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Improve Codebase Architecture

Community
mart337i
improve-codebase-architecture

Find deepening opportunities in a codebase, informed by the domain language in CONTEXT.md and the decisions in docs/adr/. Use when the user wants to improve architecture, find refactoring opportunities, consolidate tightly-coupled modules, or make a codebase more testable and AI-navigable.

Overview

Publishermart337i
Repositoryodoo-skills
Skill nameimprove-codebase-architecture
Stars
61
Forks
15
Bundled files
3
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.

  • 3 bundled files

    Scripts, templates, and references the model can read while it works. Files are read-only and never executed.

  • Open source

    Published by mart337i on GitHub. Read the source before you install it.

Installation

Install the Improve Codebase 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/mart337i/odoo-skills/tree/main/skills/improve-codebase-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/mart337i/odoo-skills.git /tmp/odoo-skills
mkdir -p .claude/skills
cp -r /tmp/odoo-skills/skills/improve-codebase-architecture .claude/skills/improve-codebase-architecture
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Improve Codebase 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 Improve Codebase 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 Improve Codebase 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.

Improve Codebase Architecture

Surface architectural friction and propose deepening opportunities: refactors that turn shallow modules into deep ones. The aim is testability and AI-navigability.

Glossary

Use these terms exactly in every suggestion. Full definitions are in LANGUAGE.md.

  • Module: anything with an interface and an implementation.
  • Interface: everything a caller must know to use the module correctly.
  • Implementation: the code inside.
  • Depth: leverage at the interface. Deep means high leverage; shallow means the interface is nearly as complex as the implementation.
  • Seam: where an interface lives; a place behavior can be altered without editing in place.
  • Adapter: a concrete thing satisfying an interface at a seam.
  • Leverage: what callers get from depth.
  • Locality: what maintainers get from depth.

Key principles:

  • Deletion test: imagine deleting the module. If complexity vanishes, it was a pass-through. If complexity reappears across many callers, it was earning its keep.
  • The interface is the test surface.
  • One adapter means a hypothetical seam. Two adapters means a real seam.

Process

1. Explore

Read the project's domain glossary and any ADRs in the area first. Then inspect the codebase organically and note where understanding creates friction:

  • Where does understanding one concept require bouncing between many small modules?
  • Where are modules shallow?
  • Where have pure functions been extracted only for testability, while real bugs hide in how they are called?
  • Where do tightly-coupled modules leak across seams?
  • Which parts are untested, or hard to test through their current interface?

Apply the deletion test to anything suspected of being shallow.

2. Present Candidates

Present a numbered list of deepening opportunities. For each candidate include:

  • Files: which files/modules are involved.
  • Problem: why current architecture causes friction.
  • Solution: plain-English description of what would change.
  • Benefits: explain locality, leverage, and how tests would improve.

Use CONTEXT.md vocabulary for the domain and LANGUAGE.md vocabulary for architecture. If a candidate contradicts an existing ADR, only surface it when the friction is real enough to warrant revisiting that ADR.

Do not propose interfaces yet. Ask: "Which of these would you like to explore?"

3. Grilling Loop

Once the user picks a candidate, walk the design tree: constraints, dependencies, the shape of the deepened module, what sits behind the seam, and what tests survive.

Side effects happen inline as decisions crystallize:

  • If naming a deepened module after a concept not in CONTEXT.md, add the term using CONTEXT-FORMAT.md.
  • If sharpening a fuzzy term, update CONTEXT.md immediately.
  • If the user rejects the candidate with a load-bearing reason, offer an ADR using ADR-FORMAT.md.
  • If exploring alternative interfaces, use INTERFACE-DESIGN.md.

Bundled files

The model reads these on demand while the skill is loaded. They are exposed as readable files and are never executed.

Frequently asked questions

What does the Improve Codebase Architecture AI skill do?

Find deepening opportunities in a codebase, informed by the domain language in CONTEXT.md and the decisions in docs/adr/. Use when the user wants to improve architecture, find refactoring opportunities, consolidate tightly-coupled modules, or make a codebase more testable and AI-navigable.

Why use Improve Codebase Architecture on TypingMind?

Because you install it once and use it with any model. Improve Codebase 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 Improve Codebase Architecture in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/mart337i/odoo-skills/tree/main/skills/improve-codebase-architecture. TypingMind reads its SKILL.md and bundles its files and installs it as a skill you can enable per chat.

Which AI models can use Improve Codebase 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 Improve Codebase Architecture?

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

Is the Improve Codebase Architecture AI skill free?

It is published on GitHub by mart337i. 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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