Turn one product brief into three distinct storefront-cover directions with GPT Image 2: consistent brand colors, readable hierarchy, configurable size and quality, and local PNG output you can inspect.
The current Agensi buyer download and public listing use GPT Image 2. Version 1.2 includes the 1280×720 storefront default, supported custom sizes, quality controls, actionable API errors, and no-partial-set output described below.
Provide a product name and description, then optionally add a price, brand colors, style, canvas size, and quality. The workflow makes three separate GPT Image 2 requests so the result is a useful choice among directions, not three renamed copies of one image.
The default is three 1280×720 PNGs, matching Gumroad's current recommended cover dimensions. For a square store thumbnail, request 1024x1024. GPT Image 2 also accepts auto and flexible sizes within its published limits, and the script validates those limits before spending an API request.
Output files are named {product_slug}_cover_1.png through _3.png and saved to generated-covers/ unless you choose another directory.
low, medium, high, or auto quality.You need Python, an OPENAI_API_KEY for a project with GPT Image 2 access, outbound network access to api.openai.com, and permission to write the chosen local output directory. The workflow does not require browser access and does not upload the saved cover files to a storefront.
The $15 skill purchase and OpenAI API usage are separate charges. Quality and size affect generation cost and latency; start with medium for finished covers or low for cheaper exploratory runs.
Generated typography can still contain spelling or layout errors, and a plausible mock interface is not evidence that the depicted feature exists. Review every cover at full size and thumbnail size. Check the product name, price, logo use, claims, contrast, crop, and any trademarked material before publishing.
The workflow creates new images; it is not a layered design-file editor, template marketplace, background remover, or automatic Gumroad/Lemon Squeezy uploader.
Generate three distinct digital-product covers with GPT Image 2 from a product brief and brand colors. Use a 1280x720 storefront-cover default, square or custom sizes, three style templates, configurable quality, and no partial output set after a failed run.
Generate three distinct digital-product covers with GPT Image 2 from a product brief and brand colors. Use a 1280x720 storefront-cover default, square or custom sizes, three style templates, configurable quality,….
Do not treat a successful run as proof beyond the supplied files, declared scope, and evidence the skill actually checked.
It generates three distinct PNG cover options from one product brief. Each option uses a different composition while preserving the requested style and brand colors.
Version 1.2 uses GPT Image 2 by default. It does not silently fall back to deprecated image models.
The default is 1280 by 720 pixels. You can request 1024 by 1024 for square thumbnails, auto sizing, or another size that satisfies GPT Image 2 constraints.
It needs Python, outbound network access to the OpenAI Images API, the OPENAI_API_KEY environment variable, and write access to the chosen local output directory. It does not need browser access.
No. The skill purchase and OpenAI API billing are separate. You supply an API key for a project with GPT Image 2 access.
The run reports the relevant authentication, access, safety, rate-limit, API, or network problem and leaves no partial cover set behind.
Version 1.2 is live on Agensi for $15 or 75 credits. Review the displayed permissions and refund terms before buying; OpenAI API usage is separate.
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