Copilot agent that assists with bug investigation, root cause analysis, and fix generation for efficient debugging and issue resolution Trigger terms: bug fix, debug, troubleshoot, root cause analysis, error investigation, fix bug, resolve issue, error analysis, stack trace Use when: User requests involve bug hunter tasks.

Build, test, and serve the documentation site using Zensical (recommended) or MkDocs.

Migrate prompts and code from Claude Sonnet 4.0, Sonnet 4.5, or Opus 4.1 to Opus 4.5. Use when the user wants to update their codebase, prompts, or API calls to use Opus 4.5. Handles model string updates and prompt adjustments for known Opus 4.5 behavioral differences. Does NOT migrate Haiku 4.5.

Use when the user provides an implementation plan file and asks to analyze it, assess impact, update specifications, or verify planned changes. Triggers on keywords like "analyze plan", "implementation plan", "assess impact", "update spec from plan", "verify plan".

Apply structured, reflective problem-solving for complex tasks requiring multi-step analysis, revision capability, and hypothesis verification. Use for complex problem decomposition, adaptive planning, analysis needing course correction, problems with unclear scope, multi-step solutions, and hypothesis-driven work.

Create a new Claude Code agent with proper YAML frontmatter structure. Use when the user wants to add a specialized agent to a plugin. Handles agent file creation with name, description, tools, model selection, and color configuration.

Use when the user asks to investigate, understand, explore, or explain how a feature works, asks about existing logic, or wants to understand code flow. Triggers on keywords like "how does", "explain", "investigate", "understand", "what does", "where is", "how works", "logic flow", "trace", "explore feature".

Use when the user asks to generate comprehensive feature documentation with verified test cases, create feature README with code evidence, or document a complete feature with test verification. Triggers on keywords like "feature documentation", "document feature", "comprehensive docs", "feature README", "test verification", "verified documentation".

Use when the user asks to implement a new feature, enhancement, add functionality, build something new, or create new capabilities. Triggers on keywords like "implement", "add feature", "build", "create new", "develop", "enhancement".

Tracks LLM token consumption and usage metrics for billing, monitoring, and optimization. Use this to log token usage, calculate costs, generate invoices, and understand which agents or users consume the most resources.

Guide users through writing their first Buck2 rule to learn fundamental concepts including rules, actions, targets, configurations, analysis, and select(). Use this skill when users want to learn Buck2 basics hands-on or need help understanding rule writing.

Your approach to handling testing vitest. Use this skill when working on files where testing vitest comes into play.

Interactive Archon integration for knowledge base and project management via REST API. On first use, asks for Archon host URL. Use when searching documentation, managing projects/tasks, or querying indexed knowledge. Provides RAG-powered semantic search, website crawling, document upload, hierarchical project/task management, and document versioning. Always try Archon first for external documentation and knowledge retrieval before using other sources.

This skill should modify the category screens and add the requested scrcpy options to the UI, depending on the type of the option (text, toggle, dropdown, etc.). Use this skill for adding new scrcpy options in the UI.

Refactor sync+async modules to eliminate duplication using the iter-coroutine

Dual-AI engineering loop orchestrating Claude Code (planning/implementation) and Codex (validation/review). Use when (1) complex feature development requiring validation, (2) high-quality code with security/performance concerns, (3) large-scale refactoring, (4) user requests codex-claude loop or dual-AI review. Do NOT use for simple one-off fixes or prototypes.

Multi-LLM collaborative brainstorming and planning. Use when user explicitly requests consultation with multiple AI models (ChatGPT, Gemini, other LLMs) before presenting an implementation plan, or asks to "consult the council", "ask other models", or "get perspectives from other AIs". Queries external LLM APIs, synthesizes their perspectives, and presents an adapted implementation plan.

Generate ROS 2 Python launch files and multi-node system configurations for educational content. This skill should be used when creating lessons that teach launch file syntax, writing exercises involving multi-node startup, parameter configuration, or generating worked examples for robot system deployment.

Guidelines for multi-agent AI and learning projects with lesson-based structures. Activate when working with AI learning projects, experimental directories like .spec/, lessons/ directories, STATUS.md progress tracking, or structured learning curricula with multiple modules or lessons.

Meta-skill that orchestrates logging, monitoring, error handling, performance, security, deployment, and testing skills to ensure a service is fully production-ready before launch. Use before first deploy, major releases, quarterly reviews, or after incidents.