120건 · 관련도순
Recommend architecture patterns (monolith, microservices, serverless, modular monolith) based on scale, team size, and constraints. Use when cto-architect needs to select the right architectural approach for a new system or migration.
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Reviews an existing codebase for structural friction, unclear ownership, leaky or shallow interfaces, excessive coupling, misplaced state, poor testability, and risky dependency direction, then prioritizes evidence-backed improvement candidates. Use for architecture audits, modularization, modernization, or recurring cross-cutting change pain. Not for designing one new interface, simplifying a local function, or fixing a reproduced bug.
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Conjecture generation, sequence analysis, and experimental mathematics for mathematical discovery. Covers sequence analysis (OEIS lookups, recurrence relations, generating functions), pattern detection methods (finite differences, ratio analysis, modular patterns), conjecture generation workflow, classical integer sequences (Fibonacci, Catalan, partition numbers, Bernoulli numbers), combinatorial identities, the probabilistic method (Erdos, expected value arguments, Lovasz Local Lemma), AI-assisted discovery (FunSearch, Ramanujan Machine), and confidence calibration with cautionary tales (Mertens conjecture, Polya conjecture). Use when discovering patterns, analyzing sequences, generating conjectures, or working with combinatorial identities.
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Advanced Zephyr RTOS kernel services. Covers inter-thread communication using Zbus (pub/sub), behavioral management with the State Machine Framework (SMF), background processing via work queues, and persistent configuration with the Settings subsystem. Trigger when building modular application architectures, complex state-driven logic, or requiring persistent data storage.
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Converts a Stitch screen, a local HTML file, or a URL into modular Vite + React components — TypeScript, theme-mapped Tailwind, dark mode via CSS variables, and clean component architecture. Use this for Vite/React apps without App Router. For Next.js 15 App Router, use stitch-nextjs-components instead. Only the Stitch route needs an API key.
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Solve Diophantine equations (integer-only solutions) including linear, quadratic, and Pell equations. Covers the extended Euclidean algorithm, descent methods, and existence proofs. Use when finding all integer solutions to ax + by = c, solving Pell's equation, generating Pythagorean triples, proving no integer solutions exist via modular constraints, or finding the fundamental solution from which all others are generated.
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Medusa v2 rules and best practices for modular commerce architecture, Workflow SDK, data models, services, and admin customizations.
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Use when a slice shows duplicate helpers, fake modularization, oversized-file pressure, or AI-shaped code slop that needs explicit cleanup discipline.
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A template for creating new modular and scalable agent skills.
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"Implement Louvain community detection to discover densely connected groups in networks. Use this skill when the user needs to find communities or clusters in social/organizational networks, segment customers by interaction patterns, or analyze network modular structure — even if they say 'find groups in this network', 'community detection', or 'network clustering'.".
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Spring Modulith 2.0 implementation for bounded contexts in Spring Boot 4. Use when structuring application modules, implementing @ApplicationModuleListener for event-driven communication, testing with Scenario API, enforcing module boundaries, externalizing events to Kafka/AMQP, building a modular monolith, defining module dependencies, managing inter-module events, or organizing DDD modules as packages. Covers package-based module boundaries, named interfaces, event publication, and Scenario API testing. For architecture decisions, see domain-driven-design skill.
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Dark-themed cloud-platform aesthetic with modular grids, glass-like panels, and strong data hierarchy for productivity dashboards.
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Modular grid layout with card-like blocks, clear hierarchy, soft spacing, and subtle visual contrast for organized, scannable interfaces.
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Generates performance-focused guidance for Google Cloud workloads based on the design principles and recommendations in the Performance Optimization pillar of the Google Cloud Well-Architected Framework (WAF). Use this skill to evaluate a workload, identify performance requirements, and provide actionable recommendations for resource allocation, modular design, and elasticity.
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Quando o usuário quer criar páginas de comparação com concorrentes ou alternativas para SEO e ativação de vendas. Use também quando o usuário menciona 'página de alternativas', 'página vs', 'comparação com concorrentes', 'página de comparação', '[Produto] vs [Produto]', '[Produto] alternativa', ou 'landing pages competitivas'. Cobre quatro formatos: alternativa singular, alternativas plurais, você vs concorrente, e concorrente vs concorrente. Enfatiza pesquisa profunda, arquitetura de conteúdo modular e tipos de seção variados além de tabelas de recursos.
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Build editorial/magazine/report webpages on a GENUINE Müller-Brockmann modular grid (International Typographic Style). Encodes the discipline (columns + modules + baseline, grotesque type, flush-left, restrained black/white/red palette) AND the front-end engineering to make the grid real, visible, and verified: one CSS-variable source of truth, an interactive grid-toggle overlay, subgrid bands, 8px baseline lock, and runtime optical alignment. Triggers: "magazine spread", "grid system", "Swiss design", "editorial layout", "show the grid", "align everything to the grid".
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Bootstrap a new Gradle module in any Kotlin Android project. Walks the user through choosing one of three module types — library module (`com.android.library`), feature module (regular Android library that hosts a feature/UI, install-time only), or dynamic feature module (`com.android.dynamic-feature`, on-demand/conditional/instant delivery). Use whenever the user wants to add a module, modularize code, extract a util/data/ui layer, create a new feature, set up Play Feature Delivery, or asks "should this be a library or feature module?". Discovers the project's existing conventions (plugin aliases, namespaces, sibling modules, version catalog) instead of hardcoding any. Pushes back on bad combos (e.g. utility code in a dynamic feature). Stops at scaffolding; app-level wiring is out of scope.
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When the user wants to create competitor comparison or alternative pages for SEO and sales enablement. Also use when the user mentions 'alternative page,' 'vs page,' 'competitor comparison,' 'comparison page,' '[Product] vs [Product],' '[Product] alternative,' or 'competitive landing pages.' Covers four formats: singular alternative, plural alternatives, you vs competitor, and competitor vs competitor. Emphasizes deep research, modular content architecture, and varied section types beyond feature tables.
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Predicts whether a DNA variant alters mRNA splicing using sequence-based deep-learning tools — SpliceAI (10kb context dilated CNN, clinical default), Pangolin (multi-tissue), MMSplice (modular per-region CNN with calibrated ΔPSI), SpliceTransformer/TrASPr (tissue-aware transformers), SpliceVault (empirical 300K-RNA lookup of likely mis-splicing outcomes), CADD-Splice (composite score). Applies the ClinGen SVI 2023 framework for ACMG/AMP variant interpretation (PVS1, PP3, BP4 evidence codes), HGVS splicing nomenclature (c.123+1G>A, c.123-3T>G, r.spl?), extended-window scoring for deep-intronic pseudoexons, tissue-specific predictions, branchpoint variant detection (BPHunter, LaBranchoR), and splice-switching ASO design. Use when interpreting splice impact of clinical variants, prioritizing VUS, identifying deep-intronic pathogenic variants, or designing ASOs.
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Build complex AI systems with declarative programming, optimize prompts automatically, create modular RAG systems and agents with DSPy - Stanford NLP's framework for systematic LM programming
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Plan which model tier handles which work BEFORE execution begins — a high-cognition model deeply understands the problem, lays the foundations, then emits a modular plan assigning each module the cheapest tier that can safely execute it, with escalation tripwires and one-way-door protection. Advisory only: it announces "next module → tier X / model Y" at each boundary and the HUMAN switches models — harnesses like Cursor cannot switch mid-run. Load when the user asks which model to use, wants a model plan, model tiers, model-tier routing, assign models to tasks or modules, says "cheap model got stuck", "which model for this task", "cost-efficient model choice", or when implementation-plan / problem-to-plan need a model: tier column. NOT dynamic-routing (plan-path selection after failure) — this skill assigns cognition tiers to work.
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Predicts whether a DNA variant alters mRNA splicing using sequence-based deep-learning tools — SpliceAI (10kb context dilated CNN, clinical default), Pangolin (multi-tissue), MMSplice (modular per-region CNN with calibrated ΔPSI), SpliceTransformer/TrASPr (tissue-aware transformers), SpliceVault (empirical 300K-RNA lookup of likely mis-splicing outcomes), CADD-Splice (composite score). Applies the ClinGen SVI 2023 framework for ACMG/AMP variant interpretation (PVS1, PP3, BP4 evidence codes), HGVS splicing nomenclature (c.123+1G>A, c.123-3T>G, r.spl?), extended-window scoring for deep-intronic pseudoexons, tissue-specific predictions, branchpoint variant detection (BPHunter, LaBranchoR), and splice-switching ASO design. Use when interpreting splice impact of clinical variants, prioritizing VUS, identifying deep-intronic pathogenic variants, or designing ASOs.
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Implements lightweight state management using Zustand with TypeScript, persistence, devtools, and modular store patterns. Use when users request "zustand store", "state management", "global state", "zustand setup", or "jotai alternative".
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v3.0 — Refactored 2026-05-02 from a 4,168-line monolith into a lean SKILL.md (~400 lines) plus 15 modular reference files in references/. Detail content loads on demand — Claude reads only the reference files relevant to the current task.
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