Command Build Review Prompt

Community

khadinakbarlabs

command-build-review-prompt

Coordinate the cross-platform /build-review-prompt workflow for Expo projects: neutral milestone-based native review requests, shared cooldowns, and optional feedback for everyone. Use when implementing or correcting review prompts.

Overview

Publisher	khadinakbarlabs
Repository	`expo-mobile-app-builder`
Skill name	`command-build-review-prompt`
Stars	3
Forks	0
Bundled files	1
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.
1 bundled files
Scripts, templates, and references the model can read while it works. Files are read-only and never executed.
Open source
Published by khadinakbarlabs on GitHub. Read the source before you install it.

Installation

Install the Command Build Review Prompt 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.
https://github.com/khadinakbarlabs/expo-mobile-app-builder/tree/main/skills/command-build-review-prompt
Enable the skill in any chat where you want it available.

Store

Installed

Skills

Add skills

Import one or more skills from a public GitHub folder or a local .skill or .zip archive, or SKILL.md file.

From GitHub URLFrom .skill, .zip, or SKILL.md

GitHub repo or folder

https://github.com/khadinakbarlabs/expo-mobile-app-builder/tree/main/skills/command-build-review-prompt

Points to a single skill folder, or any folder that contains multiple skills. Public repos only.

CancelContinue

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/khadinakbarlabs/expo-mobile-app-builder.git /tmp/expo-mobile-app-builder
mkdir -p .claude/skills
cp -r /tmp/expo-mobile-app-builder/skills/command-build-review-prompt .claude/skills/command-build-review-prompt

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

Use it in TypingMind

Enable Command Build Review Prompt 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 Command Build Review Prompt 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 Command Build Review Prompt 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.

Command workflow: /build-review-prompt

Use this host-agnostic workflow to implement native review requests without satisfaction gates or rating manipulation. Retain the existing command and skill names for compatibility.

Workflow

Apply build-review-routing and its official Apple/Google references. Inspect the current app before changing code.
Define a usage milestone, a calm presentation point, a shared cooldown and acceptance behavior. Eligibility must not depend on sentiment, predicted stars, purchases, support history or survey answers.
Select the SDK-compatible expo-store-review integration, or preserve the existing native library when appropriate. Use the Expo reference shipped with this package and confirm platform support.
Remove custom pre-review satisfaction dialogs and any delayed filtering based on their answers. Keep optional feedback separate and available to everyone.
Persist request-attempt time, prevent duplicate requests and preserve cooldown across restarts and version changes. Request native UI only when supported; resume normally on suppression, failure or completion.
Add clearly labeled Settings entries for a user-initiated store link and optional feedback. Do not automatically redirect to the store when native UI fails or does not appear.
Instrument attempts, technical skips/errors and user-initiated link actions. Do not emit “review submitted,” infer stars, or thank users for rating from an API completion callback.
Write focused tests for eligibility independence, shared cooldown, concurrent triggers, unavailable APIs, failure behavior and feedback accessibility. Verify the integration on iOS and Android with appropriate builds and platform testing routes.

Minimum acceptance checks

text
[ ] No satisfaction question, sentiment filter or predicted-rating targeting
[ ] One documented usage milestone and cooldown applied to everyone
[ ] Cooldown persists across restart/version changes; duplicate attempts prevented
[ ] Platform review UI used without customization, overlay or interception
[ ] Suppression/errors/completion resume the ordinary app journey
[ ] No automatic store fallback or unsupported review-success claims
[ ] User-initiated store link and optional feedback available to everyone
[ ] No incentives, purchased reviews, required reviews or score pressure
[ ] Focused behavior checks and iOS/Android integration evidence recorded

Handoff

Report the eligible milestone, cooldown policy, removed gating, verification results and any unverified platform behavior. Separate request attempts from confirmed store-side outcomes. Store submission and publication follow the user's external-action authority; this workflow does not grant it.

Pair with build-review-routing, instrument-growth-funnel, mine-competitor-reviews and mine-play-reviews.

Bundled files

The model reads these on demand while the skill is loaded. They are exposed as readable files and are never executed.

agents/openai.yaml1 KB

Frequently asked questions

What does the Command Build Review Prompt AI skill do?

Why use Command Build Review Prompt on TypingMind?

Because you install it once and use it with any model. Command Build Review Prompt 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 Command Build Review Prompt in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/khadinakbarlabs/expo-mobile-app-builder/tree/main/skills/command-build-review-prompt. 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 Command Build Review Prompt?

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 Command Build Review Prompt?

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

Is the Command Build Review Prompt AI skill free?

Yes. It is published on GitHub by khadinakbarlabs 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

Command workflow: /build-review-prompt

Workflow

Minimum acceptance checks

Handoff

Bundled files

Frequently asked questions

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