claude-code-templates

Testing and benchmarking LLM agents including behavioral testing, capability assessment, reliability metrics, and production monitoring—where even top agents achieve less than 50% on real-world benchmarks Use when: agent testing, agent evaluation, benchmark agents, agent reliability, test agent.

Use this agent when creating specialized Claude Code agents for the claude-code-templates components system. Specializes in agent design, prompt engineering, domain expertise modeling, and agent best practices. Examples: <example>Context: User wants to create a new specialized agent. user: 'I need to create an agent that specializes in React performance optimization' assistant: 'I'll use the agent-expert agent to create a comprehensive React performance agent with proper domain expertise and practical examples' <commentary>Since the user needs to create a specialized agent, use the agent-expert agent for proper agent structure and implementation.</commentary></example> <example>Context: User needs help with agent prompt design. user: 'How do I create an agent that can handle both frontend and backend security?' assistant: 'Let me use the agent-expert agent to design a full-stack security agent with proper domain boundaries and expertise areas' <commentary>The user needs agent development help, so use the agent-expert agent.</commentary></example>

Create, manage, and orchestrate AI agents using the AI Maestro CLI. Use when the user asks to "create agent", "list agents", "delete agent", "hibernate agent", "wake agent", "install plugin", "show agent", "restart agent", or any agent lifecycle management task.

Manage multiple local CLI agents via tmux sessions (start/stop/monitor/assign) with cron-friendly scheduling.

A hybrid memory system that provides persistent, searchable knowledge management for AI agents (Architecture, Patterns, Decisions).

Memory is the cornerstone of intelligent agents. Without it, every interaction starts from zero. This skill covers the architecture of agent memory: short-term (context window), long-term (vector stores), and the cognitive architectures that organize them. Key insight: Memory isn't just storage - it's retrieval. A million stored facts mean nothing if you can't find the right one. Chunking, embedding, and retrieval strategies determine whether your agent remembers or forgets. The field is fragm

Send and receive cryptographically signed messages between AI agents using the Agent Messaging Protocol (AMP). Use when the user asks to "send a message to an agent", "check agent inbox", "message another agent", "reply to a message", "notify an agent", or any inter-agent communication task.

Tools are how AI agents interact with the world. A well-designed tool is the difference between an agent that works and one that hallucinates, fails silently, or costs 10x more tokens than necessary. This skill covers tool design from schema to error handling. JSON Schema best practices, description writing that actually helps the LLM, validation, and the emerging MCP standard that's becoming the lingua franca for AI tools. Key insight: Tool descriptions are more important than tool implementa

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.

Autonomous AI agent platform for building and deploying continuous agents. Use when creating visual workflow agents, deploying persistent autonomous agents, or building complex multi-step AI automation systems.

Design patterns for building autonomous coding agents. Covers tool integration, permission systems, browser automation, and human-in-the-loop workflows. Use when building AI agents, designing tool APIs, implementing permission systems, or creating autonomous coding assistants.

Autonomous agents are AI systems that can independently decompose goals, plan actions, execute tools, and self-correct without constant human guidance. The challenge isn't making them capable - it's making them reliable. Every extra decision multiplies failure probability. This skill covers agent loops (ReAct, Plan-Execute), goal decomposition, reflection patterns, and production reliability. Key insight: compounding error rates kill autonomous agents. A 95% success rate per step drops to 60% b

Expert guidance for fine-tuning LLMs with Axolotl - YAML configs, 100+ models, LoRA/QLoRA, DPO/KTO/ORPO/GRPO, multimodal support

AI operational modes (brainstorm, implement, debug, review, teach, ship, orchestrate). Use to adapt behavior based on task type.

Use this agent to create blog articles for aitmpl.com from Claude Code Templates components. Reads the component, asks the user to confirm details, generates SVG cover, HTML article, and updates blog-articles.json. Examples: <example>Context: User wants a blog for a component. user: 'Create a blog article for cli-tool/components/hooks/security/secret-scanner.json' assistant: 'I'll use the blog-writer agent to create the full blog article with cover image and proper structure' <commentary>The user wants a blog article from a component, use blog-writer for the full pipeline.</commentary></example>

Runs pre-deploy build checks on the dashboard. Validates Astro build, checks for common esbuild/JSX issues, verifies API endpoints compile, and reports errors with fixes. Use before merging PRs that touch dashboard/.

Regenerates the component catalog (docs/components.json) by running the Python script. Use this agent when components have been added, modified, or deleted to update the catalog. Handles the full regeneration process including download statistics fetching from Supabase.

Master guide for using Claude Code effectively. Includes configuration templates, prompting strategies "Thinking" keywords, debugging techniques, and best practices for interacting with the agent.

Clean system caches (npm, Homebrew, Yarn, browsers, Python/ML) to free disk space

CLI interface design specialist. Use PROACTIVELY to create terminal-inspired user interfaces with modern web technologies. Expert in CLI aesthetics, terminal themes, and command-line UX patterns.

Use this agent when creating CLI commands for the claude-code-templates components system. Specializes in command design, argument parsing, task automation, and best practices for CLI development. Examples: <example>Context: User wants to create a new CLI command. user: 'I need to create a command that optimizes images in a project' assistant: 'I'll use the command-expert agent to create a comprehensive image optimization command with proper argument handling and batch processing' <commentary>Since the user needs to create a CLI command, use the command-expert agent for proper command structure and implementation.</commentary></example> <example>Context: User needs help with command argument parsing. user: 'How do I create a command that accepts multiple file patterns?' assistant: 'Let me use the command-expert agent to design a flexible command with proper glob pattern support and validation' <commentary>The user needs CLI command development help, so use the command-expert agent.</commentary></example>

Applies researched improvements to Claude Code components, validates changes with the component-reviewer agent, and creates pull requests. The only agent that modifies files and creates PRs.

Migrates components (agents, commands, skills, hooks, settings, MCPs) from external GitHub repositories to claude-code-templates, validates them with component-reviewer, and regenerates the catalog

Investigates best practices and improvement opportunities for Claude Code components using web search and codebase analysis. Returns structured research reports without modifying files.