agentforge-production

Automate production runtime management for AI agents with decoupled brain, hands, and session logs.

Updated Apr 8, 2026
One-click install
npx skills add https://github.com/Kingxiao/agentforge --skill agentforge-production
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: agentforge-production
Source: https://github.com/Kingxiao/agentforge/tree/main/agentforge-production
Command: npx skills add https://github.com/Kingxiao/agentforge --skill agentforge-production

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Production runtime for agents, decoupling brain, hands, and sessions to improve reliability, scalability, and security in long-running deployments.

Core Features & Use Cases

  • Brain/Hands/Session decoupling: Separate inference, tool execution, and durable event logs to enable crash recovery and horizontal scaling.
  • Lazy provisioning: Provision sandboxes only when needed to reduce latency and resource usage.
  • Observability: Centralized session events and metrics for reliability, cost, and performance monitoring.
  • Credential isolation: Vault-backed secret management to keep credentials out of execution environments.
  • Scaling patterns: Guidelines for single-process to full decoupled architectures across workloads.

Quick Start

Activate the production runtime by enabling Phase 9 patterns (brain/hands/session decoupling, lazy sandbox provisioning, and observability) for your agent.

Frequently Asked Questions about agentforge-production

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

FAQPage Schema
How do I make my AI agent runtime scalable for production?▼

To make an AI agent runtime scalable, decouple inference, tool execution, and session logs. This separation enables horizontal scaling and crash recovery for long-running deployments.

What is brain hands and session decoupling in agent production runtimes?▼

Brain, hands, and session decoupling separates inference, tool execution, and durable event logs. This architecture ensures fault tolerance and enables independent scaling across agent sessions.

How do I isolate credentials when running agents in a sandbox?▼

To isolate credentials in a sandbox, use vault-backed secret management. This keeps credentials completely out of the execution environment, ensuring secure agent production runtime operations.

When do I need lazy sandbox provisioning for AI agents?▼

You need lazy sandbox provisioning when reducing latency and resource usage for agent runtimes. It provisions execution environments only when needed, optimizing production scaling and performance.

How do I get observability across multiple agent sessions and tool calls?▼

Achieve observability across agent sessions and tool calls by using centralized session events and metrics. This monitors reliability, cost, and performance for fault-tolerant production runtimes.

Can I recover an agent session after a crash using event logs?▼

Yes, you can recover an agent session after a crash using durable event logs. Event-driven session replay restores the exact state through the decoupled session architecture.