Skill UI

Automates Claude Code plugin audits whenever audit or security keywords appear, checking for vulnerabilities, compliance with CLAUDE.md standards, marketplace/MCP requirements, best practices, documentation, and repository hygiene before emitting a structured report.

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.

This guide details the standardized directory structure and best practices for building robust and maintainable plugins for Claude Code. It covers critical components including the plugin manifest (plugin.json), commands, agents, skills, and hooks. Use this skill when you need to scaffold a new plugin, understand the required component organization, or configure the plugin's architecture according to best practices.

This skill provides expert guidance on writing highly portable shell scripts that adhere strictly to POSIX standards. It teaches users how to avoid shell-specific extensions (like advanced arrays, specific conditionals, or GNU features) to ensure maximum compatibility and robustness across diverse Unix-like systems (Linux, BSD, Solaris, etc.). Ideal for critical infrastructure scripting and environments requiring extreme cross-platform reliability.

Automates the collection of comprehensive diagnostic evidence for PostHog support tickets. This bundle gathers runtime environment details (Node, Python versions), SDK versions, API connectivity status to US/EU clouds, feature flag settings, event flow testing results, and redacts sensitive environment variables. It provides a structured, support-ready archive for rapid troubleshooting.

A comprehensive guide for safely upgrading PostHog SDKs (for JavaScript and Node.js). This resource details critical breaking changes across major versions, such as the explicit requirement for `sendFeatureFlags` in v5.x and the new structured autocapture API for PostHog.js. It provides a structured, step-by-step procedure covering version auditing, code modification, testing, staging validation, and rollback plan.

This comprehensive guide teaches the best practices for writing effective, blameless postmortem reports following technical incidents. It provides a structured approach to documenting timelines, conducting root cause analysis (RCA), identifying systemic failures, and creating actionable follow-up items. Mastering this skill is crucial for fostering organizational learning and preventing future service disruptions.

Handles PPTX creation, editing, and analysis by unpacking the ZIP/XML structure, extracting themes, typography, and media, and using html2pptx to build new decks with deliberate color, contrast, and hierarchy choices.

A guide to building robust projections and read models from continuous event streams. This pattern is essential for implementing CQRS read sides, creating materialized views, optimizing query performance, and building complex search indexes in event-sourced architectures. Use it when data needs to be transformed and aggregated from raw events into optimized query structures.

Provides prioritized performance optimization recommendations across frontend, backend, and infrastructure, offering bottleneck analysis, impact estimates, and phased implementation roadmaps when users request speed improvements or reviews.

This skill acts as an expert architect to generate complete, production-ready Python project structures. It supports various modern architectures, including FastAPI, Django (full-stack), standalone libraries, and CLI tools. It ensures adherence to best practices, includes dependency management (uv, pip), type hinting, and comprehensive testing skeletons.

A comprehensive technical guide covering the entire lifecycle of Python packaging. It teaches developers how to structure, build, test, and distribute robust Python libraries using modern standards like pyproject.toml, generating wheels, and publishing artifacts reliably to PyPI or private package indexes. Ideal for creating reusable, professional-grade Python code.