App Overview

Data Generator Plus icon

Data Generator Plus

Heng Jia Liang · Developer Tools

Data Generator is a fast, simple tool for generating realistic test data.

$2.99 · In-app purchases

PRICE
$2.99
In-app purchases
BUSINESS MODEL
Paid
No overall Grossing estimate available
RATING
N/A
No ratings yet

Evidence scope: No current overall US chart position is available. Category-chart positions shown in discovery are a separate scope. Revenue is a directional model estimate, not verified earnings.

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A product spec, screen plans, and build steps for your coding agent.

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What's included16 files

A product spec, phased build plan, differentiation notes, and screen references.

  • START_HERE
  • AGENTS
  • EVIDENCE
  • SPEC
  • BUILD_PLAN
  • DIFFERENTIATION
  • skills/
  • screens/
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Illustrative example: an invoice app for independent contractors. Your kit is tailored to the app you choose; this is not its generated content.

Feature spec

Goal: Send a clear invoice after finishing a job.

  • Add a client, line items, a due date, and payment instructions.
  • Preview the total before exporting a PDF.
  • Keep an editable draft if export fails.

Screen plan

Invoice editor: Client at the top, editable line items in the middle, total and preview action at the bottom.

States: Empty draft, validation errors beside each field, exporting, and a retry action that preserves the draft.

Differentiate and validate

Hypothesis: Contractors need faster repeat invoices more than more templates.

First experiment: Test duplicating a previous job with five contractors. Watch where they hesitate before expanding the feature set.

The full kit adds a phased build plan, evidence notes, tool prompts, and implementation guidance. It is a plan for your coding agent, not a finished app.

Usage: Mechanics are fair game; never reuse the original name, branding, assets, or verbatim copy.

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Quick prompt

> SELECT BUILD PLATFORM:

Good fit for mobile-first iOS and Android prototypes with managed app scaffolding.

// RORK SYSTEM PROMPT
Rork plan preview for Data Generator Plus: map the core Developer Tools workflow, choose the smallest differentiated feature set, define the data and monetization boundaries, then prototype the riskiest user journey first.
            

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Opportunities

AI-GENERATED OPPORTUNITY HYPOTHESES

These are generated suggestions, not verified review quotations. Check current App Store reviews and speak with users before treating a possible gap as a requirement.

Hypothesis 1

Expand data types and customization features.

Assumption to check: Limited data generation options compared to other tools

Validate with people who use this workflow before building.

Hypothesis 2

Provide pre-defined templates for common use cases.

Assumption to check: Lack of templates or examples for data generation

Validate with people who use this workflow before building.

Hypothesis 3

Create forums or help sections for user engagement.

Assumption to check: No user community or support

Validate with people who use this workflow before building.

Hypothesis 4

Simplify purchase options and provide clear value propositions.

Assumption to check: In-app purchases may be confusing

Validate with people who use this workflow before building.

App evidence

Original App Store material. Ratings and screenshots describe the existing app, not proof of demand for your version.

App Store description

Data Generator is a fast, simple tool for generating realistic test data. It offers configuration options that provide great flexibility and manual control over the generated data. Test data can be used for machine learning or database testing purposes. Features: • Easy-to-use interface • Ability to set the amount of data • Ability to set minimum and maximum ranges for x-values and y-values • Support for integer or double data types • Option to avoid duplicate data (generate unique values only) • Preview data as a graph • Copy or save data in array format • Supported array formats: [x], [y], [x, y], (x, y), {x, y} Example Data: [x] - [2, 2, 2, 10, ... , 2, 10, 4, 8] [y] - [5, 3, 7, 8, ... , 4, 1, 2, 1] [x,y] - [[2, 5], [2, 3], [2, 7], [10, 8], ... , [2, 4], [10, 1], [4, 2], [8, 1]] (x,y) - ((2, 5), (2, 3), (2, 7), (10, 8), ... , (2, 4), (10, 1), (4, 2), (8, 1)) {x,y} - {{2, 5}, {2, 3}, {2, 7}, {10, 8}, ... , {2, 4}, {10, 1}, {4, 2}, {8, 1}} Example Usage: • Use for machine learning data training. Training data is used to teach an algorithm or machine learning model to predict specific outcomes. Test data is then used to evaluate the model's performance, such as accuracy and efficiency. • Generate dummy data for Excel training. • Create sample data as placeholders for both testing and operational purposes. • Or use it for any other purpose based on your imagination! Note: For datasets with more than 500 points, only the first 500 data points are displayed in the graph preview to improve performance. Thanks for your support and do visit nitrio.com for more apps for your iOS devices.

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Screenshots

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Build scope

Plan a focused first version with your coding agent. These are planning assumptions, not a delivery guarantee.

Define the first version

Choose one audience and one core workflow. Use the kit to agree on its screens, data, and acceptance criteria before building.

Set boundaries

Decide which secondary features, integrations, and platform support can wait. Your version does not need to reproduce everything in the original.

Check the hard parts

Validate external services, specialist technology, data access, and ongoing costs for your chosen scope.

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BUILD KIT DIFFICULTY
Starter

From the Build Kit assessment.

A reliable timeline needs an agreed scope and a technical check. Ask your agent to estimate the phases in BUILD_PLAN.md after that review.