By NikiforovAll
Analyze tasks and codebase context to propose minimal multi-agent teams with defined roles and responsibilities, then create the team after confirmation. Also generate Architecture Decision Records with ordered implementation steps for planning non-trivial changes.
Analyze a task and produce an Architecture Decision Record with implementation steps.
Analyze a task, propose an agent team composition with roles and responsibilities, and create the team after user confirmation. Use when the user says "team stack", "create a team", "set up agents for this", or describes a complex task that would benefit from multiple agents working together.
A collection of Claude Code recommendations and practices.
Learn practical techniques to enhance your AI-assisted development workflow with Claude Code.

# Add the marketplace
claude plugin marketplace add nikiforovall/claude-code-rules
# Install plugins
claude plugin install handbook@cc-handbook
claude plugin install handbook-extras@cc-handbook
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Sign in to claimKeycloak administration and Keycloak.AuthServices .NET library development skills
GitLab CLI (glab) expertise for managing merge requests, issues, CI/CD pipelines, and repositories from the command line
Discover and audit all plugins in a Claude Code marketplace with installation status, versions, and component breakdown
C# Language Server Protocol support using csharp-ls for code intelligence features
Python scripting and Gemini image generation using uv with inline script dependencies
npx claudepluginhub nikiforovall/claude-code-rules --plugin handbook-team-stackIntelligently compose and deploy Claude Code Agent Teams. Auto-selects optimal team composition from 24+ agents and 83+ skills across 5 scopes, generates task dependency graphs, and orchestrates multi-agent workflows with a single command.
Orchestrate multi-agent teams for parallel code review, hypothesis-driven debugging, and coordinated feature development using Claude Code's Agent Teams
Multi-agent development workflow (/crew) — planning, implementation, review, documentation, evals, and audit gates. Commands, agents, and skills are auto-discovered from the repo.
The mentor framework for Claude Code: a self-contained process layer with per-session modes, a work-item lifecycle with a hard Definition of Done, budget-aware autonomy, visual verification, and safety rules that travel into every subagent
AI Development Environment - Multi-agent orchestration for Claude Code
Spec-driven development workflow system with structured phases: Requirements → Design → Tasks → Implementation