Generate and maintain project structure index for fast AI navigation. Creates docs/structure.md with optimized file index. Load this skill when starting new project, after major changes, or when docs/structure.md is outdated.

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

Use when the user asks to debug, diagnose, fix a bug, troubleshoot errors, investigate issues, or pastes error messages/stack traces. Triggers on keywords like "bug", "error", "fix", "not working", "broken", "debug", "stack trace", "exception", "crash", "issue".

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 creating API services for backend communication with proper patterns for caching, error handling, and type safety.

Start and interact with the Dataset Analysis Tool (dataviewer) for browsing, annotating, and exporting robotic training episodes

Principles for designing context-efficient AI agents and tools. Use when designing LLM tools, agents, MCP servers, or multi-agent systems.

Multi-perspective AI consultation. Invoke with /tzurot-council-mcp for major refactors (>500 lines), structured debugging after failed attempts, or when a technical decision has multiple viable approaches.

Use when the user asks to analyze package upgrades, check for outdated dependencies, plan npm/NuGet updates, or assess breaking changes in package updates. Triggers on keywords like "upgrade packages", "outdated", "npm update", "breaking changes", "dependency upgrade", "package update", "version upgrade".

Analyze student git activity, lab submissions, and project work for software engineering courses. Use when asked to "update student analysis", "check student activity", "analyze the class", or when working with student rosters and git repositories. Handles inconsistencies in student behavior like multiple usernames, name variations, and missing data.

Layer 4 Learning and Pattern Extraction for Cognitive Surrogate Systems

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.

Comprehensive code refactoring operations for improving code quality and maintainability

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 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".

Add a new property to the AI agents database. Use when the user wants to add, create, or introduce a new column, property, field, or feature to track across all agents in the comparison matrix. Handles all four required steps - database updates, groups.json, table display, and GitHub issue templates.

Implement production-ready features across database, backend, and frontend layers with incremental phased approach

Use when testing web applications, debugging browser console errors, automating form interactions, or verifying UI implementations. Load for localhost testing, authenticated app testing (Gmail, Notion), or recording demo GIFs. Requires Chrome extension 1.0.36+, Claude Code 2.0.73+, paid plan.

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.