Skill UI

Generates production-ready Kubernetes deployment, service, ingress, and autoscaler manifests using best practices such as health checks, TLS, and resource limits. Use this when creating or updating deployments, services, ConfigMaps, Secrets, or other Kubernetes resource manifests for any application.

A protocol that provides LLM agents with persistent structural memory of a codebase. It maps the project as a directed graph, tracking not only dependencies (what imports what) but also the 'reasons' (why it connects). This allows agents to understand context, perform impact analysis, and navigate large repositories without loading the entire source code into the context window.

This skill provides step-by-step guidance for creating production-ready Kubernetes manifests. It covers essential resources including Deployments, Services, ConfigMaps, Secrets, and PersistentVolumeClaims. Use this skill when defining complete, robust containerized application architectures, managing network connectivity, stateful workloads, and ensuring adherence to Kubernetes best practices like resource limits and security contexts.

This comprehensive checklist guides developers through the pre-release verification process for Obsidian community plugins. It covers critical technical areas such as validating manifest structure, ensuring clean production builds (e.g., removing sourcemaps), identifying potential memory leaks, and verifying cross-platform readiness, ensuring a high-quality user experience upon submission.

A comprehensive guide to integrating Sentry into continuous integration and continuous deployment (CI/CD) pipelines (e.g., GitHub Actions, GitLab CI, CircleCI). This skill automates complex tasks such as creating releases, uploading source maps for readable stack traces, associating commits, and tracking deployment environments, ensuring rapid and accurate debugging of production errors.

Integrate Sentry into your CI/CD pipeline to achieve end-to-end release tracking. This skill guides you through using the Sentry CLI and SDK to record deployments, associate commits, upload source maps, and monitor crucial release health metrics. Key functions include detecting regressions, calculating crash-free session rates, and tracking user adoption curves for every deployed version.

A comprehensive checklist for ensuring Sentry is properly configured before any production deployment. This guide covers best practices for managing environment variables (DSN), implementing release tracking, optimizing error and trace sample rates, uploading source maps, and filtering noise. Essential for go-live readiness and auditing existing monitoring setups.

This guide details how to use the Sentry CLI to manage the full application release lifecycle. Users can create versioned releases (using Semver or SHA), upload source maps to deminify stack traces, and associate specific git commits. This ensures that every error is accurately linked to the exact code version and deployment that caused it, significantly improving debugging and observability in CI/CD pipelines.

This comprehensive guide dives deep into the internals of Go's built-in data structures (slices, maps, arrays) and standard library packages. It covers critical topics like capacity growth mechanics, preallocation strategies, pointer types (unsafe/weak), and the optimized usage of specialized containers (heap, list, ring). Use this resource to select the correct structure for optimal performance and memory safety in expert Go development.

This skill involves creating structured specifications before writing any code to serve as a shared source of truth between developers and engineers. It is used when starting new projects, features, or significant changes where requirements are unclear or ambiguous. The workflow includes a scope check, specifying objectives, planning, task breakdown, and implementation with human reviews at each phase. It helps decompose complex requirements into capability maps and ensures clarity before coding begins.

This guide maps user questions and topics (e.g., configuration, memory, skills, CLI) to specific, relevant documentation paths and source code entry points within the QwenPaw ecosystem. It is designed for built-in QA Agents to eliminate aimless searching, ensuring the agent reads the most accurate files to provide comprehensive and precise answers about the system's features.

This comprehensive tool analyzes a detailed specification by synthesizing data from multiple source files (JSON, Markdown, etc.). It tracks phase completion, identifies task progress, maps boundary contexts (upstream/downstream dependencies), and proactively highlights necessary revalidation points or blockers, providing a single, unified report of the spec's completeness and current development state.