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ShenQingchuan
ShenQingchuanCOMMUNITY
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locus-agent-sdk

Define runtime contracts, hooks, plugins, and prompt utilities for Locus Agent workflows.

21|1|Updated Feb 6, 2026
Search Tags:#developer tools#hooks#sdk#runtime#ai agent#plugin system
One-click install
npx skills add https://github.com/ShenQingchuan/locus-agent --skill locus-agent-sdk
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: locus-agent-sdk
Source: https://github.com/ShenQingchuan/locus-agent/tree/main/packages/agent-sdk/skills/locus-agent-sdk
Command: npx skills add https://github.com/ShenQingchuan/locus-agent --skill locus-agent-sdk

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

This Skill provides the foundational contracts and utilities for building and extending AI agents within the Locus Agent framework, simplifying the development of agentic workflows.

Core Features & Use Cases

  • Runtime Contracts: Defines interfaces for agent loops, tool execution, and delegation.
  • Hook System: Enables agents to react to and modify lifecycle events.
  • Plugin Architecture: Facilitates modular extension of agent capabilities.
  • Context & Prompt Management: Offers utilities for managing conversation history and constructing prompts.
  • Use Case: Developers can use this SDK to create custom tools, integrate new AI models, or build complex agent behaviors that interact with the Locus Agent runtime.

Quick Start

Import types and utilities directly from '@univedge/locus-agent-sdk' for agent development.

Frequently Asked Questions about locus-agent-sdk

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

FAQPage Schema
How do I build modular AI agents with a hook system and plugin architecture?▼

To build modular AI agents with a hook system and plugin architecture, use this SDK to access runtime interfaces, lifecycle event models, and standardized plugin contracts for extending agentic workflows.

What is the best way to manage context and conversation history for AI agent development?▼

The best way to manage context and conversation history for AI agent development is using SDK utilities designed for context and prompt management within the agent runtime.

Does this AI agent SDK support custom tool integration and execution?▼

Yes, this AI agent SDK supports custom tool integration and execution by providing shared runtime contracts and interfaces for tool execution and agent delegation.

Can I use this framework to create custom tools and integrate new AI models?▼

You can use this framework to create custom tools and integrate new AI models by leveraging its modularity, extensibility, and standardized agentic workflow development utilities.

What are the limitations of building agent workflows without a standardized SDK?▼

Without a standardized SDK, building agent workflows risks lacking modularity and extensibility, making it difficult to react to lifecycle events or integrate new tools consistently.

How do I extend agent capabilities using lifecycle hook events?▼

You extend agent capabilities using lifecycle hook events by importing the hook event models from the SDK, enabling agents to react to and modify runtime events during execution.

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