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Improvement

OrganizationPopular
tddworks
improvement

Guide for making improvements to existing ClaudeBar functionality using TDD. Use this skill when: (1) Enhancing existing features (not adding new ones) (2) Improving UX, performance, or code quality (3) User asks "improve X", "make Y better", or "enhance Z" (4) Small enhancements that don't require full architecture design For NEW features, use implement-feature skill instead.

Overview

Publishertddworks
RepositoryClaudeBar
Skill nameimprovement
Stars
1.5K
Forks
153
Bundled files
Instructions only
LicenseApache-2.0
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 tddworks on GitHub. Read the source before you install it.

Installation

Install the Improvement 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/tddworks/ClaudeBar/tree/main/.claude/skills/improvement
  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/tddworks/ClaudeBar.git /tmp/ClaudeBar
mkdir -p .claude/skills
cp -r /tmp/ClaudeBar/.claude/skills/improvement .claude/skills/improvement
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Improvement 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 Improvement 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 Improvement 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 ClaudeBar Feature

Make improvements to existing functionality using TDD and rich domain design.

When to Use This vs Other Skills

ScenarioSkill to Use
Enhance existing behaviorimprovement (this skill)
Fix broken behaviorfix-bug
Add new featureimplement-feature
Add new AI provideradd-provider
A new report card over usage historyadd-report

Workflow

┌─────────────────────────────────────────────────────────────┐
│  0. CHECK THE DESIGN (docs are the source of truth)          │
├─────────────────────────────────────────────────────────────┤
│  • Read USER_JOURNEYS, CANONICAL, TARGET, design.md          │
│  • Think the domain: how should it be? (domain-shape.md)     │
│  • Does the improvement change a law, an owner, a word?      │
│  • If so: write it into the docs, ask the user to confirm    │
└─────────────────────────────────────────────────────────────┘
                            │
                            ▼ (design confirmed, or unchanged)
┌─────────────────────────────────────────────────────────────┐
│  1. UNDERSTAND CURRENT STATE                                 │
├─────────────────────────────────────────────────────────────┤
│  • Read existing code                                        │
│  • Understand current behavior                               │
│  • Identify what to improve                                  │
└─────────────────────────────────────────────────────────────┘
                            │
                            ▼
┌─────────────────────────────────────────────────────────────┐
│  2. WRITE TEST FOR IMPROVED BEHAVIOR (Red)                   │
├─────────────────────────────────────────────────────────────┤
│  • Test describes the IMPROVED behavior                      │
│  • Test should FAIL initially                                │
│  • Keep existing tests passing                               │
└─────────────────────────────────────────────────────────────┘
                            │
                            ▼
┌─────────────────────────────────────────────────────────────┐
│  3. IMPLEMENT & VERIFY (Green)                               │
├─────────────────────────────────────────────────────────────┤
│  • Implement the improvement                                 │
│  • New test PASSES                                           │
│  • All existing tests still pass                             │
└─────────────────────────────────────────────────────────────┘

Phase 0: Check the design

The design docs are the source of truth (AGENTS.md). Read the design in order — USER_JOURNEYS.md, CANONICAL_MODEL.md, TARGET_ARCHITECTURE.md, then the feature's design.md. An improvement that only makes the code match the docs needs no approval. One that changes a law, its owner, a word the screen prints, or adds a piece is a design change: write it into the docs and ask the user to confirm before coding.

Think the domain first. Before changing code, ask how the domain should be, from the person's problem rather than the class at hand. Ask the five questions of the types the improvement touches (would the person say it, does the thing decide about itself, can you see every state, is it as small as it can be, is what differs data) and refine them in the same change → domain-shape.md. An improvement is the usual moment to fit a type to its shape; a new aggregate or a moved owner is a design change, confirmed first.

Types of Improvements

1. UX Improvements

Enhance user experience without changing core logic:

Examples:
- Settings view scrolls on small screens
- Better loading indicators
- Improved accessibility
- Cleaner visual layout

Test approach: a mockup in design-concept/<feature>/ first for a visible change, then the real UI on mock data (scripts/demo-screenshots.sh) — never real names, emails or usage. Views render and tell; a rule they need lives in the domain.

2. Domain Improvements

Enhance a rule on the type that owns it (CANONICAL §5) — tell, don't ask:

Examples:
- A status the view used to work out moves onto its owner
- A better status calculation
- Better encapsulation of an invariant

Never a new field on UsageSnapshot: the kernel is shrinking toward Usage (CANONICAL §6). Put the rule on the value or aggregate that owns it.

Test approach: State-based tests on the owner

swift
@Test func `should be critical when a tenth is left`() {
    let quota = UsageQuota(percentRemaining: 10, quotaType: .session, providerId: "claude")
    #expect(quota.status == .critical)
}

3. Data Source Improvements

Make fetching or reading usage better: a provider's definition, or a generic worker in DataSources that every definition can use:

Examples:
- Better error messages (a `text` mapping's error phrases, a `UsageError` hint)
- More robust reading (a new JSON mapping rule instead of a script)
- Timeouts, `cache.ttl`, a remembered rate limit
- A fallback or hand-off (`fallback`, `fallbackOn`)

Test approach: golden tests that run the real definition over stubbed connections (StubbedProvider), or worker tests in Modules/DataSources/Tests/. Never a vendor-named Swift type: improve the definition, or the generic piece.

4. Performance Improvements

Optimize existing functionality:

Examples:
- Reduce redundant API calls
- Lazy loading
- Parallel execution
- Caching

Test approach: Behavior tests (same results, better performance)

TDD Pattern (Chicago School)

Name each test should <outcome> [when <situation>], in the person's words, never a method, type or mechanism verb → Naming tests.

Write Test for Improved Behavior

swift
@Suite
struct {Component}Tests {

    @Test func `should {improved outcome} [when {situation}]`() {
        // Given - standard setup
        let component = Component(...)

        // When - action
        let result = component.improvedMethod()

        // Then - verify improved behavior
        #expect(result.hasImprovedProperty)
    }
}

Keep Existing Tests

Improvements should NOT break existing behavior:

bash
tuist test Providers         # one module's tests while working (schemes: Providers, DataSources, Domain, Infrastructure, AppTests, AcceptanceTests)
# tuist caches results; one suite for real, and the final check of everything:
xcodebuild test -workspace ClaudeBar.xcworkspace -scheme ClaudeBar-Workspace \
  -destination 'platform=macOS,arch=arm64' -only-testing:ProvidersTests/ClaudeAPITests
xcodebuild test -workspace ClaudeBar.xcworkspace -scheme ClaudeBar-Workspace -destination 'platform=macOS,arch=arm64'

Architecture Reference

Reference: MODULAR_DESIGN.md (modules) · TARGET_ARCHITECTURE.md (how a provider runs) · ARCHITECTURE.md (the app layers)

Find which module the behaviour lives in before you change it: the table in implement-feature → Architecture is the one map (where each thing lives, and where its tests go).

A bug or improvement in a provider is made in its JSON (or its mapping script), or generically in DataSources — never with vendor-named Swift, and never with a line in ClaudeBarApp that names it (providers are found by ProviderCatalog.detect()). Modules never import Domain.

Guidelines

Do

  • Keep changes focused and minimal
  • Maintain existing behavior
  • Add tests for new behavior
  • Follow existing code patterns
  • Add the CHANGELOG line for a change the person notices

Don't

  • Over-engineer simple improvements
  • Change unrelated code
  • Break existing tests
  • Add features (use implement-feature)
  • Skip tests for "small" changes

Checklist

  • Current behavior understood
  • Domain thought through: the touched types asked the five questions, refined in scope
  • Improvement scope defined (minimal)
  • Test for improved behavior written
  • Test FAILS before implementation
  • Improvement implemented
  • New test PASSES
  • Full xcodebuild test green (tuist test skips cached targets)
  • Docs updated in the same change (feature or provider README / design.md)
  • One line under ## [Unreleased] in CHANGELOG.md, under its heading (Fixed / Changed): the effect in the person's words, ≤300 characters, an absolute issue or PR link, for a change the person notices

Frequently asked questions

What does the Improvement AI skill do?

Guide for making improvements to existing ClaudeBar functionality using TDD. Use this skill when: (1) Enhancing existing features (not adding new ones) (2) Improving UX, performance, or code quality (3) User asks "improve X", "make Y better", or "enhance Z" (4) Small enhancements that don't require full architecture design For NEW features, use implement-feature skill instead.

Why use Improvement on TypingMind?

Because you install it once and use it with any model. Improvement 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 Improvement in TypingMind?

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

Which AI models can use Improvement?

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 Improvement?

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

Is the Improvement AI skill free?

Yes. It is published on GitHub by tddworks under the Apache-2.0 license. 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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