Skill UI

This guide details the recommended pattern for managing per-project plugin settings and state within a development environment. Plugins store their configuration in a dedicated `.claude/plugin-name.local.md` file. This file utilizes YAML frontmatter for structured settings (like enabling flags, retry counts, and parameters) and a Markdown body for additional context or instructions. It provides techniques for reading these settings using Bash hooks, commands, and agents.

A concise collection of idiomatic Python best practices—from readability and explicit configuration to type hints, error handling, and context managers—aimed at building robust, maintainable applications.

Expert in designing and implementing advanced Retrieval-Augmented Generation (RAG) pipelines. This role focuses on optimizing the entire information retrieval process—from document chunking and embedding model selection to vector database architectures and hybrid search strategies. The goal is to bridge the gap between raw knowledge documents and accurate LLM understanding, drastically reducing hallucination and enhancing context relevance for enterprise applications.

This guide outlines best practices for building highly flexible and maintainable React components. It addresses common architectural pitfalls, such as 'boolean prop proliferation,' by recommending advanced patterns like compound components, state lifting, and context providers. Use this when refactoring large component libraries, designing robust APIs, or reviewing component architecture, including considerations for React 19 APIs.

Automates React Context setup within frontend development, guiding users through best practices, production-ready code, and validation for React-related modern web patterns.

Implements schema.org JSON-LD across webpages so search engines grasp content intent and serve rich results like FAQs, breadcrumbs, and products, with validation checklists and contextual guidance.

This skill helps in deriving actionable security requirements directly from threat models and business contexts. It is essential for translating identified security threats into concrete, verifiable requirements, writing robust security user stories, building comprehensive test cases, and mapping compliance needs into architectural documentation.

Capture and enrich application errors in Sentry with contextual data, tags, and user attribution to streamline issue triage, exception handling, and configuration validation.

Capture and submit your first error event to Sentry, then confirm it appears in the dashboard with stack trace, metadata, user context, and tags for verifying integrations.

Defines best-practice patterns for using the Sentry SDK in TypeScript and Python, including centralized handlers, scoped contexts, structured breadcrumbs, custom fingerprinting, async propagation, and performance tracing for reliable error monitoring.

Suggests manual /compact runs at strategic workflow milestones by tracking PreToolUse calls so Claude retains context without unexpected truncation, with reminders after configurable thresholds.

A workflow for executing implementation plans by spinning up a fresh subagent for each task and enforcing consecutive spec compliance and code quality reviews so the session stays focused and high-quality without manual context switches.