Produce a comprehensive technical blueprint for a web product or SaaS, suitable for implementation in Figma Make, engineering sprints, and cloud deployment.
The English summary is being prepared. Showing the original description.
Review the instructions the agent will receive before you install.
Produce a comprehensive technical blueprint for a web product or SaaS, suitable for implementation in Figma Make, engineering sprints, and cloud deployment.
/enterprise-design <product or feature> — full blueprint/enterprise-design ia — information architecture + sitemap only/enterprise-design api — API surface definition only/enterprise-design data — data architecture + entity model only/enterprise-design ux — user journeys + component inventory only/enterprise-design stack — tech stack recommendation only/enterprise-design review — audit current project against enterprise standardsPROJECT_ROOT=$(git rev-parse --show-toplevel)
INSTRUCTION_FILE=$(for f in CLAUDE.md AGENTS.md .cursorrules; do [ -f "$PROJECT_ROOT/$f" ] && echo "$PROJECT_ROOT/$f" && break; done)
[ -n "$INSTRUCTION_FILE" ] && head -100 "$INSTRUCTION_FILE"
Establish: site/product type, primary audience, core capabilities (3–5), technical priorities.
Produce a structured technical blueprint covering:
Complete sitemap with primary, secondary, semantic, and neutral path hierarchy. URL conventions (kebab-case, hierarchy reflects ownership, pagination via query params).
Three critical conversion paths: acquisition→activation, free→paid, core workflow loop. Include drop-off points and success metrics.
Entity relationships and schema models. Indexing strategy (FK indexes, composite for pagination, GIN for full-text). Caching tier (Redis key patterns + TTLs). Analytics tier (event schema for BigQuery).
Core REST endpoints (auth, primary entity CRUD, billing, admin). Standard response envelope. Third-party integrations table. Rate limiting per tier.
Layout, navigation, data display, form, feedback, and feature-specific components. For each: purpose + key props.
Structural wireframe descriptions for: landing page, dashboard, detail/entity view, settings page.
Recommended stack with rationale for: frontend, styling, state, backend, database, cache, auth, payments, email, hosting, CI/CD, observability, IaC.
Core Web Vitals targets (LCP < 1.8s, INP < 100ms, CLS < 0.05). API latency targets (P50/P95). Performance budget per page.
URL conventions, meta structure per page type, schema markup strategy, Core Web Vitals for SEO.
Domain-Driven Design bounded contexts, API governance, zero-trust security, multi-region DR. Only include if product is at scale (> 10K users / multi-team / regulated).
Structured specification with clear headings, bullet points, and numbered lists throughout. Suitable for direct handoff to Figma Make or engineering sprint planning.
No reviews yet. Tell others what you thought.
No login needed. Share how it worked for you, ask a question, or note where it did not run.
No comments yet. Be the first to write one.
Act as a Senior Accessibility Engineer to audit a page, component, or design against WCAG 2.2 AA. Produces a triaged finding list (critical/serious/moderate), focus-order map, contrast report, ARIA decision tree, and a screen-reader test plan. Use when shipping new UI, hardening an existing flow, or preparing for VPAT/accessibility conformance.
The English summary is being prepared. Showing the original description.
When the user wants to plan, design, or implement an A/B test or experiment — "split test," "variant copy," "multivariate test," "hypothesis," "statistical significance," "how long should I run this test," or comparing two versions. For tracking implementation, see analytics-tracking. For page-level conversion optimization, see page-cro.
The English summary is being prepared. Showing the original description.
When the user wants to generate, iterate, or scale ad creative — headlines, descriptions, primary text, full variations — for any paid platform; 'ad copy variations,' 'RSA headlines,' 'bulk ad copy,' 'creative testing,' 'write me some ads.' For campaign strategy and targeting, see paid-ads. For landing page copy, see copywriting.
The English summary is being prepared. Showing the original description.
When the user wants content cited by LLMs or surfaced in AI-generated answers — 'AI SEO,' 'AEO,' 'GEO,' 'LLMO,' 'answer engine optimization,' 'AI Overviews,' 'optimize for ChatGPT/Perplexity/Claude,' 'AI citations,' 'zero-click search.' For traditional technical/on-page audits, see seo-audit. For structured data, see schema-markup.
The English summary is being prepared. Showing the original description.
When the user wants to set up, improve, or audit analytics tracking and measurement — "GA4," "conversion tracking," "event tracking," "UTM parameters," "tag manager," "GTM," "tracking plan," "attribution," "Mixpanel," "Segment," "are my events firing," or how to measure marketing results. For A/B test measurement, see ab-test-setup.
The English summary is being prepared. Showing the original description.
Architectural decision advisor for cloud, data, and SaaS distributed systems. Use when the user asks "should we use X or Y", weighs a tradeoff, or needs a decision matrix, scaling analysis, cost-at-scale review, data-tier design, multi-tenancy model, or API/resilience guidance. For full technical blueprints, use enterprise-design.
The English summary is being prepared. Showing the original description.