Can NicheMaps be vibe coded?
Find mobile niches already making money via live ad spend, IAP, and growth signals
You can build a personal watchlist that checks a handful of store listings and ad-library pages, but NicheMaps' value is a continuously refreshed catalog of millions of iOS/Android apps with ad-status, IAP, velocity, and creative evidence you cannot rebuild.
Jump to the build brief ↓Checked Aug 2026
What you pay today, before any DIY hosting
high editorial confidence
Buildability by layer
Screens, forms, and focused interactions
The repeatable job the product performs
Availability and legality of required data
Uptime, queues, support, and maintenance
Security, compliance, and user confidence
The achievable core
- Track a small list of competitor apps, pull public store metadata, open their Google Ads Transparency and Meta Ad Library pages, and note which creatives are still running.
- Ingest a known data source, calculate a focused metric set, and render a useful dashboard.
- A responsive interface with real empty, loading, success, and error states.
The parts a prompt cannot buy
- 5M+ app catalog with searchable filters
- live ad-running status across the whole store
- IAP and install/rating velocity joins
- aggregated Google and Meta creative history
- The useful dataset is owned, accumulated, or expensive to reproduce.
- Reliability at the vendor's scale is an operations problem, not a prompt.
Why people still pay
They pay for the dataset and the joins, not the UI. Knowing which niches are buying ads right now across millions of apps is the product; a DIY watchlist only covers apps you already know to check.
The useful dataset is owned, accumulated, or expensive to reproduce.
Reliability at the vendor's scale is an operations problem, not a prompt.
The brief
Context, requirements, acceptance criteria, non-goals, and the full production standard — as Markdown, ready for any coding agent.
Build brief — a focused alternative to NicheMaps
Context
**NicheMaps** — Find mobile niches already making money via live ad spend, IAP, and growth signals. It currently costs $79/mo.
You can build a personal watchlist that checks a handful of store listings and ad-library pages, but NicheMaps' value is a continuously refreshed catalog of millions of iOS/Android apps with ad-status, IAP, velocity, and creative evidence you cannot rebuild.
This brief describes a focused, single-operator replacement for the part of NicheMaps that is genuinely reproducible. It is deliberately narrower than the product it replaces, and it says so in writing. Build the useful core; do not pretend to have rebuilt the rest.
What you are building
Track a small list of competitor apps, pull public store metadata, open their Google Ads Transparency and Meta Ad Library pages, and note which creatives are still running.
Ingest a known data source, calculate a focused metric set, and render a useful dashboard.
A responsive interface with real empty, loading, success, and error states.
Requirements
Functional
App Store / Play public listing access.
Google Ads Transparency Center.
Meta Ad Library.
SQLite or local JSON storage.
Data and integrations
Optional residential proxy if scraping at volume.
Each of these needs a real account, credential, or quota. Set them up before writing feature code.
Non-functional
Accessibility: semantic markup, labelled controls, visible focus, and reduced-motion support.
Security: server-side secrets, validated input, and no credentials in the client bundle.
Reliability: retries with backoff on external calls, and a clear failure state when a provider is down.
Portability: the operator can export their data and leave without losing it.
Implementation brief
Build me a local competitor-app watchlist, the one slice of NicheMaps worth building solo. Requirements:
Node 22 + TypeScript + SQLite + a tiny localhost UI (Vite + React is fine).
apps.json lists up to 25 apps with platform (ios|android), store id, and optional advertiser name.
`npm run refresh` fetches public store listing fields (title, rating, ratings count, free/paid, last updated) via the facundoolano google-play-scraper / app-store-scraper libraries. Respect rate limits; sleep between requests.
For each app, store deep links to Google Ads Transparency and Meta Ad Library search URLs (domain or advertiser name). Do not pretend you have store-wide ad-running bitmaps.
Optional: with PLAYWRIGHT=1, open those two URLs headlessly and save a dated HTML snapshot plus a count of creatives mentioning the app name. Expect blocks; document proxy/env needs and fail soft.
SQLite tables: apps, snapshots, creative_checks. Keep full history.
Localhost dashboard: table of watched apps, sparkline of ratings-count delta, last creative-check time, and buttons to open the transparency URLs.
Secrets in .env only (.env.example shipped). No accounts, no cloud, no telemetry.
Out of scope: crawling the whole store, IAP detection at scale, "apps advertising now" filters, and niche ranking across categories. That dataset is the subscription.
README: setup, refresh cron example, honest statement that NicheMaps is a proprietary multi-store + ad-library index and this replaces a personal watchlist, not the catalog.
Delivery standard
Inspect the repository first, then write a short implementation plan before writing code.
Deliver the smallest complete end-to-end workflow first; every primary control must work against persisted data.
Use real validation and storage; never substitute fake dashboards, decorative controls, hard-coded success states, or mock integrations.
Include responsive layouts plus genuine empty, loading, success, validation, and failure states.
Keep secrets server-side in environment variables, provide .env.example, and never commit credentials or user data.
Add structured logs around every external call and return actionable errors without leaking sensitive details.
Write unit tests for the core logic and one automated test of the main user journey.
Finish with a README covering setup, architecture, data location, backups, tests, deployment, and known limitations.
Acceptance criteria
A clean install starts the app using only the README and .env.example.
The primary journey works from first visit through saved result, reload, edit, export, and deletion where applicable.
Invalid input, missing configuration, provider failure, and an empty database each have a usable state.
The interface works at 390px and 1440px, is keyboard navigable, and shows visible focus on every control.
Tests, type checking, linting, and a production build all pass with no ignored failures.
No part of the interface implies a live integration, security guarantee, or scale capability that was not actually built and verified.
Non-goals
Do not build these, and do not claim to have replaced them:
5M+ app catalog with searchable filters.
Live ad-running status across the whole store.
IAP and install/rating velocity joins.
Aggregated Google and Meta creative history.
The useful dataset is owned, accumulated, or expensive to reproduce.
Reliability at the vendor's scale is an operations problem, not a prompt.
What you still own after launch
Secure credentials, rotate secrets, and handle provider rate limits.
Run migrations, backups, restores, and dependency updates.
Test the critical journey after every model, API, or hosting change.
Monitor failures and fix the edge cases a first prompt will miss.
Risk
**Operational risk.** The code is achievable; dependable data, integrations, and ongoing operations are the real cost.
Editorial confidence in this assessment: high. No independent one-shot implementation is linked yet.
Prior art
Working open-source software you can read, fork, or borrow from before starting:
[google-play-scraper](https://github.com/facundoolano/google-play-scraper) — Node library for public Play Store listing metadata; does not provide ad-status or creatives
[app-store-scraper](https://github.com/facundoolano/app-store-scraper) — Node library for public App Store listing metadata; same consolation-layer limits
Generated by [Can It Be Vibe Coded?](https://www.canitbevibecoded.com) · Full report: https://www.canitbevibecoded.com/nichemaps
You still own the product
- Secure credentials, rotate secrets, and handle provider rate limits.
- Run migrations, backups, restores, and dependency updates.
- Test the critical journey after every model, API, or hosting change.
- Monitor failures and fix the edge cases a first prompt will miss.
Open-source prior art
Before you start
Can NicheMaps be vibe coded?
Not faithfully. You can build a personal watchlist that checks a handful of store listings and ad-library pages, but NicheMaps' value is a continuously refreshed catalog of millions of iOS/Android apps with ad-status, IAP, velocity, and creative evidence you cannot rebuild.
What can an AI coding agent reproduce from NicheMaps?
Track a small list of competitor apps, pull public store metadata, open their Google Ads Transparency and Meta Ad Library pages, and note which creatives are still running. Ingest a known data source, calculate a focused metric set, and render a useful dashboard. A responsive interface with real empty, loading, success, and error states.
What will a DIY NicheMaps replacement still be missing?
5M+ app catalog with searchable filters; live ad-running status across the whole store; IAP and install/rating velocity joins; aggregated Google and Meta creative history; The useful dataset is owned, accumulated, or expensive to reproduce.; Reliability at the vendor's scale is an operations problem, not a prompt.
What do I still own after building a NicheMaps alternative?
Secure credentials, rotate secrets, and handle provider rate limits. Run migrations, backups, restores, and dependency updates. Test the critical journey after every model, API, or hosting change. Monitor failures and fix the edge cases a first prompt will miss.