Multi-agent orchestration framework for autonomous AI collaboration. Use when building teams of specialized agents working together on complex tasks, when you need role-based agent collaboration with memory, or for production workflows requiring sequential/hierarchical execution. Built without LangChain dependencies…
Framework for building LLM-powered applications with agents, chains, and RAG. Supports multiple providers (OpenAI, Anthropic, Google), 500+ integrations, ReAct agents, tool calling, memory management, and vector store retrieval. Use for building chatbots, question-answering systems, autonomous agents, or RAG…
Use when building or modifying a Python app that uses the agent-squad Python package — async multi-agent orchestration for Python 3.11+: orchestrator, agents (BedrockLLMAgent, AnthropicAgent, OpenAIAgent, SupervisorAgent, GroundedAgent, ChainAgent, and more), classifier routing (Bedrock, Anthropic, OpenAI), storage…
Use when building or modifying a Swift app that uses the AgentSquad Swift framework — on-device multi-agent orchestration for iOS 16+ / macOS 14+: orchestrator, agents (Agent, GroundedAgent), classifier routing, LLM clients (OpenAI-compatible), tools (native + MCP), tool UIs/widgets, on-device storage, tracing, and…
Applies Anthropic's official brand colors and typography to any sort of artifact that may benefit from having Anthropic's look-and-feel. Use it when brand colors or style guidelines, visual formatting, or company design standards apply.
Use this skill when the user asks about creating videos with React, Remotion framework, programmatic video generation, video animations, or needs help with Remotion projects.
Audit a CLAUDE.md file for the patterns that actually degrade Claude Code's output — vagueness, unnamed files, stale facts, and bloat. Use when asked to review, audit, improve, shrink, or fix a CLAUDE.md, and when a project's results feel inconsistent or Claude keeps rediscovering the same context.
Defines practical standards for implementation-focused coding agents. Use when creating or editing code, especially when reliability, clarity, and low-risk delivery are required.
Designs clear, testable prompts for agent workflows. Use when creating new prompts, refining weak prompts, or establishing reusable prompting patterns.
Provides a structured verification workflow for code and prompt outputs. Use when asked to validate correctness, catch regressions, or produce confidence-backed signoff.
Automatic code quality and best practices analysis. Use proactively when files are modified, saved, or committed. Analyzes code style, patterns, potential bugs, and security basics. Triggers on file changes, git diff, code edits, quality mentions.
Automatically suggest tests for new functions and components. Use when new code is written, functions added, or user mentions testing. Creates test scaffolding with Jest, Vitest, Pytest patterns. Triggers on new functions, components, test requests, testing mentions.
Host-side setup, configuration, customization, builds, migration, and troubleshooting for the Aerovato Container CLI. Use when working with Aerovato Container, settings.json, Dockerfile.User, build stages, V2-to-V3 migration, mounts, harnesses, tools, permissions, Docker, or Podman. Do not use it to expose host…
Fan out a one-shot or flat parallel batch of cc-fleet PROVIDER subagents (headless cc-fleet subagent) that return a result — DeepSeek / GLM / Kimi / Qwen / MiniMax, or a Codex/Claude subscription. Trigger ONLY to delegate a task to a cc-fleet provider worker (parallel research, bulk per-file work, a specialized…
Orchestrate a MULTI-PHASE, dependent, or resumable run over many cc-fleet PROVIDER subagents from a JS script, off the main context (cc-fleet workflow). Use for fan-out→barrier→synthesis, per-item pipelines, loop-until-dry, or a run that must survive a kill and --resume from its journal. Trigger ONLY to run a cc-fleet…
Spawn long-lived provider LLM teammates in tmux panes that you message via the native agent-team tools — multi-turn, collaborative, watchable. Use for sustained parallel build/work ("spawn workers", N teammates on N files), or when you need a collaborator you message across turns. NOT a fire-and-forget one-shot or a…
Record a clean product demo video of a web app on a disposable cloud VM — provision a GCE instance, install Xvfb + Chrome + ffmpeg + real fonts, deploy the app, drive the UI deterministically with Playwright over CDP while x11grab records, then cut the raw take into a social-ready clip with speed ramps and burned-in…
Developer implementation guide for building hierarchical (folded) memory into an Agent. Three-layer architecture where recent turns stay detailed, older content compresses into episodes, and the oldest distills into durable semantic facts. Use when compact-memory-implementation is not retaining enough, or when agents…