langchain-architecture
Architect production-grade LLM applications using LangChain 1.x and LangGraph. Implement stateful AI agents, multi-step workflows, and custom memory systems for complex conversational and automation tasks.
Discover reusable agent skills, browse implementation details, and find the right skill for your workflow.
481 skills found
Architect production-grade LLM applications using LangChain 1.x and LangGraph. Implement stateful AI agents, multi-step workflows, and custom memory systems for complex conversational and automation tasks.
Expert tool for auditing and validating the structural integrity, naming conventions, and best practices of Claude Code configurations, including skills, hooks, and commands.
Extracts Supabase anonymous API keys from client-side source code to facilitate RLS testing and security auditing.
Manage Slack communications: send, edit, delete messages, handle reactions, pin items, and fetch member information directly through your AI agent.
Expert Zed editor assistant for settings, keymaps, tasks, AI agent profiles, and language server configuration.
Perform comprehensive trading comparables analysis using peer multiples, operational KPIs, and valuation modeling to assess company relative value.
Generate and edit images, diagrams, and infographics using Google's Gemini 3 Pro model. Supports text-to-image, style transformation, and data-accurate visual creation.
Autonomous multi-team codebase improvement agent with specialized modes: narrow (goal-directed), broad (hypothesis-divergent), and sweep (quality-focused).
Intelligent orchestration for dispatching tasks to specialized background agents with performance-based routing and execution tracking.
Keep your technical specifications, test suites, and source code perfectly synchronized during AI-assisted development.
Infrastructure for cross-product HealthSim data persistence, entity correlation via SSN, and DuckDB database operations.
Operate the btca CLI for source-first code research. Manage git, local, and npm resources to ground AI answers in actual codebase context rather than outdated documentation.