpt-image-2.5-flare uses the standard OpenAI Images API (/v1/images/generations or /v1/images/edits) and requires OPENAI_API_KEY. A Codex or ChatGPT desktop login is a different entitlement and is not a drop-in replacement for OPENAI_API_KEY; do not paste a Codex OAuth token into OPENAI_API_KEY or only set OPENAI_BASE_URL to a Codex backend.

If the user wants to use their Codex subscription / GPT Image 2 entitlement without an OpenAI API key, route through a Codex-native backend instead of this skill's openai provider:

• In Codex runtime: use the native imagegen skill/tool.
• In non-Codex runtimes with codex CLI installed and logged in: use baoyu-image-gen --provider codex-cli (preferred — it gives you the same retry / cache / batch flow as every other provider). The provider spawns the bundled scripts/codex-imagegen/main.ts; the same code lives upstream at packages/baoyu-codex-imagegen/src/main.ts for standalone callers.
• In Hermes runtimes with a native image_generate tool: use that tool as a fallback, and state whether reference images were passed directly or reconstructed from extracted traits.

Do not modify the existing openai provider to silently consume Codex OAuth. The first-class Codex-CLI path is the dedicated codex-cli provider, which has its own auth (Codex login), route (codex exec), request shape, and tests. See references/codex-oauth-vs-openai-api-key.md.

Model Resolution

Priority (highest → lowest) applies to every provider:

1. CLI flag --model <id>
2. EXTEND.md default_model.[provider]
3. Env var <PROVIDER>_IMAGE_MODEL
4. Built-in default

For OpenAI, the built-in default is gpt-image-2.5-flare (fast, lowest latency). gpt-image-2.5-sunburst is the most capable variant for complex scenes and precise edits; gpt-image-2, gpt-image-1.5, gpt-image-1, and dated GPT Image snapshots (e.g. gpt-image-2.5-flare-2026-09-08, gpt-image-2-2026-04-21) remain selectable with --model or OPENAI_IMAGE_MODEL.

For Google, the built-in default is gemini-3-pro-image. gemini-3.1-flash-image is the faster low-cost option, and gemini-3.1-flash-lite-image is the cheapest — it only produces 1K output, so --quality 2k / --imageSize 2K|4K is clamped to 1K with a warning.

For DashScope, the built-in default is qwen-image-2.0-pro; qwen-image-3.0-pro is the newest flagship and uses the same sizing rules.

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. If your Azure deployment is named after the underlying model, use gpt-image-2.5-flare; otherwise use the exact custom deployment name.

EXTEND.md overrides env vars: if EXTEND.md sets default_model.google: "gemini-3-pro-image" and the env var sets GOOGLE_IMAGE_MODEL=gemini-3.1-flash-image, EXTEND.md wins.

Display model info before each generation:

• Using [provider] / [model]
• Switch model: --model <id> | EXTEND.md default_model.[provider] | env <PROVIDER>_IMAGE_MODEL

OpenAI-Compatible Gateway Dialects

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:

• 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

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.

Provider-Specific Guides

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:

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
Codex CLI (wraps bundled scripts/codex-imagegen/; Codex login, no OPENAI_API_KEY)	references/providers/codex-cli.md
Agnes (agnes-image-2.5-flash, reference-image support)	references/providers/agnes.md

Provider Selection

1. --ref provided + no --provider → auto-select Google → OpenAI → Azure → OpenRouter → Replicate → Seedream → MiniMax → Agnes (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/codex-cli/agnes)
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 → Agnes
5. codex-cli is never auto-selected — set default_provider: codex-cli in EXTEND.md or pass --provider codex-cli. It spawns codex exec via the bundled scripts/codex-imagegen/main.ts TS entrypoint (run with bun) and uses the user's Codex subscription (no OPENAI_API_KEY). Requires codex on PATH with an active codex login.

Quality Presets

Preset	Google imageSize	OpenAI size	OpenRouter size	Replicate resolution	Use case
normal	1K	1024px target	1K	1K	Quick previews
2k (default)	2K	2048px target	2K	2K	Covers, illustrations, infographics

Google/OpenRouter imageSize can be overridden with --imageSize 1K|2K|4K.

For OpenAI native gpt-image-2.5-* and gpt-image-2, normal maps to quality=medium and a low-latency valid size near the requested aspect ratio; 2k maps to quality=high and 2048px-class sizes such as 2048x2048, 2048x1152, or 1152x2048. Use explicit --size for valid custom or 4K outputs, e.g. 3840x2160.

Aspect Ratios

Supported: 1:1, 16:9, 9:16, 4:3, 3:4, 2.35:1.

• Google multimodal: imageConfig.aspectRatio
• OpenAI: gpt-image-2.5-* and gpt-image-2 use the closest valid custom size for the requested ratio; older GPT Image and DALL·E models use their closest supported fixed 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. Batch parallel: enabled automatically when --batchfile contains 2+ pending tasks.

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 {baseDir}/scripts/build-batch.ts to assemble the payload	The outline + prompt files already contain everything needed

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.

Parallel behavior:

• Default worker count is automatic, capped by config, built-in default 10
• 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

• Missing API key → error with setup instructions
• Generation failure → auto-retry up to 3 attempts per image
• Invalid aspect ratio → warning, proceed with default
• Reference images with unsupported provider/model → error with fix hint

Codex image2 fallback

If --provider openai --model gpt-image-2.5-flare fails because OPENAI_API_KEY is missing but the current runtime has a native image-generation backend or the repo-level codex-imagegen wrapper is available, use that path rather than leaving the user waiting. Be explicit about whether the fallback is true reference-image generation or only a text-prompt reconstruction from extracted visual traits. See references/codex-image2-fallback.md.

References

File	Content
references/usage-examples.md	Extended CLI examples across providers and batch mode
references/codex-oauth-vs-openai-api-key.md	Why Codex/ChatGPT OAuth image2 entitlement is not usable through baoyu-image-gen's standard OpenAI API-key provider
references/codex-image2-fallback.md	Practical fallback behavior when OpenAI API credentials are absent but Codex/native image generation is available
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/providers/agnes.md	Agnes (agnes-image-2.5-flash) sizing, refs, and limits
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 Step 0 for paths and schema.