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Found 409 Skills
Quantum-resistant, self-learning version control for AI agents with ReasoningBank intelligence and multi-agent coordination
Invoke MassGen's multi-agent system for general-purpose tasks, evaluation, planning, or spec writing. Use whenever you want multiple AI agents to tackle a problem, need outside perspective on your work, a thoroughly refined plan, or a well-specified set of requirements. Perfect for: writing, code generation, research, design, analysis, pre-PR review, complex project planning, feature specification, architecture decisions, or any task where multi-agent iteration produces better results than working alone.
Run yourself in a loop with programmatic control via the Agent SDK. Use for long-running tasks like optimization, research, iterative improvement, multi-agent coordination, or any multi-step workflow where you need to repeat, branch, or track progress.
Meta-skill for understanding and customizing Mindfold Trellis — the all-in-one AI workflow system for 11 AI coding platforms (Claude Code, Cursor, OpenCode, iFlow, Codex, Kilo, Kiro, Gemini CLI, Antigravity, Qoder, CodeBuddy). Documents the original Trellis system design including architecture, commands, hooks, multi-agent pipelines, monorepo support, and task lifecycle hooks. Use when understanding Trellis architecture, customizing workflows, adding commands or agents, troubleshooting issues, or adapting Trellis to specific projects. Modifications should be recorded in a project-local trellis-local skill, not here.
Design, implement, and debug autonomous AI agents and multi-agent systems using the Google Antigravity (AGY) SDK. ACTIVATE this skill when the user wants to create, configure, or orchestrate Google Antigravity agents.
Step-by-step guide to building AI agents from simple chat loops to autonomous multi-agent systems with tools, memory, and event-driven architecture
Orchestrates design workflows by routing work through brainstorming, multi-agent review, and execution readiness in the correct order. Prevents premature implementation, skipped validation, and unreviewed high-risk designs.
Decompose complex tasks, design dependency graphs, and coordinate multi-agent work with proper task descriptions and workload balancing. Use this skill when breaking down work for agent teams, managing task dependencies, or monitoring team progress.
Expert in designing and building autonomous AI agents. Masters tool use, memory systems, planning strategies, and multi-agent orchestration. Use when "build agent, AI agent, autonomous agent, tool use, function calling, multi-agent, agent memory, agent planning, langchain agent, crewai, autogen, claude agent sdk, ai-agents, langchain, autogen, crewai, tool-use, function-calling, autonomous, llm, orchestration" mentioned.
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.
Load PROACTIVELY when task involves building a complete feature across multiple layers. Use when user says "build a feature", "add user profiles", "create a dashboard", or any request spanning database, API, UI, and tests. Orchestrates multi-agent work sequentially: schema and migrations, API endpoints, UI components, tests, and review. Handles dependency ordering and cross-layer type sharing.
Spec-Driven Development (SDD) methodology based on GitHub's SpecKit. Use for structured AI-assisted development with constitutional governance, phased workflows, and multi-agent coordination. Implements 7-phase process from constitution to implementation.