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Found 1,145 Skills
Safe experimentation framework for AI agents. Creates isolated sandbox environments for trying new features, testing approaches, and exploring solutions without polluting the main codebase. USE WHEN: Agent needs to try something uncertain, explore multiple approaches, test a new library, prototype a feature, or run a technical spike before committing to implementation. PRIMARY TRIGGERS: "experiment with" = Setup sandbox + run experiment "try this approach" = Quick experiment in sandbox "spike" / "POC" / "prototype" = Time-boxed technical investigation "tinker" / "tinkering mode" = Enter experimentation workflow "explore options" = Multi-approach comparison in sandbox NOT FOR: Debugging (use debugger), testing (use test runner), or committed feature work (use git branches). DIFFERENTIATOR: Unlike git branches (for committed direction), tinkering is for "I don't know if this will work" exploration. Try 5 things in sandbox before committing to a branch. Faster feedback, zero codebase pollution.
Generates iterable checklist PROMPT files for Ralph Loop from plan files or current context, and provides the /ralph-loop execution command.
Управление сессиями AI агентов через agent-deck CLI. Триггеры (RU): "запусти агента", "запусти саб-агента", "создай сессию", "проверь сессию", "проверь статус", "покажи вывод агента", "что агент ответил". Triggers (EN): "launch sub-agent", "create sub-agent", "start session", "check session", "show agent output".
Quick persona switching. Triggers: 'switch persona', 'switch to X', 'become X'. Lists personas, reads selected file, switches immediately.
Guide for creating and enhancing skills. Use when users want to create a new skill, update/improve an existing skill, or audit skill quality. Supports both creation from scratch and enhancement of existing skills with audit rubric scoring.
Build AI agents with persistent threads, tool calling, and streaming on Convex. Use when implementing chat interfaces, AI assistants, multi-agent workflows, RAG systems, or any LLM-powered features with message history.
The soul of MOOLLM — self-explanation, help, navigation, philosophy
Build production-ready AI agents using Google's Agent Development Kit with AI assistant integration, React patterns, multi-agent orchestration, and comprehensive tool libraries. Use when appropriate context detected. Trigger with relevant phrases based on skill purpose.
Deploy and orchestrate Vertex AI ADK agents using A2A protocol. Manages AgentCard discovery, task submission, Code Execution Sandbox, and Memory Bank. Use when asked to "deploy ADK agent" or "orchestrate agents". Trigger with phrases like 'deploy', 'infrastructure', or 'CI/CD'.
Proposal-first development workflow with commit hygiene and decision authority rules. Enforces: propose before modifying, atomic commits, no force flags, warnings-as-errors. Use for any project where AI agents are primary developers and need guardrails.
Apply plugin knowledge base updates to an existing generated system. Consults the Ars Contexta research graph for methodology improvements, proposes skill upgrades with research justification. Never auto-implements. Triggers on "/upgrade", "upgrade skills", "check for improvements", "update methodology".
Use when improving agent prompts, frontmatter, and tool restrictions.