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SKILL verified MIT Self-run

Baoyu Image Gen

skill-jimliu-baoyu-skills-baoyu-image-gen · by JimLiu

AI image generation with OpenAI GPT Image 2, Azure OpenAI, Google, OpenRouter, DashScope, Z.AI GLM-Image, MiniMax, Jimeng, Seedream, Replicate and Agnes 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. U…

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Install

$ agentstack add skill-jimliu-baoyu-skills-baoyu-image-gen

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Security review

✓ Passed

No issues found. Passed automated security review. · v0.1.0 How review works →

  • Prompt-injection patterns
  • Secret / credential exfiltration
  • Dangerous shell & filesystem operations
  • Untrusted network calls
  • Known-malicious package signatures

What it can access

  • Network access No
  • Filesystem access No
  • Shell / process execution No
  • Environment & secrets Used
  • Dynamic code execution No

From automated source analysis of v0.1.0. “Used” means the capability is present in the source — more access means more to trust, not that it’s unsafe.

View the full security report →

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Reliability & compatibility

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Declared compatibility

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Compatibility is declared by the source manifest. End-to-end runtime verification is coming, see below.

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About

Image Generation (AI SDK)

Official API-based image generation. Supports OpenAI GPT Image 2, 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

# 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 , -p | Prompt text | | --promptfiles | Read prompt from files (concatenated) | | --image | Output image path (required in single-image mode) | | --batchfile | JSON batch file for multi-image generation | | --jobs | 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 , -m | Model ID — see provider references for defaults and allowed values | | --ar | Aspect ratio (16:9, 1:1, 4:3, …) | | --size | Explicit size (e.g., 1024x1024; for 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 | 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 | Number of images. Replicate requires --n 1 (single-output save semantics) | | --json | JSON output |

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 | | _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 | | _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__CONCURRENCY | Per-provider concurrency (e.g., BAOYU_IMAGE_GEN_REPLICATE_CONCURRENCY; for codex-cli use BAOYU_IMAGE_GEN_CODEX_CLI_CONCURRENCY) | | BAOYU_IMAGE_GEN__START_INTERVAL_MS | Per-provider start-gap | | BAOYU_CODEX_IMAGEGEN_BIN | Override the codex-imagegen wrapper path for the codex-cli provider (default: bundled scripts/codex-imagegen/main.ts; accepts .ts or legacy .sh/binary) | | BAOYU_CODEX_IMAGEGEN_CACHE_DIR | Enable idempotency cache for the codex-cli provider (off by default) | | BAOYU_CODEX_IMAGEGEN_TIMEOUT_MS | Per-attempt codex exec timeout for the codex-cli provider (default: 300000 ms) | | BAOYU_CODEX_IMAGEGEN_RETRIES | Wrapper-side retry attempts on retryable errors for the codex-cli provider (default: 2) | | BAOYU_CODEX_IMAGEGEN_LOG_FILE | Append JSONL diagnostic log for the codex-cli provider |

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

Codex/ChatGPT OAuth is not an OpenAI API key

--provider openai --model gpt-image-2 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
  2. EXTEND.md default_model.[provider]
  3. Env var _IMAGE_MODEL
  4. Built-in default

For OpenAI, the built-in default is gpt-image-2. gpt-image-1.5, gpt-image-1, and GPT Image snapshots remain selectable with --model or OPENAI_IMAGE_MODEL.

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; 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 | EXTEND.md default_model.[provider] | env _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-2.1-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, 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 uses the closest valid custom size for the requested ratio; older GPT Image and DALL·E models u

Source & license

This open-source skill is cataloged on AgentStack and links to its original source — we do not rehost the code.

Install and usage instructions live in the source repository linked above.

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Versions

  • v0.1.0 Imported from the upstream source.