Comprehensive inter-agent messaging and coordination system providing protocol-based communication, shared context management, event broadcasting with subscriptions, automated handoff documentation, and message persistence. This skill enables agents to coordinate work, share decisions, negotiate contracts, and maintain consistent state across distributed parallel execution environments.

Execute an autonomous development loop that picks one task per iteration, implements it, verifies it, and commits the result — each iteration in a fresh context window. Use when user runs /ralph, mentions "ralph loop", "autonomous loop", "builder verifier", "run tasks automatically", "iterate on tasks", "develop autonomously", or wants an automated build-verify-commit cycle with task tracking.

Create and manage Architecture Decision Records (ADRs) with auto-numbering, template detection, and index maintenance. Use when user mentions "ADR", "architecture decision", "document this decision", "create ADR", editing ADR files (docs/adr/, doc/adr/, .adr/), or discussing architectural choices and tradeoffs.

Creates feature branches with optimized short naming, auto-incrementing, and commit type detection (feat/fix/refactor). Supports manual descriptions and auto-generation from uncommitted git changes. Use when user requests to create branch, start new branch, make branch, checkout new branch, switch branch, new task, start working on, begin work on feature, begin feature, create feature branch, run /create-branch command, or mentions "branch", "feature", "new feature", "feat", "fix", or "checkout".

Creates Mermaid and ASCII diagrams for flowcharts, architecture, ERDs, state machines, mindmaps, and more. Use when user mentions diagram, flowchart, mermaid, ASCII diagram, text diagram, terminal diagram, visualize, C4, mindmap, architecture diagram, sequence diagram, ERD, or needs visual documentation.

Explains complex code through clear narratives, visual diagrams, and step-by-step breakdowns. Use when user asks to explain code, understand algorithms, analyze design patterns, wants code walkthroughs, or mentions "explain this code", "how does this work", "code breakdown", or "understand this function".

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.

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 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".

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

Analyze competitors and search landscape in Russian/CIS markets using Yandex tools. Finds who ranks for keywords, identifies content gaps, and discovers ranking opportunities. Use when user asks about competitors, who ranks for something, content gaps, or SERP analysis in Russia/CIS.

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".

Expertise in deployment automation, container orchestration, and infrastructure as code. Activates when working with "deploy", "kubernetes", "docker", "terraform", "helm", "k8s", "container", or cloud infrastructure.

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

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.

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.

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.

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

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.