adversarial-spec
Iteratively refine a product spec by debating with multiple LLMs (GPT, Gemini, Grok, etc.) until all models agree. Use when user wants to write or refine a specification document using adversarial development.
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Iteratively refine a product spec by debating with multiple LLMs (GPT, Gemini, Grok, etc.) until all models agree. Use when user wants to write or refine a specification document using adversarial development.
21 production-ready scripts for iOS app testing, building, and automation. Provides semantic UI navigation, build automation, accessibility testing, and simulator lifecycle management. Optimized for AI agents w...
WooCommerce REST API - products, orders, customers, webhooks
AWS Aurora Serverless v2, RDS Proxy, Data API, connection pooling
Multi-person projects - shared state, todo claiming, handoffs
Web UI - glassmorphism, Tailwind, dark mode, accessibility
User experience flows - journey mapping, UX validation, error recovery
Firebase Firestore, Auth, Storage, real-time listeners, security rules
Shopify app development - Remix, Admin API, checkout extensions
Google Gemini CLI code review with Gemini 2.5 Pro, 1M token context, CI/CD integration
Latest AI models reference - Claude, OpenAI, Gemini, Eleven Labs, Replicate
Mandatory code reviews via /code-review before commits and deploys
Express/Hono with Supabase and Drizzle ORM
SEO and AI discovery (GEO) - schema, ChatGPT/Perplexity optimization
AI-first application patterns, LLM testing, prompt management
Atomic commits, PR size limits, commit thresholds, stacked PRs
Centralized API key management from Access.txt
Python development with ruff, mypy, pytest - TDD and type safety
Reddit API with PRAW (Python) and Snoowrap (Node.js)
Medusa headless commerce - modules, workflows, API routes, admin UI
Schema awareness - read before coding, type generation, prevent column errors
Technical SEO - robots.txt, sitemap, meta tags, Core Web Vitals
Next.js with Supabase and Drizzle ORM
Analyze existing repositories, maintain structure, setup guardrails and best practices
Le classement utilise les étoiles du dépôt GitHub indexé. Plusieurs skills peuvent partager ce nombre : ce n’est ni un nombre d’installations ni une note de qualité.