ai-llm-patterns
Anthropic Claude integration patterns: streaming, RAG with pgvector, tool use, model selection (Haiku/Sonnet/Opus), prompt caching, and cost management for AI-powered engineering.
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146 skills found
Anthropic Claude integration patterns: streaming, RAG with pgvector, tool use, model selection (Haiku/Sonnet/Opus), prompt caching, and cost management for AI-powered engineering.
Manage long-running PapersFlow DeepScan research workflows with asynchronous monitoring, live progress tracking, and automated report generation.
Multi-LLM code review pipeline using consensus-based analysis to detect security, architectural, and quality issues.
Context Engineering agent skill to initialize, generate, and execute comprehensive implementation blueprints (PRPs) for one-pass software development.
Enforces a strict evidence-based debugging workflow using structured observation, hypothesis testing, and causality validation to eliminate speculation in technical investigations.
Analyze Claude Code session history to identify inefficiencies, optimize token usage, and suggest workflow improvements.
Analyze AppWorld task failures to extract specific API patterns and generate actionable playbook bullets with concrete code examples.
Master professional TDD with the London (mockist) and Chicago (classicist) schools. Automate test-first workflows, style selection, and refactoring with AI agents.
Fetches expert perspectives from OpenAI Codex and Google Gemini for architecture, code reviews, and debugging, with transparent LLM synthesis.
Review, audit, and build production-grade frontend interfaces with high design quality, accessibility standards, and design system compliance.
Implements an autonomous, critical self-verification layer for AI agents to validate code quality, security, and requirement alignment before task completion.
An advanced development guide for Claude Code, covering REPL environments, MCP integration, development workflows, and best practices for AI-assisted coding.