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Unhappy

Community
educlopez
unhappy

State-first design pass — inventories and implements all non-happy states (loading, empty, error, partial, conflict, offline) before the happy path, and refactors impossible boolean state to proper state machines. Use when starting a new screen, reviewing an existing one for edge-case gaps, or when the user says "handle the error state" / "add loading states" / "what happens when data is missing". Invoke when the user asks for unhappy on their UI, or mentions 'unhappy' alongside design / UI / frontend work.

Overview

Publishereduclopez
Repositoryui-craft
Skill nameunhappy
Stars
344
Forks
17
Bundled files
Instructions only
LicenseMIT
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 educlopez on GitHub. Read the source before you install it.

Installation

Install the Unhappy 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.
  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/educlopez/ui-craft.git /tmp/ui-craft
mkdir -p .claude/skills
cp -r /tmp/ui-craft/cli/assets/codex/skills/unhappy .claude/skills/unhappy
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Unhappy 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 Unhappy 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 Unhappy 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.

Context: this sub-skill is one lens of the broader ui-craft skill. If the ui-craft skill is also installed, read its SKILL.md first for Discovery + Anti-Slop + Craft Test, then apply the specific lens below.

Design every non-happy state for the UI at $ARGUMENTS. Load the ui-craft skill and read references/state-design.md.

Step 1 — Inventory. List every data source and interactive surface in the target. For each, enumerate its states:

Surfaceidleloadingemptyerrorpartialconflictoffline

Mark each cell as designed (exists in code), missing (must add), or N/A (not applicable — e.g., a read-only view has no conflict state).

Step 2 — Fill the missing states. For each missing state, either stub it inline or add a follow-up task comment. Use references/state-design.md for:

  • Skeleton sizing (match final layout, 200ms delay, 5s upper bound)
  • Empty-state copy (why empty + next action + visual)
  • Error-state contract (specific cause + one-click recovery + support ID)
  • Offline handling (queue writes + reconcile on reconnect)

Step 3 — Audit the happy path. Flag every spot where the happy path assumes resource presence without checking. Fix with early-returns, state guards, or discriminated-union state handling. Booleans like isLoading && !error && data that allow impossible states are findings — refactor to a proper state machine or reducer.

Step 4 — Optimistic UI + reconciliation. For offline-likely actions (saves, sends, edits, toggles), implement optimistic UI with reconciliation on reconnect. Queue writes locally. Surface any rejected writes — never swallow them.

Knob gating (CRAFT_LEVEL):

CRAFT_LEVELRequired states to stub
≤ 4idle, loading, error
5-7idle, loading, empty, error, success
8+all six — add partial, conflict, offline

If CRAFT_LEVEL is unknown, default to 7.

Convergence note: To iterate until all required states are present, load skills/ui-craft/references/loops.md and run preset state-coverage (budget = the default loop budget defined in loops.md): after stubbing the highest-priority missing required state, re-inventory until all knob-required states are present or budget exhausted. Emit the pre-flight cost notice before iteration 1.

Output: edit the code directly. After each file, print the Review Format table from SKILL.md:

BeforeAfterWhy
no loading state on <ProjectList>skeleton rows matching final layout, 200ms delayprevents "is it broken?" perception; avoids CLS
generic "Error" toastinline error with specific cause + retry + support IDrecoverability (heuristic 9)

One row per state added. No full diffs.

Next step: /harden — implement the states you just designed (rung 1).

Frequently asked questions

What does the Unhappy AI skill do?

State-first design pass — inventories and implements all non-happy states (loading, empty, error, partial, conflict, offline) before the happy path, and refactors impossible boolean state to proper state machines. Use when starting a new screen, reviewing an existing one for edge-case gaps, or when the user says "handle the error state" / "add loading states" / "what happens when data is missing". Invoke when the user asks for unhappy on their UI, or mentions 'unhappy' alongside design / UI / frontend work.

Why use Unhappy on TypingMind?

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

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/educlopez/ui-craft/tree/main/cli/assets/codex/skills/unhappy. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Unhappy?

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 Unhappy?

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

Is the Unhappy AI skill free?

Yes. It is published on GitHub by educlopez 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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