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Found 458 Skills
Multi-agent orchestration using dmux (tmux pane manager for AI agents). Patterns for parallel agent workflows across Claude Code, Codex, OpenCode, and other harnesses. Use when running multiple agent sessions in parallel or coordinating multi-agent development workflows.
Create custom multi-agent workflows for Atomic CLI using the defineWorkflow() session-based API with programmatic SDK code. Use this skill whenever the user wants to create a workflow, build an agent pipeline, define a multi-stage automation, set up a review loop, or connect multiple coding agents together. Also trigger when they mention workflow files, .atomic/workflows/, defineWorkflow, or ask how to automate a sequence of agent tasks — even if they don't use the word "workflow" explicitly.
Multi-agent autonomous startup system for Claude Code. Triggers on "Loki Mode". Orchestrates 100+ specialized agents across engineering, QA, DevOps, security, data/ML, business operations, marketing, HR, and customer success. Takes PRD to fully deployed, revenue-generating product with zero human intervention. Features Task tool for subagent dispatch, parallel code review with 3 specialized reviewers, severity-based issue triage, distributed task queue with dead letter handling, automatic deployment to cloud providers, A/B testing, customer feedback loops, incident response, circuit breakers, and self-healing. Handles rate limits via distributed state checkpoints and auto-resume with exponential backoff. Requires --dangerously-skip-permissions flag.
Q-learning, DQN, PPO, A3C, policy gradient methods, multi-agent systems, and Gym environments. Use for training agents, game AI, robotics, or decision-making systems.
Military-style Situation Report (SITREP) generation for multi-agent coordination. Creates structured status updates with completed/in-progress/blocked sections, authorization codes, handoff protocols, and clear next actions. Optimized for complex project management across multiple AI agents and human operators.
Multi-agent coordination patterns for OpenCode swarm workflows. Use when work benefits from parallelization or coordination. Covers: decomposition, worker spawning, file reservations, progress tracking, and review loops.
Letta framework for building stateful AI agents with long-term memory. Use for AI agent development, memory management, tool integration, and multi-agent systems.
Coordinate multi-agent code review with specialized perspectives. Use when conducting code reviews, analyzing PRs, evaluating staged changes, or reviewing specific files. Handles security, performance, quality, and test coverage analysis with confidence scoring and actionable recommendations.
Creates multi-agent orchestration workflows for complex tasks. Handles enterprise workflows, operational procedures, and custom orchestration patterns. Use when user needs to automate multi-phase processes with agent coordination.
LLM cost tracking with Langfuse for cached responses. Use when monitoring cache effectiveness, tracking cost savings, or attributing costs to agents in multi-agent systems.
Expert in CrewAI - the leading role-based multi-agent framework used by 60% of Fortune 500 companies. Covers agent design with roles and goals, task definition, crew orchestration, process types (sequential, hierarchical, parallel), memory systems, and flows for complex workflows. Essential for building collaborative AI agent teams. Use when: crewai, multi-agent team, agent roles, crew of agents, role-based agents.
Deterministic AI engineering workflow with multi-agent teams. Triggers: architect mode, consistency sweep, pipeline audit, team workflow