architecture-registries

Consolidate and validate Think TARS agent, automation, and settings registries.

Updated Aug 23, 2026
One-click install
npx skills add https://github.com/freddomingues/think-tars --skill architecture-registries
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: architecture-registries
Source: https://github.com/freddomingues/think-tars/tree/main/.cursor/skills/architecture-registries
Command: npx skills add https://github.com/freddomingues/think-tars --skill architecture-registries

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Este Skill facilita a gestão da arquitetura de registries e configuração do Think TARS, consolidando informações sobre registries de agentes, automações e configurações do sistema.

Core Features & Use Cases

  • Gerenciamento consolidado de registries de agentes (playground e internos) e a fonte da verdade para prompts e ferramentas.
  • Configuração centralizada de automations (config/automations.py) e settings, com suporte a reexports entre ai/agents.py e config/settings.py.
  • Procedimentos consistentes de atualização ao alterar registries, automations ou settings.

Quick Start

Liste todos os registries de agentes (AGENTS_REGISTRY e INTERNAL_AGENTS_REGISTRY) e verifique o DEFAULT_AGENT_ID; assegure a integridade da re-exportação e, se necessário, adicione uma nova entrada de agente Playground com prompts/ferramentas correspondentes.

Frequently Asked Questions about architecture-registries

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I centralize agent configuration and registry management in Think TARS?

Agent configuration and registry management are centralized by consolidating AGENTS_REGISTRY and INTERNAL_AGENTS_REGISTRY entries, validating the DEFAULT_AGENT_ID, and ensuring consistent configuration across environments.

What is the best way to update automation routes and settings in a Python configuration?

Updating automation routes and settings is done by modifying config/automations.py and config/settings.py, applying consistent procedures to maintain re-export compatibility between ai/agents.py and config/settings.py.

How do I onboard a new playground agent with prompts and tools in a centralized registry?

Onboarding a new playground agent involves adding a corresponding entry to the AGENTS_REGISTRY alongside its specific prompts and tools, then verifying the integrity of the re-export configuration.

Why does get_agent_config or get_automation_handler require re-export compatibility?

Re-export compatibility is required to satisfy get_agent_config and get_automation_handler functions, ensuring that agents and automations maintain consistent configuration and functional routing across module boundaries.

Can I use this skill to maintain repository configuration across multiple environments?

Yes, this skill applies to repository maintenance by consolidating and validating registries and settings, ensuring that agent configurations and automation routes remain consistent across different deployment environments.

What are the limitations of consolidating registries through config/settings.py?

Consolidating registries requires careful adherence to re-export compatibility between ai/agents.py and config/settings.py; inconsistencies in these configuration files can disrupt automation handlers and agent routing.