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.
App Overview
AI Photo Fake Detector Pro
AI Photo Fake Detector analyzes a photo’s forensic signals and summarizes them in plain language
$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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Build Kit
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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.
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
Good fit for mobile-first iOS and Android prototypes with managed app scaffolding.
// RORK SYSTEM PROMPT
Rork plan preview for AI Photo Fake Detector Pro: map the core Photo & Video 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
Include more detailed analysis features and explanations.
Assumption to check: Limited functionality for photo analysis
Validate with people who use this workflow before building.
Hypothesis 2
Simplify navigation and provide better onboarding.
Assumption to check: User experience can be confusing
Validate with people who use this workflow before building.
Hypothesis 3
Clearer paywall messaging and trial options.
Assumption to check: In-app purchase confusion
Validate with people who use this workflow before building.
Hypothesis 4
Optimize image processing and analysis speed.
Assumption to check: Performance issues with large images
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
AI Photo Fake Detector analyzes a photo’s forensic signals and summarizes them in plain language. It combines five independent checks—Error Level Analysis, noise consistency, stylization artifacts, JPEG blockiness, metadata red flags and much more—then outputs a verdict with confidence plus an ELA visualization and human-readable notes. Use it to triage images from social, messages, or your own camera roll. Nothing leaves your device unless you share a result. Multi-signal analysis. One view, five checks, less guesswork. Confidence and transparency. See the score and the evidence. Clear ELA heatmap. Bright regions can indicate re-compression or edits. Metadata notes that matter. Camera make/model, timestamps, JFIF, software tags. Private by design. Runs offline. No accounts. No ads. No tracking. Fast. Results in seconds on modern iPhones and iPads. ELA anomaly: re-compression differences that can reveal edits. Noise heterogeneity: inconsistent sensor noise across regions. Stylization artifacts: AI/filters that leave style fingerprints. JPEG blockiness: abnormal blocking beyond expected compression. Metadata red flags: missing camera fields, software edits, JFIF export, etc. Pick a photo. Review verdict, confidence, scores, and ELA map. Read metadata notes and decide with context. Forensics estimate likelihood. They are not proof. Use context and corroborating evidence. Dynamic Type, VoiceOver labels, high-contrast friendly.
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
Expo
FastAPI
Zustand
axios
react-native-reanimated
BUILD KIT DIFFICULTY
Advanced
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.
