code-review-expert
Expert code review agent that performs systematic audits of git changes for SOLID violations, security vulnerabilities, performance regressions, and architectural smells.
Discover reusable agent skills, browse implementation details, and find the right skill for your workflow.
179 skills found
Expert code review agent that performs systematic audits of git changes for SOLID violations, security vulnerabilities, performance regressions, and architectural smells.
Language-agnostic backend architectural patterns covering API design, authentication, security protocols, and database modeling.
A specialized skill for building and managing Next.js App Router API routes, handling HTTP methods, request bodies, streaming, and response configuration.
Expert guide for OpenCode AI: TUI commands, CLI operations, AGENTS.md configuration, custom agent workflows, and project setup.
AWS DynamoDB engineering assistant for schema design, query optimization, single-table patterns, and infrastructure management using Boto3 and AWS CLI.
Optimize Node.js performance via Redis caching, clustering, profiling, and monitoring to build fast, scalable, and efficient backend services.
A toolkit for building robust LLM integrations: API patterns, streaming, function calling, RAG pipelines, and cost-effective model routing.
Create, register, and manage custom agent tools and MCP servers to extend AI agent capabilities with external APIs and custom logic.
Neural web search and code context retrieval via Exa AI. Ideal for documentation, technical research, code examples, and company intelligence.
Guide for implementing features using architecture-first design, TDD, rich domain models, and Swift 6.2 patterns, ensuring a clean separation between Domain, Infrastructure, and App layers.
Statistical visualization library for Python. Create publication-quality graphics like box plots, heatmaps, and violin plots with pandas integration and automatic statistical estimation.
Build systematic evaluation frameworks for AI agents using multi-dimensional rubrics, LLM-as-a-judge, and regression testing to measure performance, quality, and context engineering effectiveness.