architecture

Document system architecture covering Java components, STDIO transport, batching patterns, crawler internals, and MCP token budgets.

5|2|Updated Jan 27, 2026
One-click install
npx skills add https://github.com/mirkosertic/MCPLuceneServer --skill architecture-mirkosertic
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: architecture
Source: https://github.com/mirkosertic/MCPLuceneServer/tree/main/.claude/skills/architecture
Command: npx skills add https://github.com/mirkosertic/MCPLuceneServer --skill architecture-mirkosertic

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes references (resource) components.

What problem does it solve?

This Skill provides deep insights into the system's architecture, design choices, and processing patterns, enabling a thorough understanding of its internal workings and rationale.

Core Features & Use Cases

  • Architecture Deep Dive: Explains the system's components, communication protocols, and design decisions (e.g., why plain Java, STDIO transport).
  • Processing Patterns: Details how data is processed, including batching, NRT optimization, and configuration priorities.
  • Crawler Architecture: Outlines the layered structure of the document crawler service.
  • MCP Response Token Budget: Guides on optimizing response sizes for AI client efficiency.
  • Use Case: When planning a new feature, use this Skill to understand existing architectural constraints and how components interact, ensuring your changes align with the system's design.

Quick Start

Explain the system's architecture and key design decisions.

Frequently Asked Questions about architecture

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

FAQPage Schema
How do I document system architecture design decisions for plain Java and STDIO transport?

System architecture design decisions for plain Java and STDIO transport are documented by detailing the rationale behind technology choices, communication protocols, and component interactions to ensure changes align with the system's design.

What are MCP response token budgets and how do they affect AI client efficiency?

MCP response token budgets constrain the response size sent to AI clients. Optimizing these budgets ensures efficient processing by preventing token limit overflows during system communication.

How does batching and NRT optimization work in processing patterns?

Batching and NRT (Near Real-Time) optimization processing patterns work by grouping data operations to balance throughput and latency, detailed within the system's architectural documentation to guide implementation.

How do I understand crawler architecture for document processing?

Crawler architecture for document processing is understood by reviewing its layered service structure, which outlines how the crawler interacts with internal components and manages data extraction workflows.

Does this architecture documentation explain configuration priorities for processing patterns?

Yes, the architecture documentation explains configuration priorities for processing patterns, detailing how the system ranks and applies different settings to manage batching and NRT optimization effectively.

When should I review system internals before planning a new feature?

You should review system internals before planning a new feature when you need to understand existing architectural constraints, ensuring your proposed changes align with the system's design and processing patterns.