Skill UI

A comprehensive guide detailing five robust architectural patterns for building applications powered by Claude, including Chatbot, RAG, Agent, Content Pipeline, and Evaluation. It provides complete code examples and decision matrices to help developers select the optimal architecture based on project requirements, cost, and complexity.

This comprehensive guide presents three validated architectural blueprints for integrating Adobe services (Firefly, PDF, etc.). It helps developers decide between simple direct SDK integration (suitable for MVPs), native Adobe App Builder (serverless functions), or robust, high-throughput dedicated microservices, based on team size, complexity, and required scalability.

A comprehensive guide for startups to maximize Return on Investment (ROI) by optimizing operational costs and leveraging R&D tax credits. This skill covers strategies for improving bookkeeping efficiency, structuring employment (W-2 vs. contractor), selecting the optimal financial plan, and minimizing overall accounting complexity using Fondo's tools.

idea-os is a comprehensive, five-phase pipeline designed to transform a raw, abstract idea into a fully structured, build-ready plan. It guides users through Triage, Clarification, Deep Research, detailed PRD creation (including non-goals and metrics), and finally, a phased execution plan. The system adapts its complexity and vocabulary to the user's sophistication level, providing everything from foundational market analysis to actionable technical stack recommendations.

This guide provides comprehensive methods for building robust change detection and event handling within Notion workspaces. It compares the reliability, complexity, and latency of three approaches: polling using last_edited_time, utilizing native webhooks, and using third-party connectors. Learn how to implement reliable, incremental synchronization, change feeds, and event-driven workflows using the Notion API to ensure data consistency and near real-time updates.

This guide helps users select and implement the optimal architecture pattern for Salesforce integrations. It compares three main approaches: simple Direct API polling, highly scalable Event-Driven using Change Data Capture (CDC), and complex Enterprise Middleware/iPaaS solutions. Use this when designing new integrations, planning data migration, or determining the best sync method based on data volume, latency, and complexity requirements.

This skill provides systematic frameworks for tackling complex marketing challenges. It helps overcome creative blocks, reduce campaign complexity, identify root causes of recurring failures, and challenge limiting industry assumptions through advanced methods like collision thinking and inversion exercises. Ideal for strategic planning and optimization.

This skill automatically routes subtasks to the most cost-effective Claude model (Haiku, Sonnet, or Opus) based on complexity. It logs real token usage and cost per session, and includes an A/B testing feature to validate model tier savings against your actual workload, ensuring accurate cost control.

A structured playbook for improving the time and space complexity (Big-O) of existing, slow code. This skill guides developers through systematic refactoring, focusing on identifying bottlenecks like nested loops or N+1 queries. It emphasizes applying transformations one at a time, maintaining test coverage, and measuring performance gains to ensure correct and efficient code.

This skill enforces an algorithm-first discipline, requiring the user to state the time and space complexity (Big-O), the intended data structure, and the core algorithm family before writing any complex code (loops, queries, recursion). It serves as a critical gatekeeper to prevent common performance pitfalls like O(n²) complexity, N+1 database queries, and brute-force implementation errors, significantly improving code robustness and efficiency.

A specialized skill for achieving asymptotic performance gains when classical algorithms are already near optimal. It leverages advanced mathematical techniques and probabilistic data structures (e.g., Bloom Filters, HyperLogLog, FFT, MinHash/LSH) to handle massive datasets (n ≥ 10⁶) by accepting bounded approximations or exploiting deep structural properties. Requires strict adherence to error parameter and complexity justification protocols.

A critical discipline for managing expenses when integrating paid AI or inference APIs. This guard treats dollar cost as a third complexity dimension, mandating the definition of cost contracts (max calls per run, max budget per run, max budget per day). It enforces best practices for bounding loops, retries, and fan-out, ensuring that code bugs cannot lead to unexpected overspending. Best practice requires configuring hard caps both in the code and at the provider dashboard for defense in depth.