p5.js sketches: gen art, shaders, interactive, 3D.
Master graphic-design knowledge for producing real visual assets with AI image models — blog and article covers, hero images, social and OG cards, ad creative, banners, icons, spot illustrations, and brand visuals. Use whenever someone asks you to design, create, generate, or art-direct an image, illustration, cover, banner, logo concept, or a coherent set of visuals; or when they hand you content (a post, a launch, a campaign) to illustrate. Covers composition, color, typography, brand identity, format/aspect specs, design critique, and — critically — how to write prompts and use reference images for the gpt-image and Gemini (Nano Banana) image toolkits so the output looks intentionally designed, not generically AI. Triggers: 'design a cover', 'make a banner', 'generate an illustration', 'create social cards', 'art direction', 'image prompt', 'on-brand visuals', 'a matching set of images'.
The unified visual generator — turn a brief into rendered high-res PNG/PDF graphics across seven fixed formats (carousel, story, infographic, slides, poster, chart, tweet). Resolve a style from a 16-style catalog, extract an ad-hoc style from a reference image, or synthesize a brand style from hex colors + fonts; source imagery (Unsplash or keyless) and ASCII art; the agent authors the HTML content while a deterministic driver binds design tokens to templates, runs a WCAG contrast check, and a Playwright renderer screenshots single files or whole slide directories at deviceScaleFactor 2. Use for any "make me a graphic / carousel / slides / poster / infographic / story" request and as the visual arm of social-kit.
Extract the highest-converting ad angles from real customer-voice data — reviews, Reddit threads, social complaints, and competitor ads — and return a ranked angle bank with verbatim proof quotes and recommended ad formats. For growth/paid-media teams who want ad copy grounded in evidence, not brainstorms.
Turn raw ad-campaign performance data (Google, Meta, LinkedIn) into clear cut/scale/test decisions — diagnose waste, identify winners, check statistical significance, and produce a concrete cross-channel budget-reallocation plan with scenario modeling and dollar-amount shifts. For founders/paid-media owners who need a specialist's read, not a dashboard summary.
Audit message match between each ad and its landing page — does the ad's promise carry through to the LP headline, body, and CTA? — and flag every disconnect plus conversion friction that kills click-to-convert rates. For teams getting ad clicks but few conversions.
Keep a brand's AI answer-engine visibility under continuous watch — on a recurring schedule re-run the AEO visibility check across Perplexity/ChatGPT/Gemini over a frozen prompt set, persist each run, diff against history, and alert the team only when mention rate, prominence, or share-of-voice materially moves (a competitor overtakes you, an engine drops you, a new citation source appears). The recurring wrapper around aeo-visibility. Requires one answer-engine key (Perplexity canonical); durable history defaults to a local JSONL ledger, with Supabase as an optional upgrade.
Measure a brand's visibility across AI answer engines (Perplexity, ChatGPT/OpenAI, Gemini, Tavily) — how often and how prominently it is mentioned, and where competitors get cited instead — then audit the site's AI-readability and produce prioritized recommendations. Use for a one-shot AEO baseline ("how visible are we in ChatGPT/Perplexity?", "audit our site for AI search"). Requires at least one answer-engine API key (Perplexity is canonical).