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Register and implement PydanticAI tools with proper context handling, type annotations, and docstrings. Use when adding tool capabilities to agents, implementing function calling, or creating agent actions.
Guides architectural decisions for LangGraph applications. Use when deciding between LangGraph vs alternatives, choosing state management strategies, designing multi-agent systems, or selecting persistence and...
Detects common LLM coding agent artifacts in codebases. Identifies test quality issues, dead code, over-abstraction, and verbose LLM style patterns. Use when cleaning up AI-generated code or reviewing for agent...
Configure LLM providers, use fallback models, handle streaming, and manage model settings in PydanticAI. Use when selecting models, implementing resilience, or optimizing API calls.
Analyzes feedback logs to identify patterns and suggest improvements to review skills. Use when you have accumulated feedback data and want to improve review accuracy.
Create PydanticAI agents with type-safe dependencies, structured outputs, and proper configuration. Use when building AI agents, creating chat systems, or integrating LLMs with Pydantic validation.
Extract architectural decisions from conversations. Identifies problem-solution pairs, trade-off discussions, and explicit choices. Use when analyzing session transcripts for ADR generation.
Implements agents using Deep Agents. Use when building agents with create_deep_agent, configuring backends, defining subagents, adding middleware, or setting up human-in-the-loop workflows.
Reviews LangGraph code for bugs, anti-patterns, and improvements. Use when reviewing code that uses StateGraph, nodes, edges, checkpointing, or other LangGraph features. Catches common mistakes in state managem...
Guides architectural decisions for Deep Agents applications. Use when deciding between Deep Agents vs alternatives, choosing backend strategies, designing subagent systems, or selecting middleware approaches.
Implements stateful agent graphs using LangGraph. Use when building graphs, adding nodes/edges, defining state schemas, implementing checkpointing, handling interrupts, or creating multi-agent systems with Lang...
Vercel AI Elements for workflow UI components. Use when building chat interfaces, displaying tool execution, showing reasoning/thinking, or creating job queues. Triggers on ai-elements, Queue, Confirmation, Too...
Vercel AI SDK for building chat interfaces with streaming. Use when implementing useChat hook, handling tool calls, streaming responses, or building chat UI. Triggers on useChat, @ai-sdk/react, UIMessage, ChatS...
This skill should be used when writing or improving system prompts for AI agents, providing expert guidance based on Anthropic's context engineering principles.
Design ETL/ELT pipelines with proper orchestration, error handling, and monitoring. Use when building data pipelines, designing data workflows, or implementing data transformations.
Choose optimal Next.js rendering strategy (SSR, SSG, ISR, CSR) based on content type, update frequency, and performance requirements. Use when deciding how to render pages, optimizing performance, or implementi...
Troubleshoots agent behavior, logs LLM interactions, and inspects database state. Use this when responses are unexpected, to understand context the LLM receives, or to diagnose data issues.
Handles file uploads, image attachments, and media processing in agent conversations. Use this when agents analyze images, process documents, or generate files.
Streams agent responses in real-time to clients without blocking. Use this for responsive UIs, long-running generations, and asynchronous streaming to multiple clients.
Enables agents to call external functions, APIs, and database operations through tool definitions. Use this when agents need to fetch data, perform actions, or integrate with external services while maintaining...
Integrates human agents into automated workflows for human-in-the-loop interactions. Use this when humans need to respond alongside AI agents, handle escalations, or provide context that AI cannot determine.
Orchestrates multi-step agent operations with durable execution, automatic retries, and recovery from failures. Use this for complex workflows that need to survive server restarts or coordinate multiple agents.
Manages conversation threads to group messages into linear histories. Use this when organizing multi-turn conversations, managing per-user history, and handling thread metadata.
Guide for creating effective skills. This skill should be used when users want to create a new skill (or update an existing skill) that extends Claude's capabilities with specialized knowledge, workflows, or to...
Le classement utilise les étoiles du dépôt GitHub indexé. Plusieurs skills peuvent partager ce nombre : ce n’est ni un nombre d’installations ni une note de qualité.