create-agent

Generating a custom Claude agent from natural language involves processing a text prompt to automatically scaffold all required definition files, including agent.md, context.md, tools.md, behavior.md, memory-keys.json, and meta.json, producing a production-ready agent structure.

Automated agent scaffolding is the process of creating a standardized directory structure with necessary configuration files for a new agent. It streamlines Claude workflows by eliminating manual file creation, enforcing validation, and enabling rapid deployment of domain-specific agents.

Yes, you can use natural language to scaffold agents for specific domain tasks. By describing the desired functionality, such as a sentiment-analysis agent, the system generates a ready-to-run scaffold that can be extended with domain-specific rules and tools.

Yes, the generated agent scaffolding handles name collisions and validation. It sanitizes the provided agent name to a safe slug, checks for existing agents to avoid directory conflicts, and registers the new agent with MemoryGraph for discovery across sessions.

Custom agent definitions generated from text prompts are stored under the .claude/agents/custom/{name}/ directory. This standardized structure ensures all agent files, including metadata and memory keys, are organized for deployment and reuse.

The best way to create reusable agents across different Claude sessions is to generate a production-ready scaffold with integrated MemoryGraph registration. This approach ensures the agent is discoverable and its state persists, enabling rapid scaffolding and reuse.