xiaden

Reference for the Nomarr Docker development environment. Use when working with Docker containers, running e2e tests, querying ArangoDB directly, debugging prod-like issues, testing DB migrations, or interacting with the containerized Nomarr API. Contains credentials, ports, PowerShell snippets, AQL queries, and collection schema.

Generates a structured prompt for spawning Support-Librarian to gather relevant ADRs, logs, and design docs before a design, planning, or execution task. Use before starting any significant work — designing a feature, creating a plan, executing a plan, or reviewing code — to ensure prior decisions and dead ends are known. Trigger automatically in agents that have this skill, or manually when entering an unfamiliar area.

Fetch authoritative, up-to-date external documentation using Context7 MCP tools. Use proactively — without being asked — whenever writing or reviewing code that involves a third-party library or framework API (method signatures, config keys, behavior); a named library version (e.g., "Next.js 15", "React 19", "AWS SDK v3"); non-trivial configuration such as auth flows, crypto, or security-critical patterns; unfamiliar error messages from external tools; or any situation where guessing an API would be risky. Skip for purely local refactors and language fundamentals with no external dependencies.

Guide for building Python applications using the GitHub Copilot SDK. Use when integrating GitHub Copilot into Python apps: creating CopilotClient sessions, defining custom tools, handling streaming responses, managing session lifecycle, Pydantic parameter validation, BYOK (Bring Your Own Key) provider configuration, or any GitHub Copilot SDK API pattern. Requires Python 3.9+, asyncio, and GitHub Copilot CLI in PATH.

Use when executing implementation plans produced by the feature-planning skill. Orchestrates execution subagents (one plan phase at a time), dispatches review subagents for thorough quality enforcement after each plan, and manages fix cycles when review finds issues. Trigger when user says "execute the plans", "implement the feature", "work through the plans", or when validated plans exist in artifacts/plans/pending/TASK-*-{A..Z}-*.md and need implementation. Not for single-plan execution — use plan_complete_step directly for those.

Use when decomposing a major feature design into dependency-ordered implementation plans. Handles the full pipeline from design document to validated, cross-referenced plan files with minimal drift. Trigger when user mentions planning a large feature, breaking down a design doc into parts, creating implementation plans for multi-part work, or coordinating plans that span multiple sessions. Not for single plans or simple tasks — use the Plan subagent directly for those.

Use when checking code quality, finding violations, detecting complexity issues, or running QC checks. Provides scripts for linting, naming enforcement, dead code detection, and legacy code discovery.

Guide for creating high-quality MCP (Model Context Protocol) servers that enable LLMs to interact with external services through well-designed tools. Use when building MCP servers to integrate external APIs or services, whether in Python (FastMCP) or Node/TypeScript (MCP SDK).

Create a subsystem orientation skill after deep research on a stable, non-churning part of the codebase when no skill exists for it. Use when you have just read many files, traced call chains, or explored architecture to understand how a subsystem works — and that knowledge should be captured to prevent the same context burn on every future session touching that area. Triggers include: had to explore 5+ files to understand one concept, traced IPC/process/worker/pipeline topology manually, or answered "how does X actually work" from scratch.

Use when executing implementation plans produced by the feature-planning skill. Orchestrates execution subagents (one plan phase at a time), dispatches review subagents for thorough quality enforcement after each plan, and manages fix cycles when review finds issues. Trigger when: (1) the user explicitly says "execute the plans", "implement the feature", or "work through the plans"; OR (2) the user asks to start implementation and every plan for the single feature being executed (all lettered plans A–Z for that specific feature slug, covering its full scope) exists and is schema-valid in artifacts/plans/pending/TASK-*-{A..Z}-*.md. Not for single-plan execution — use plan_complete_step directly for those.

Use when decomposing a major feature design into dependency-ordered implementation plans. Handles the full pipeline from design document to validated, cross-referenced plan files with minimal drift. Trigger when **any** of the following are true, with user requests (4) taking priority over the other conditions: (1) the feature involves 3+ implementation parts, (2) it spans multiple architectural layers, (3) it requires coordination across multiple sessions, or (4) the user explicitly asks to break down a design doc into implementation plans. Not for single plans or simple tasks — use the Plan subagent directly for those.

Use when creating or updating VS Code Copilot agent hook files in .github/hooks. Covers all 8 hook event types (PreToolUse, PostToolUse, SessionStart, SubagentStart, SubagentStop, Stop, UserPromptSubmit, PreCompact), the stdin/stdout JSON contract, permissionDecision allow/deny/ask, exit code semantics, hook command properties, and repository conventions for Python validator scripts.

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 tool integrations.

Guide for creating high-quality MCP (Model Context Protocol) servers that enable LLMs to interact with external services through well-designed tools. Use when building MCP servers to integrate external APIs or services, whether in Python (FastMCP) or Node/TypeScript (MCP SDK).

Generates a structured prompt for spawning Support-Librarian to gather relevant ADRs, logs, and design docs before a design, planning, or execution task. Use before starting any significant work — designing a feature, creating a plan, executing a plan, or reviewing code — to ensure prior decisions and dead ends are known. Trigger automatically in agents that have this skill, or manually when entering an unfamiliar area.

Use when exploring codebase structure, discovering module APIs, understanding imports, or checking what functions exist. Provides scripts that replace manual file reading with structured discovery.