MCP server + CLI for production-grade software assets (logos, app icons, favicons, OG, illustrations) — routes across 30+ image models, zero-key first, validates before shipping.
openbooklet.com/s/prompt-to-assetopenbooklet.com/s/[email protected]GET /api/v1/skills/prompt-to-assetGenerate an app icon from a single 1024² master and fan out to iOS (AppIcon.appiconset with squircle-ready 1024 opaque), Android (adaptive foreground + background + Android 13 monochrome), PWA (192/512 + 512 maskable with 80% safe zone), and visionOS (3-layer parallax).
Classify a software-asset brief (logo, app icon, favicon, OG image, illustration, splash, icon pack, transparent mark), route to the right image model, rewrite the prompt in the target model's dialect, pick an execution mode (inline_svg / external_prompt_only / api) based on what's actually available, and run the pipeline. Use whenever the user asks for any visual asset for a software product.
Diagnose and repair asset-generation failures. Maps tier-0/1/2 validation codes (checkerboard, missing alpha, safe-zone violation, palette drift, garbled wordmark, low contrast) to concrete repair primitives (matte, inpaint, route change, seed sweep, composite). Applies a retry budget so Claude does not loop on hopeless regenerations.
Engaged when a user is generating more than one asset for the same brand, or when an existing `brand.json` / `brand.md` is in play. Wraps `asset_brand_bundle_parse`, `asset_generate_*`, and validation.
Generate a production-grade logo (primary brand mark). Returns RGBA PNG master + SVG vector + monochrome variant. Route by text-length and per-model ceiling. Strong-text models render multi-word and even paragraph-length wordmarks reliably; weak-text models composite SVG type post-render.
Engaged when `asset_generate_*` returns an `InlineSvgPlan`. Read `svg_brief` (viewBox, palette, path_budget, require[], do_not[], skeleton) and emit one `<svg>â¦</svg>` code block that honors every constraint. Then call `asset_save_inline_svg({ svg, asset_type })` so the file lands on disk.
Rewrite an asset brief into the exact prompt dialect of the target image model (OpenAI gpt-image-1, Google Imagen/Gemini, SDXL, Flux.1/Flux.2, Midjourney, Ideogram, Recraft). Handles negative-prompt translation, token budgets, transparency quirks, brand-palette injection, and text-in-image ceilings so that `asset_generate_*` submissions succeed on the first try.
Produce a truly RGBA-transparent asset from a brief. Handles the
This skill turns a UI brief into a single paste-ready prompt for a strong-text image model (gpt-image-2, Nano Banana Pro, Ideogram 3 Turbo, Flux 2 Pro, Midjourney v7) that produces designer-quality mockups for **inspiration**, not pixel-exact production UI.
Auto-indexed from MohamedAbdallah-14/prompt-to-asset
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