Mobile Design Review logo

Mobile Design Review

Community
Xinvtech
mobile-design-review

Audit mobile product briefs, UX architectures, UI specifications, design-system artifacts, screenshots, prototypes, or implemented apps for product fit, task completion, information architecture, state coverage, visual consistency, native iOS/Android behavior, accessibility, privacy, ethics, brand differentiation, and implementation readiness. Use when Codex needs blockers, P0-P3 findings, a 100-point score, evidence-backed fixes, verification steps, regression review, or a release/design handoff decision.

Overview

PublisherXinvtech
Repositorymobile-design-os
Skill namemobile-design-review
Stars
4
Forks
0
Bundled files
7
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.

  • 7 bundled files

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

  • Open source

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

Installation

Install the Mobile Design Review 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/Xinvtech/mobile-design-os/tree/main/skills/mobile-design-review
  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/Xinvtech/mobile-design-os.git /tmp/mobile-design-os
mkdir -p .claude/skills
cp -r /tmp/mobile-design-os/skills/mobile-design-review .claude/skills/mobile-design-review
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Mobile Design Review 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 Mobile Design Review 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 Mobile Design Review 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.

Mobile Design Review

Produce an evidence-backed quality decision, not taste commentary. Every finding names the affected artifact/location, user impact, concrete fix, and verification method.

Select review mode

  • Package review: audit brief, Design DNA, UX architecture, wireframe, design system, UI specification, prototype, and code handoff together.
  • Visual review: audit screenshots, Figma frames, or rendered concepts against upstream contracts.
  • Implementation review: audit a running app or code plus visual/system behavior.
  • Regression review: verify that selected prior findings are fixed without introducing new failures.

Review only what the user supplied or authorized. Do not modify designs or code unless the user also requests fixes.

Establish the evidence contract

Inventory every source with stable IDs, path/URL, version/date, platform, and limitation. Validate structured upstream artifacts when validators exist.

Separate:

  • observed: directly present in an artifact or runtime.
  • derived: found by deterministic schema, coverage, contrast, target-size, or consistency checks.
  • risk: plausible failure needing prototype/device/user validation.
  • not-tested: required check that the available evidence cannot establish.

Do not claim contrast, screen-reader behavior, target size, animation performance, delivery semantics, or platform compliance from a prose specification alone.

Follow the workflow

1. Reconstruct the contract

Extract primary user, core task, activation, must requirements, non-goals, trust boundaries, screen/state coverage, design principles, platform targets, and acceptance signals. Resolve conflicting sources by authority and date; report unresolved conflicts.

2. Run deterministic checks first

Run available JSON/schema validators and inspect missing/extra IDs, state coverage, orphan components/screens, token provenance, broken references, duplicate responsibilities, and empty acceptance signals. Record tool results as evidence; a passing schema is not a passing design.

3. Review critical flows end to end

Trace activation, dominant loop, failure/recovery, permission denial, destructive actions, interrupted work, and exit. Check whether each step communicates system truth and preserves user control.

4. Review every quality dimension

Use references/review-rubric.md. Inspect:

  • Product and task match.
  • Information architecture and UX.
  • Visual hierarchy and consistency.
  • Platform-native behavior.
  • State and recovery completeness.
  • Accessibility, privacy, and ethics.
  • Brand differentiation and anti-copying.

For rendered or implemented UI, read references/visual-review-method.md and inspect each supplied view rather than filenames alone.

5. Classify severity

  • P0: safety, privacy, security, irreversible data loss, legal exposure, or core task impossible for most users. Release blocker.
  • P1: core task, trust, accessibility, or platform failure with major impact and no acceptable workaround. Fix before release/design handoff.
  • P2: comprehension, efficiency, recovery, consistency, or maintainability problem with a workaround. Schedule before polish.
  • P3: low-impact refinement or visual polish.

Mark blocker: true only for P0 or an explicit rubric blocker. Do not inflate severity to make the report look important.

6. Write actionable findings

Each finding must answer:

  1. What is wrong or unverified?
  2. Where is the evidence?
  3. Which user/task is affected?
  4. What consequence follows?
  5. What exact change is recommended?
  6. How will a reviewer prove it is fixed?

Keep separate issues separate when they have different owners or verification methods. Combine repeated instances under one system-level finding when the same fix resolves them.

7. Score without hiding blockers

Score out of 100 using the fixed dimension maximums. Every deduction references one or more finding IDs. A high score never overrides a blocker. Treat untested high-risk requirements as findings or explicit release conditions, not automatic passes.

8. Make a decision

Use one result:

  • pass: no blocker or P1; ready for the stated next stage.
  • conditional-pass: no blocker; P1 or required validation remains, with explicit conditions.
  • fail: one or more blockers.

Name the next stage: wireframe, visual production, implementation, usability test, beta, or release.

9. Produce and validate

When files are requested or this Skill is part of a workflow, create:

Run python3 scripts/validate_review.py <path-to-review.json> and fix every error.

Run the quality gate

Do not finish until every score deduction traces to a finding, every P0 is a blocker, every P1 has an owner/verification path, missing tests are distinguished from observed failure, and the decision matches the issue set.

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 Mobile Design Review AI skill do?

Audit mobile product briefs, UX architectures, UI specifications, design-system artifacts, screenshots, prototypes, or implemented apps for product fit, task completion, information architecture, state coverage, visual consistency, native iOS/Android behavior, accessibility, privacy, ethics, brand differentiation, and implementation readiness. Use when Codex needs blockers, P0-P3 findings, a 100-point score, evidence-backed fixes, verification steps, regression review, or a release/design handoff decision.

Why use Mobile Design Review on TypingMind?

Because you install it once and use it with any model. Mobile Design Review 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 Mobile Design Review in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/Xinvtech/mobile-design-os/tree/main/skills/mobile-design-review. 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 Mobile Design Review?

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 Mobile Design Review?

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

Is the Mobile Design Review AI skill free?

Yes. It is published on GitHub by Xinvtech 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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