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Found 11,827 Skills
🎰 Monad Casino - An AI-powered casino where OTHER AI agents gamble against each other. You're the house. The house always wins. Built for Moltiverse Hackathon.
Guides architects on when and how to use goal-seeking agents as a design pattern. This skill helps evaluate whether autonomous agents are appropriate for a given problem, how to structure their objectives, integrate with goal_agent_generator, and reference real amplihack examples like AKS SRE automation, CI diagnostics, pre-commit workflows, and fix-agent pattern matching.
Spawn a single autonomous AI agent with a specific task, personality, and CLI backend (Claude, Gemini, OpenCode, Copilot). Agent accepts task from docs/todo/pending/, selects personality based on task type, and works autonomously with CLI tools. Integrates with docs-first workflow via task signals and progress tracking.
Amazon Bedrock AgentCore Policy for defining agent boundaries using natural language and Cedar. Deterministic policy enforcement at the Gateway level. Use when setting agent guardrails, access control, tool permissions, or compliance rules.
Amazon Bedrock AgentCore Memory for persistent agent knowledge across sessions. Episodic memory for learning from interactions, short-term for session context. Use when building agents that remember user preferences, learn from conversations, or maintain context across sessions.
Agent skill for issue-tracker - invoke with $agent-issue-tracker
Create and manage AI agent sessions with multiple backends (SDK, Claude CLI, Codex, Cursor). Also supports multi-agent workflows with shared context, @mention coordination, and collaborative voting. Use for "start agent session", "create worker", "run agent", "multi-agent workflow", "agent collaboration", "test with tools", or when orchestrating AI conversations programmatically.
Use this skill to design new products, iterate on product ideas, or develop product specifications. Triggers: "design product", "new product idea", "product concept", "product development", "product spec", "iterate on product", "product design", "invention", "prototype spec", "product requirements", "product engineering", "develop product" Outputs: Product specification, BOM estimate, feature breakdown, differentiation analysis.
Multi-agent orchestration and state management.
Patterns and architectures for building AI agents and workflows with LLMs. Use when designing systems that involve tool use, multi-step reasoning, autonomous decision-making, or orchestration of LLM-driven tasks.
Debug Node.js/TypeScript/JavaScript applications using the agent-dbg CLI debugger. Use when: (1) investigating runtime bugs by stepping through code, (2) inspecting variable values at specific execution points, (3) setting breakpoints and conditional breakpoints, (4) evaluating expressions in a paused context, (5) hot-patching code without restarting, (6) debugging test failures by attaching to a running process, (7) any task where understanding runtime behavior requires a debugger. Triggers: "debug this", "set a breakpoint", "step through", "inspect variables", "why is this value wrong", "trace execution", "attach debugger", "runtime error".
This skill should be used when the user mentions "openclaw", "OpenClaw CLI", asks to "send a message via openclaw", "manage openclaw agents", "configure openclaw gateway", "check openclaw status", "run openclaw agent", or asks about OpenClaw setup, channels, devices, or messaging automation.