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Critique

Community
Tranz007
critique

Review and compare UX designs, flows, prototypes, specifications, or implementations against user goals, evidence, interaction behavior, accessibility, design-system fit, content, and engineering intent. Use when a designer asks for critique, comparison, tough feedback, review before approval, or wants to check whether implementation preserved the intended experience.

Overview

PublisherTranz007
Repositoryux-skills
Skill namecritique
Stars
48
Forks
4
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 Tranz007 on GitHub. Read the source before you install it.

Installation

Install the Critique 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/Tranz007/ux-skills/tree/main/skills/critique
  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/Tranz007/ux-skills.git /tmp/ux-skills
mkdir -p .claude/skills
cp -r /tmp/ux-skills/skills/critique .claude/skills/critique
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Critique 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 Critique 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 Critique 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.

Critique

Review the work against its context and intent rather than personal taste.

Always

  • Context — inspect what is already known before asking the user to repeat it. Use .ux/INTENT.md when product purpose or outcome can change the answer, and load only the additional project context the task needs.
  • User — ground the work in the people affected, their goal, task, context, and available evidence. Do not invent user needs, behaviors, or personas.
  • Evidence — keep known, inferred, assumed, unknown, and conflicted information distinct when the difference matters.
  • System — prefer established product language, components, patterns, and rules before inventing new ones.
  • Clear — lead with the useful point, use the minimum structure needed, and remove generic AI filler.
  • Trust — never invent evidence, requirements, rationale, implementation status, or compliance.
  • Outcome — for substantial multi-step work, keep intent active, use a small .ux/STATE.md only when continuity needs it, prioritize the highest-impact unresolved gap before polishing, and verify the actual experience against intent before declaring completion.

Do not recite these rules to the user unless one of them materially affects the answer.

Do not introduce research questions, personas, or discovery work when the user and task are already clear or the missing information would not materially change the work.

Establish the basis

Inspect the artifact plus the smallest relevant .ux/ context, evidence, design-system patterns, accessibility rules, known constraints, and prior decisions. If reviewing implementation, inspect the actual code/diff as well as the intended UX source.

If the goal is unclear, state any cautious inference before critiquing against it, or ask only if the critique would otherwise be misleading.

Review through relevant lenses

Use only lenses that matter to this work:

  • user goal and task clarity;
  • evidence and unsupported assumptions;
  • information hierarchy and cognitive effort;
  • interaction behavior, branches, interruption, and recovery;
  • state completeness;
  • content and terminology;
  • accessibility and inclusive use;
  • consistency and design-system fit;
  • engineering or service dependencies;
  • trust, privacy, or consequence where relevant.

Compare when needed

When reviewing multiple options, derive the important decision criteria from the actual problem and evaluate each option against the same criteria. Do not turn the comparison into a beauty contest. "Neither" is a valid recommendation.

Review implementation drift

When the artifact is code or a PR, look for UX behavior that changed or disappeared: states, recovery, persistence, content, design-system usage, focus/keyboard behavior, or acceptance intent.

A diff does not prove runtime behavior. Say what still needs to be verified rather than presenting inference as fact.

Prioritize findings

Lead with issues likely to cause failure, exclusion, loss, misunderstanding, or significant implementation drift. Put polish later.

Point to the behavior or element, explain why it matters, and recommend a direction. Avoid vague comments such as "improve hierarchy" without saying what is wrong.

When the work is strong, spend fewer words validating it. Do not manufacture issues.

Guardrails

Do not claim accessibility compliance from visual or code inspection alone. Do not invent research findings. Do not prefer novelty over an established system pattern without evidence.

Contrast example

Bad:

Improve the visual hierarchy, make the CTA more prominent, simplify the form, and consider accessibility.

Good:

The primary action appears available before the required travel date is valid. That creates a false affordance: the user can try to continue before the form is ready. Keep the action unavailable until the date is valid, or surface validation early enough that the required fix is obvious before submit.

Why: the good critique identifies a specific behavior, explains the consequence, and gives a direction instead of offering generic design advice.

Examples

  • "Review this before I show engineering."
  • "Give me a tough critique."
  • "Compare these two approaches against the user problem."
  • "Review this PR against the intended experience."

Frequently asked questions

What does the Critique AI skill do?

Review and compare UX designs, flows, prototypes, specifications, or implementations against user goals, evidence, interaction behavior, accessibility, design-system fit, content, and engineering intent. Use when a designer asks for critique, comparison, tough feedback, review before approval, or wants to check whether implementation preserved the intended experience.

Why use Critique on TypingMind?

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

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/Tranz007/ux-skills/tree/main/skills/critique. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Critique?

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 Critique?

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

Is the Critique AI skill free?

Yes. It is published on GitHub by Tranz007 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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