「best practices」の検索結果

Pythonic idioms, PEP 8 standards, type hints, and best practices for building robust, efficient, and maintainable Python applications.

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PostgreSQL database patterns for query optimization, schema design, indexing, and security. Based on Supabase best practices.

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Backend architecture patterns, API design, database optimization, and server-side best practices for Node.js, Express, and Next.js API routes.

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Django security best practices, authentication, authorization, CSRF protection, SQL injection prevention, XSS prevention, and secure deployment configurations.

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Database migration best practices for schema changes, data migrations, rollbacks, and zero-downtime deployments across PostgreSQL, MySQL, and common ORMs (Prisma, Drizzle, Kysely, Django, TypeORM, golang-migrate).

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Django architecture patterns, REST API design with DRF, ORM best practices, caching, signals, middleware, and production-grade Django apps.

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ClickHouse database patterns, query optimization, analytics, and data engineering best practices for high-performance analytical workloads.

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Universal coding standards, best practices, and patterns for TypeScript, JavaScript, React, and Node.js development.

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Entity Framework Core best practices including NoTracking by default, query splitting for navigation collections, migration management, dedicated migration services, and common pitfalls to avoid.

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Comprehensive web quality audit covering performance, accessibility, SEO, and best practices. Use when asked to "audit my site", "review web quality", "run lighthouse audit", "check page quality", or "optimize my website".

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Comprehensive AI/ML development guide for LangChain, LangGraph, and ML model integration in FastAPI. Use when building LLM applications, agents, RAG systems, sentiment analysis, aspect-based analysis, chain orchestration, prompt engineering, vector stores, embeddings, or integrating ML models with FastAPI endpoints. Covers LangChain patterns, LangGraph state machines, model deployment, API integration, streaming, error handling, and best practices.

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Step-by-step checklist and best practices for implementing new AI agent tools in the omer-akben portfolio. Use when creating new agent tools, API routes, or extending agent capabilities.

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AI content generation with OpenAI and Claude, callAIWithPrompt usage, prompt storage in app_settings, structured outputs, response format validation, multi-criteria scoring, rate limiting, JSON schema, and AI API best practices. Use when generating content, creating prompts, scoring articles, or working with OpenAI/Claude APIs.

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Patterns for multi-agent coordination, task decomposition, handoffs, and workflow orchestration. Best practices for building and managing agent systems.

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Dependency management guidelines for Jarvy - crate selection criteria, feature flag best practices, version management, security auditing with cargo-audit and cargo-deny.

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Security best practices and guidelines for the Jarvy CLI codebase - a cross-platform development environment provisioning tool that executes system commands with elevated privileges

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Tools are how AI agents interact with the world. A well-designed tool is the difference between an agent that works and one that hallucinates, fails silently, or costs 10x more tokens than necessary. This skill covers tool design from schema to error handling. JSON Schema best practices, description writing that actually helps the LLM, validation, and the emerging MCP standard that's becoming the lingua franca for AI tools. Key insight: Tool descriptions are more important than tool implementa

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Comprehensive templates, patterns, and best practices for creating Claude Code subagents and skills. Use when building new agents/skills or need reference examples for proper structure and formatting.

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Create and manage AI agent skills following best practices. Use when creating new skills, optimizing context, designing multi-agent systems, or implementing progressive disclosure patterns.

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Creates new agent skills following modern best practices with proper structure and documentation. Use when asked to build a new skill, organize skill resources, design skill descriptions, or validate skill structure for portability across Copilot platforms.

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Create, use, and manage Agent Skills for Claude. Use when working with Skills, creating custom capabilities, or understanding how Skills extend Claude's functionality. Covers Skill architecture, file structure, and best practices.

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Elite AI context engineering specialist mastering dynamic context management, vector databases, knowledge graphs, and intelligent memory systems. Orchestrates context across multi-agent workflows, enterprise AI systems, and long-running projects with 2024/2025 best practices. Use PROACTIVELY for complex AI orchestration. Use when: the task directly matches context manager responsibilities within plugin agent-orchestration. Do not use when: a more specific framework or task-focused skill is clearly a better match.

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Evaluate a codebase for agent-friendliness based on autonomous agent best practices. Use when asked to "evaluate for agents", "check agent readiness", "audit for autonomous execution", "assess agent-friendliness", or when reviewing infrastructure for unattended agent operation. Also use when asked about making a codebase more suitable for AI agents or autonomous workflows.

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This skill provides knowledge for generating effective Claude Code agents tailored to specific projects. It is used internally by the agent-team-creator plugin when analyzing codebases and creating specialized agent teams. Contains templates, best practices, and patterns for writing project-aware agents.

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