App Overview

Forkr: AI Menu Scanner icon

Forkr: AI Menu Scanner

Rekishi, LLC · Health & Fitness

stop guessing what to order

$1.99 · In-app purchases

PRICE
$1.99
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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Build Kit

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

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What's included15 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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Free quick prompt For a smaller starting point

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 Forkr: AI Menu Scanner: map the core Health & Fitness 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

Provide more detailed nutritional insights and meal suggestions.

Assumption to check: Limited functionality after initial scans

Validate with people who use this workflow before building.

Hypothesis 2

Implement machine learning for better accuracy in menu item recognition.

Assumption to check: Inaccurate scanning results

Validate with people who use this workflow before building.

Hypothesis 3

Add functionality for users to share their scans and meals on social media.

Assumption to check: No social sharing features

Validate with people who use this workflow before building.

Hypothesis 4

Offer a one-time purchase option alongside subscriptions to cater to different user preferences.

Assumption to check: Subscription fatigue

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

stop guessing what to order. forkr uses ai to scan restaurant menus and instantly tells you what to eat based on your dietary preferences. how it works snap a photo of any restaurant menu ai analyzes every dish in seconds get personalized recommendations ranked by how well they match your preferences personalized to you forkr learns your unique dietary profile during a quick onboarding: • nutrition focus (protein, fiber, carbs, fat) • diet types (keto, vegan, vegetarian, gluten-free, paleo, low-fodmap) • allergies (all fda big 9 + common intolerances) • ingredients to avoid (dairy, soy, nuts, shellfish, and more) smart recommendations each menu item gets scored 0-100% based on your personal alignment: • best choice - perfectly matches your preferences • good choice - solid option with minor tradeoffs • okay choice - acceptable but not ideal • avoid - conflicts with your dietary needs see estimated nutrition, ingredient highlights, and clear explanations for every recommendation. privacy first your dietary data stays on your device. we don't sell your information to advertisers. you're the customer, not the product. powered by advanced ai forkr uses vision technology to read and understand menus just like you would—but faster and with perfect recall of your preferences. for informational purposes only. not a substitute for professional dietary or medical advice. download forkr and take the guesswork out of dining.

Written user reviews are not shown here. Check current App Store reviews >

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.

SUGGESTED BUILD STACK
React Native
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zustand
BUILD KIT DIFFICULTY
Intermediate

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.