Claude Skills by ssrjkk

Tailwind CSS v4 features

Apply TypeScript for type-safe JavaScript: type design, generics, utility types, strict mode, and integration with modern tooling. Use for any JS codebase.

Build reactive user interfaces with Vue 3: Composition API, reactivity, components, state, and tooling. Use for any Vue-based UI work.

Expo SDK for React Native development

Build cross-platform mobile apps with Flutter: widgets, state management, navigation, platform channels, and release builds. Use for iOS/Android/desktop.

Automate browsers with Playwright: selectors, waits, assertions, screenshots, network interception, and CI. Use for E2E tests and scraping.

Write reliable Python tests with pytest: fixtures, parametrize, mocking, async tests, and CI integration. Use for any Python testing.

Implements OAuth 2.0 authentication and JWT-based authorization with refresh tokens. Use for secure API access.

Harden web applications against the OWASP Top 10: injection, XSS, auth flaws, CSRF, SSRF, and insecure dependencies. Use for any web app security review.

Design effective prompts for LLMs: role framing, structured output, chain-of-thought, few-shot, and evaluation. Use to get reliable model behavior.

AI-powered test generation and validation

Build algorithmic trading systems: backtesting, strategy design, order execution, risk management, and market data pipelines. Use for quantitative finance.

Build financial risk models: VaR, CVaR, Monte Carlo simulation, stress testing, and portfolio risk decomposition. Use for quantitative risk management.

Implement 2D/3D game physics: rigid bodies, collisions, constraints, raycasting, and performance optimization. Use for realistic game mechanics.

Build scalable Unity games with Entity Component System (ECS): systems, queries, jobs, burst compilation, and DOTS patterns. Use for high-performance Unity.

Implement HIPAA compliance in healthcare software: PHI protection, access controls, audit logging, encryption, and breach notification. Use for health IT security.

Build healthcare integrations with HL7 FHIR: resources, operations, SMART on FHIR apps, and clinical data exchange. Use for health IT interoperability.

Build reliable LLM agents and agentic workflows: tool use, memory, loops, guardrails, and evaluation. Use for autonomous AI systems.

Curate LLM context windows for quality and cost: system prompts, compaction, just-in-time retrieval, progressive disclosure, and token budgets. Use for effective agent context.

Work with text embeddings: model selection, vectorization, similarity, clustering, and caching for search and retrieval. Use for semantic representation of text.

Designs and curates few-shot examples to guide LLM behavior, including example selection, formatting, and ordering. Use for task specification without fine-tuning.

Implement robust LLM function/tool calling: schemas, multi-call handling, validation, error recovery, and structured execution. Use for agent tool use.

Build evaluation suites for LLM applications: golden datasets, metrics, LLM-as-judge, regression gates, and CI integration. Use for trustworthy model behavior.

Fine-tunes open-source LLMs (Llama, Mistral, Qwen) using LoRA/QLoRA with HuggingFace and Unsloth. Use for domain-specific model adaptation.

Add safety guardrails to LLM apps: prompt injection defense, content filtering, PII protection, policy enforcement, and red-teaming. Use for safe production AI.

Build Model Context Protocol servers and clients: tools, resources, prompts, transport, and secure agent integration. Use for connecting agents to external systems.

Operate machine learning in production: experiment tracking, pipelines, model registry, serving, monitoring, and CI/CD for ML. Use for ML lifecycle.

Design and run multi-agent systems: orchestrator-worker, routing, handoffs, shared state, and coordination patterns. Use for complex agent teams.

Optimize LLM cost and latency with prompt caching: cacheable prefixes, cache-control headers, context layout, and cache-aware prompting. Use for high-volume apps.

Build retrieval-augmented generation pipelines: chunking, embeddings, vector search, hybrid retrieval, and citation. Use for grounded LLM answers over your data.

Force LLMs to emit valid, schema-constrained structured output: JSON modes, function calling, JSON Schema validation, and error recovery. Use for reliable data extraction.

Deno runtime and standard library

Build secure web applications with Django: models, views, ORM, admin, auth, REST APIs, and deployment. Use for Python web backends.

Build .NET backends with ASP.NET Core: minimal APIs, EF Core, dependency injection, middleware, and testing. Use for C# services.

Build Node.js web APIs with Express: routing, middleware, error handling, validation, and production hardening. Use for Node backends.

Build high-performance Python APIs with FastAPI: routing, Pydantic validation, async, dependency injection, OpenAPI, and testing. Use for any Python backend.

Build production REST APIs in Go with the standard library or Gin, including routing, middleware, JSON handling, and testing. Use for performant backends.

Design and implement GraphQL APIs: schemas, resolvers, queries, mutations, subscriptions, and N+1 avoidance. Use for flexible client-driven APIs.

Build high-performance services with gRPC: protobuf schemas, unary/streaming RPCs, interceptors, and error handling. Use for inter-service communication.

Build PHP web applications with Laravel: routing, Eloquent ORM, Blade, migrations, validation, and deployment. Use for PHP backends.

Creates Node.js server-side applications with NestJS, modules, dependency injection, and decorators. Use for enterprise-grade Node.js APIs.

Design consistent REST APIs: resource modeling, status codes, pagination, versioning, error contracts, and documentation. Use for any API design task.

Async Rust with Tokio runtime

Build production Java/Kotlin backends with Spring Boot: REST controllers, dependency injection, data access, security, and testing. Use for JVM services.

Build real-time features with WebSockets: connection lifecycle, protocols, backpressure, scaling, and reconnection. Use for live updates and chat.

Zero-knowledge proof development

Orchestrate data pipelines with Apache Airflow: DAGs, tasks, dependencies, sensors, and retries. Use for scheduled workflows.

Process large-scale data with Apache Spark: DataFrames, SQL, joins, partitioning, and optimization. Use for big data and ETL.

Create clear data visualizations with Matplotlib, Plotly, and Altair: chart selection, design, interactivity, and dashboards. Use for communicating data.

Build analytics engineering workflows with dbt: models, tests, sources, macros, and documentation. Use for transform-layer data pipelines.