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.
Discover reusable agent skills, browse implementation details, and find the right skill for your workflow.
500 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.
Expert Svelte 5 runes guidance: reactive state ($state), derived values ($derived), effects ($effect), props, and migration strategies. Prevents reactivity anti-patterns.
Comprehensive management for the Flow Nexus platform, covering user authentication, sandbox execution, app deployment, credit management, and gamified challenges.
Production-grade observability stack featuring Prometheus metrics, Grafana dashboarding, PromQL query language, alerting rules, and AI-powered anomaly detection for cloud-native applications.
Development CLI for the Multigres project: automate unit tests, integration tests, and environment coordination for Vitess-for-Postgres.
Autonomous multi-agent orchestration framework for Claude Code with memory-driven workflows, parallel-first task execution, Aristotle-based deconstruction, and multi-stage quality gates.
Language-agnostic debugging framework: scientific method, stack trace analysis, logging strategies, and advanced techniques like Git bisect and rubber ducking.
Development guide for self-improving MassGen via programmatic automation testing and visual UI/UX evaluation.
Asana project management integration. Manage tasks, projects, workspaces, and team workflows directly via the Membrane CLI.
Optimize agent performance and token usage through advanced context compression, structured summarization, and task-oriented state management for long-running sessions.
Production-grade React 19 and TypeScript patterns featuring hooks, state management, TanStack Query, form validation with Zod, and performance optimization workflows.
Production-grade testing strategy implementing feature flags, canary releases, synthetic monitoring, and chaos engineering for continuous reliability in live environments.