State Machine

Organization

WellApp-ai

state-machine

Document UI component states (current vs expected) with transitions

Overview

Publisher	WellApp-ai
Repository	`Well`
Skill name	`state-machine`
Stars	342
Forks	48
Bundled files	Instructions only
License	MIT
Links	Skill source Repository Homepage

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 WellApp-ai on GitHub. Read the source before you install it.

Installation

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

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.

Open the app and go to Plugins → Skills.
Choose "Install from GitHub".
Paste the skill folder URL below and confirm.
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.

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/WellApp-ai/Well.git /tmp/Well
mkdir -p .claude/skills
cp -r /tmp/Well/cursor-rules/skills/state-machine .claude/skills/state-machine

Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable State Machine 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 State Machine 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 State Machine 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.

State Machine Skill

Document the state machine for UI components, comparing current behavior to expected behavior and mapping all state transitions.

When to Use

During Ask mode CONVERGE loop for stateful components
When refactoring existing components with complex state
Before implementing new interactive UI components

Instructions

Phase 1: Identify States

List all possible states for the component:

State	Current Behavior	Expected Behavior
Initial	[What happens now]	[What should happen]
Loading	[Current loading UX]	[Expected loading UX]
Success	[Current success display]	[Expected success display]
Error	[Current error handling]	[Expected error handling]
Empty	[Current empty state]	[Expected empty state]

Common States to Consider:

State Type	Examples
Data states	Initial, Loading, Success, Error, Empty, Stale
Interaction states	Idle, Hover, Focus, Active, Disabled
Visibility states	Hidden, Visible, Collapsed, Expanded
Selection states	Unselected, Selected, Partially selected
Validation states	Valid, Invalid, Pending validation

Phase 2: Map Transitions

Define what triggers each state change:

From	To	Trigger	Side Effects
Initial	Loading	User action / Mount	Start fetch
Loading	Success	Data received	Populate UI
Loading	Error	Request failed	Show error message
Loading	Empty	Empty response	Show empty state
Error	Loading	Retry clicked	Restart fetch
Success	Loading	Refresh clicked	Refetch data

Phase 3: State Diagram

Create a Mermaid state diagram:

mermaid
stateDiagram-v2
    [*] --> Initial
    Initial --> Loading : fetch
    Loading --> Success : data received
    Loading --> Error : request failed
    Loading --> Empty : no data
    Error --> Loading : retry
    Success --> Loading : refresh
    Empty --> Loading : refresh
    Success --> [*] : unmount

Phase 4: Data Requirements

For each state, define what data is needed:

State	Required Data	UI Elements
Initial	None	Placeholder or skeleton
Loading	None	Spinner, skeleton, progress
Success	[List required fields]	Full component
Error	Error message, retry action	Error banner, retry button
Empty	Empty message, CTA	Empty illustration, CTA button

Phase 5: Edge Cases

Identify edge cases and how to handle:

Edge Case	Current	Expected
Network timeout	[Current]	Show timeout message, retry option
Partial data	[Current]	Graceful degradation, show available
Stale data	[Current]	Show stale indicator, background refresh
Concurrent updates	[Current]	Optimistic update, rollback on conflict
Auth expired	[Current]	Redirect to login, preserve state

Output Format

markdown
## State Machine: [Component Name]

### State Table

| State | Current | Expected | Data Required |
|-------|---------|----------|---------------|
| Initial | [Behavior] | [Behavior] | [Data] |
| Loading | [Behavior] | [Behavior] | [Data] |
| Success | [Behavior] | [Behavior] | [Data] |
| Error | [Behavior] | [Behavior] | [Data] |
| Empty | [Behavior] | [Behavior] | [Data] |

### Transition Diagram

[Mermaid stateDiagram]

### Edge Cases

| Case | Handling |
|------|----------|
| [Case] | [How to handle] |

### Summary
- States: [N] identified
- Transitions: [N] mapped
- Edge cases: [N] documented

Invocation

Invoke manually with "use state-machine skill" or follow Ask mode CONVERGE loop which references this skill.

Related Skills

qa-planning - Uses states to define test coverage
design-context - Check existing component states in Storybook

Frequently asked questions

What does the State Machine AI skill do?

Document UI component states (current vs expected) with transitions

Why use State Machine on TypingMind?

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

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/WellApp-ai/Well/tree/main/cursor-rules/skills/state-machine. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use State Machine?

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 State Machine?

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

Is the State Machine AI skill free?

Yes. It is published on GitHub by WellApp-ai under the MIT 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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Overview

Installation

Install in TypingMind

Install in another agent

Use it in TypingMind

Works with any AI model

Skill instructions

State Machine Skill

When to Use

Instructions

Phase 1: Identify States

Phase 2: Map Transitions

Phase 3: State Diagram

Phase 4: Data Requirements

Phase 5: Edge Cases

Output Format

Invocation

Related Skills

Frequently asked questions

Related AI Skills

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