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Found 416 Skills
Configure and orchestrate Claude Code agent teams (TeamCreate, SendMessage, TaskUpdate workflow). Use when you need multiple agents working in parallel on a complex task, want to coordinate background agents with messaging, or are setting up a lead/teammate architecture with a shared task list. Teams are experimental — enable with --enable-teams flag.
Agent skill for queen-coordinator - invoke with $agent-queen-coordinator
Orchestrates group discussions between installed BMAD agents, enabling natural multi-agent conversations where each agent is a real subagent with independent thinking. Use when user requests party mode, wants multiple agent perspectives, group discussion, roundtable, or multi-agent conversation about their project.
Orchestrator that runs first for lead generation requests. Gathers business context via website analysis or questions, identifies competitors, builds ICP, and routes to signal skills with pre-filled inputs.
Decomposes a spec or architecture into buildable tasks with acceptance criteria, dependencies, and implementation order for AI agents or engineers. Produces `.agents/tasks.md`. Not for clarifying unclear requirements (use discover) or designing architecture (use system-architecture). For code quality checks after building, see review-chain. For packaging and PRs, see ship.
Comprehensive map and workflows for the Database domain. Triggers when users ask to 'design a database', 'optimize query', 'schema architecture', 'database ecosystem', or migrate data.
Orchestrates multi-advisor council debates on high-impact architecture, technology, or product decisions. Dispatches 3-5 domain archetype subagents (pragmatic-engineer, architect-advisor, security-advocate, product-mind, devils-advocate, the-thinker) through opening statements, tensions, position evolution, and synthesis phases. Preserves dissent and delivers actionable recommendations with captured risks. Use when evaluating trade-offs, stress-testing a PRD or tech spec, resolving dilemmas with multiple viable options, or when a decision needs diverse expert perspectives. Don't use for simple yes/no questions, factual lookups, creative brainstorming without tradeoffs, or tasks where a single expert perspective suffices.
Launch an intelligent sub-agent with automatic model selection based on task complexity, specialized agent matching, Zero-shot CoT reasoning, and mandatory self-critique verification
Builds production AI/ML systems — model training, fine-tuning, MLOps pipelines, model serving, evaluation frameworks, RAG optimization, and agent orchestration at scale. Use when the user asks to build, train, or deploy ML models, set up MLOps pipelines, optimize RAG systems, create inference endpoints, or design production AI agents.
Execute from requirement analysis to frontend design document creation
Use when the user asks to create, generate, or scaffold a SeeFlow flow from a natural-language prompt — "create a flow", "show how X works", "diagram our checkout system", "add a flow to this repo". Orchestrates four sub-agents and bun scripts to write a registered, validated flow under <project>/.seeflow/<slug>/.
Convene 11 role-specialized Claude agents to debate technical decisions in parallel, with the invoking Claude acting as CEO