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Software Architecture

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krishnakanthb13
software_architecture

Guide for quality-focused software architecture. Use this when designing architecture, writing code, or analyzing software systems.

Overview

Publisherkrishnakanthb13
Repositoryantigravity_global_skills
Skill namesoftware_architecture
Stars
66
Forks
11
Bundled files
Instructions only
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • Self-contained

    Everything the model needs lives in the instructions — no extra files to sync.

  • Open source

    Published by krishnakanthb13 on GitHub. Read the source before you install it.

Installation

Install the Software Architecture AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
    https://github.com/krishnakanthb13/antigravity_global_skills/tree/main/software_architecture
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/krishnakanthb13/antigravity_global_skills.git /tmp/antigravity_global_skills
mkdir -p .claude/skills
cp -r /tmp/antigravity_global_skills/software_architecture .claude/skills/software_architecture
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Software Architecture in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Software Architecture on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Software Architecture is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

Software Architecture

This skill provides guidance for quality-focused software development and architecture. It focuses on Clean Architecture and Domain-Driven Design principles.

Core Rules & Principles

  1. Early Return Pattern: Always use early returns when possible over nested conditions.
  2. Decompose Components: Break down components longer than 80 lines and split files larger than 200 lines.
  3. Library-First Approach:
    • ALWAYS search for existing solutions before writing custom code.
    • Use libraries for common problems (retry logic, state management, validation).
  4. Clean Architecture & DDD:
    • Separate domain entities from infrastructure. Keep business logic independent of frameworks.
  5. Naming & Bounded Contexts:
    • AVOID generic names (utils, helpers, common, shared).
    • USE domain-specific names (OrderCalculator, InvoiceGenerator).
  6. Separation of Concerns:
    • Do NOT mix business logic with UI components.
    • Keep database queries out of controllers.
  7. SOLID Principles:
    • Single Responsibility: A class should have one reason to change. Decompose large monoliths.
    • Open/Closed: Design for extension without modifying existing source code (e.g., plugins, inheritance).
    • Liskov Substitution: Subclasses must be interchangeable with their base classes.
    • Interface Segregation: Prefer many specific interfaces over one general-purpose interface.
    • Dependency Inversion: Depend on abstractions (interfaces/abstract classes), not concrete implementations.

Anti-Patterns to Avoid

  • NIH (Not Invented Here) Syndrome: Don't build custom auth when Auth0 exists.
  • Dumping Grounds: Don't create utils.js or shared.js with lots of unrelated functions. Every module should have a single, clear purpose.

Architecture Decision Records (ADRs)

Document every architectural decision with trade-offs. If making a significant decision, use the following framework:

ADR Template

markdown
# ADR-[XXX]: [Decision Title]

## Status
Proposed | Accepted | Deprecated | Superseded by [ADR-YYY]

## Context
- **Problem**: [What problem are we solving?]
- **Constraints**: [Team size, scale, timeline, budget]

## Options Considered
| Option | Pros | Cons | Complexity |
|--------|------|------|------------|
| Opt A  | ...  | ...  | Low/High   |

## Decision
[What we chose - be specific]

## Rationale
[Why - tie to requirements and constraints]

## Consequences
- **Positive**: [Benefits we gain]
- **Negative**: [Costs/risks we accept]
- **Mitigation**: [How we'll address negatives]

## Revisit Trigger
- [When to reconsider this decision]

Storage

Store these records sequentially in docs/architecture/ (e.g., adr-001-use-nextjs.md).

Frequently asked questions

What does the Software Architecture AI skill do?

Guide for quality-focused software architecture. Use this when designing architecture, writing code, or analyzing software systems.

Why use Software Architecture on TypingMind?

Because you install it once and use it with any model. Software Architecture is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Software Architecture in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/krishnakanthb13/antigravity_global_skills/tree/main/software_architecture. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Software Architecture?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Software Architecture?

As many as you like. As long as a model supports skills, you can use Software Architecture with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Software Architecture AI skill free?

It is published on GitHub by krishnakanthb13. Check the repository for licensing terms. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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