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hive-concepts

Explain core Hive concepts for goal-driven agent architecture.

10.9k|5.7k|Updated Jan 12, 2026
Search Tags:#workflow#architecture#tool-discovery#node-types#goal-driven#event_loop#agent-concepts
One-click install
npx skills add https://github.com/aden-hive/hive --skill hive-concepts-aden-hive
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: hive-concepts
Source: https://github.com/aden-hive/hive/tree/main/.claude/skills/hive-concepts
Command: npx skills add https://github.com/aden-hive/hive --skill hive-concepts-aden-hive

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Clarifies foundational concepts, architecture, and workflow required to design and implement goal-driven agents.

Core Features & Use Cases

  • Architecture overview: Python package layout and how components map to agent creation and operation.
  • Node and edge concepts: event_loop vs function nodes, client-facing behavior, and edge conditions.
  • Tool discovery and workflow: discovering, validating, and wiring tools into graph execution.
  • Educational use: onboarding teams and prototyping new agent projects.

Quick Start

Review the hive-concepts material and begin scaffolding a Python package for your agent following the architecture described.

Frequently Asked Questions about hive-concepts

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

FAQPage Schema
How do I structure a Python package for a goal-driven agent?▼

Structuring a Python package for a goal-driven agent involves mapping components to agent creation and operation. The architecture defines a specific package layout to support node behavior, edge conditions, and tool integration within the execution workflow.

What is the difference between event_loop and function nodes in agent workflows?▼

In agent workflows, event_loop nodes and function nodes differ primarily in client-facing behavior and execution conditions. Event loops manage iterative processing, while function nodes handle discrete operations, connected by edges that define specific graph execution conditions.

How does tool discovery work when wiring tools into graph execution?▼

Tool discovery works by systematically finding and validating tools before wiring them into graph execution. This workflow ensures that only properly validated tools are integrated into the goal-driven agent architecture, maintaining stable operation throughout the workflow.

Can I use these hive architecture concepts for onboarding a development team?▼

Yes, these hive architecture concepts are designed for onboarding development teams. The documentation clarifies foundational concepts and workflow, making it suitable for educating teams and prototyping new goal-driven agent projects effectively.

What are edge conditions in a goal-driven agent architecture?▼

Edge conditions in a goal-driven agent architecture define the rules and logic connecting event_loop and function nodes. They determine the flow of graph execution, specifying how the agent transitions between different operational states and tool integrations.

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