baoyu-image-gen_skill

Overview

This skill provides CLI-driven image generation using official OpenAI and Google APIs via an AI SDK. It supports text-to-image, reference-image editing, aspect ratios, size presets, and quality levels for quick, reproducible image outputs. The tool auto-selects provider based on available keys but allows explicit provider and model selection.

How this skill works

Scripts in the scripts/ directory expose a main CLI that accepts prompt text, prompt files, reference images, output path, and generation options. The CLI picks a provider (OpenAI or Google) based on flags and available API keys, maps quality/aspect settings to provider parameters, calls the respective SDK image endpoints, saves images, and can print JSON metadata. It retries once on failure and warns/ignores incompatible options like references with image-only models.

When to use it

• Generate single or batch images from plain prompts or prompt files.
• Create variants with specific aspect ratios or exact sizes for cover art, banners, and social posts.
• Produce higher-resolution outputs (2k) for presentations or infographics.
• Edit images using reference files when using Google multimodal models.
• Integrate image generation into agent workflows where OpenAI or Google APIs are available.

Best practices

• Prepare prompts in dedicated files for complex or repeatable scenes and pass them with --promptfiles for consistency.
• Specify --image to set the exact output path; use --json for machine-readable results in pipelines.
• Pick quality presets: use normal for quick iterations and 2k for final assets requiring more detail.
• When both API keys exist, set --provider explicitly if you need a specific model behavior.
• Provide --ref only when using Google multimodal models; the CLI will warn and ignore refs for image-only models.

Example use cases

• Generate a 2.35:1 cover image for an article with --ar 2.35:1 and --quality 2k.
• Create square social media images with --ar 1:1 for Instagram posts.
• Edit a photo by supplying --ref original.png and a targeted prompt with --provider google.
• Batch-produce illustrated scenes by supplying multiple prompt files via --promptfiles.
• Run CI tasks that emit JSON metadata by adding --json for automated asset ingestion.