network-ai

Coordinate multi-framework AI agents with shared state, permissions, and audit logs.

69|12|Updated Feb 4, 2026
One-click install
npx skills add https://github.com/Jovancoding/Network-AI --skill network-ai
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: network-ai
Source: https://github.com/Jovancoding/Network-AI/tree/main
Command: npx skills add https://github.com/Jovancoding/Network-AI --skill network-ai

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes scripts (resource) and references (resource) and assets (resource) components.

What problem does it solve?

This Skill addresses the challenge of coordinating multiple AI agents sharing state, ensuring race condition prevention, enforcing permissions, budgets, and providing audit trails in complex workflows.

Core Features & Use Cases

  • Atomic shared state: Prevents race conditions with propose-validate-commit file-system mutex.
  • Permission gating: Uses cryptographically signed tokens for resource access control.
  • Per-agent token budgets: Enforces token ceilings to prevent runaway costs.
  • Workflow management: FSM-based gating, timeouts, and compliance monitoring.
  • Multi-framework support: Integrates LangChain, AutoGen, CrewAI, MCP, OpenClaw, and custom adapters.
  • Audit trail: Maintains signed logs of permissions, state changes, and violations.
  • Persistent project context: Layer-3 memory injection for goal, milestone, and decision continuity.
  • Advanced modules: Agent VCR, comparison runner, coverage report, agent sandbox runtime, and versatile CLI.

Quick Start

Use Network-AI to orchestrate a multi-agent workflow with atomic blackboard updates, enforce budgets and permissions, and monitor compliance, enabling safe and transparent AI pipeline management.

Frequently Asked Questions about network-ai

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

FAQPage Schema
How do I prevent race conditions when multiple AI agents share state in a complex workflow?

Multi-agent shared state race conditions are prevented using a propose-validate-commit file-system mutex. This atomic blackboard update mechanism ensures that concurrent agents cannot overwrite each other's changes during complex workflows.

Does multi-agent orchestration work with LangChain, AutoGen, and CrewAI frameworks?

Multi-agent orchestration works with LangChain, AutoGen, CrewAI, MCP, and OpenClaw frameworks. The system integrates these platforms using custom adapters to coordinate shared state and permissions across different environments.

Can I enforce per-agent token budgets to prevent runaway costs in AI pipelines?

Per-agent token budgets are enforceable to prevent runaway costs in AI pipelines. The system sets strict token ceilings for each agent, halting execution when the allocated budget is exceeded.

What is the best way to maintain an audit trail for AI agent permissions and state changes?

The best way to maintain an audit trail for AI agent permissions and state changes is through cryptographically signed logs. These logs record all permission grants, state transitions, and violations for full compliance monitoring.

How do I control resource access permissions across multiple coordinating AI agents?

Resource access permissions across multiple coordinating AI agents are controlled using cryptographically signed tokens. This permission gating mechanism ensures that only authorized agents can access specific resources during execution.

When should I use finite state machine gating for multi-agent workflow management?

Finite state machine gating for multi-agent workflow management should be used when you need strict timeouts, compliance monitoring, and ordered state transitions. It ensures agents follow predefined workflow paths without unauthorized deviations.