Browse reusable Agent Skills, each with a clear purpose and practical guidance.
Guide for creating agent-deck watchers conversationally. This skill should be used when users want to set up a new watcher (webhook, ntfy, github, slack, gmail) to route events to a conductor. It walks the user through selecting an adapter type, gathering required settings, generating watcher.toml and clients.json entries, and emits the exact `agent-deck watcher create` command to run.
Terminal session manager for AI coding agents. Use when user mentions "agent-deck", "session", "sub-agent", "MCP attach", "git worktree", or needs to (1) create/start/stop/restart/fork sessions, (2) attach/detach MCPs, (3) manage groups/profiles, (4) get session output, (5) configure agent-deck, (6) troubleshoot issues, (7) launch sub-agents, or (8) create/manage worktree sessions. Covers CLI commands, TUI shortcuts, config.toml options, and automation.
Guide for creating and integrating Skills in DXOS. Use when adding skills to plugins, wiring operations as tools, structuring skill definitions, or testing with AssistantTestLayer.
Codex wrapper plus same-process expect PTY injector that keeps work moving until an explicit parseable done signal is emitted.
Building stateful, resilient AI agents with LangGraph v1.0.
You are an expert prompt engineer specializing in crafting effective prompts for LLMs through advanced techniques including constitutional AI, chain-of-thought reasoning, and model-specific optimizati
Use this skill when a design or idea requires higher confidence, risk reduction, or formal review. This skill orchestrates a structured, sequential multi-agent design review where each agent has a strict, non-overlapping role. It prevents blind spots, false confidence, and premature convergence.
Architecting real-time Voice AI agents.
Production-ready patterns for building LLM applications. Covers RAG pipelines, agent architectures, prompt IDEs, and LLMOps monitoring. Use when designing AI applications, implementing RAG, building agents, or setting up LLM observability.