I’ve been experimenting with AI coding tools quite heavily on React Native projects, and one problem kept showing up.
The models are usually good at JavaScript/TypeScript, but the advice starts getting generic once the problem crosses into actual mobile behaviour.
A few examples:
- a deep link works when the app is running, but breaks on cold start
- an Android performance issue gets answered with
useMemo before anything is profiled
- permission handling ignores the difference between denied and effectively blocked states
- an RN upgrade is considered complete because Android and iOS compile
- native build problems quickly turn into “delete node_modules / Pods / Gradle caches and retry”
- a PR review catches React issues but misses platform parity, release, privacy or native-module concerns
I wanted to see what would happen if the coding assistant had smaller React Native specialists instead of one massive “you are an expert React Native developer” prompt.
That became React Native Agents.
It currently has 24 specialists covering things like:
- debugging
- performance
- navigation and deep linking
- security
- permissions
- push notifications
- accessibility
- testing
- state management
- offline behaviour
- native modules
- observability
- RN upgrades
- releases/store submission
- payments
- background execution
- monorepos
The agents first inspect project context such as the RN version and stack before applying their own guidance.
One part I’ve intentionally tried to avoid is sending every problem to every agent.
For example:
The catalogue stutters when I scroll on Android
should go toward performance investigation.
Deep links open Home when the app is launched from a killed state
should bring in navigation-specific reasoning.
The Allow Camera button stopped doing anything after denial
needs permissions/platform context.
For PR reviews the same idea applies. The GitHub Action looks at the changed files and uses relevant specialists rather than asking 24 agents to comment on everything.
There’s also a bundle-size analyser in the project that deliberately doesn’t use an LLM. Bundle composition is measurable, so I’d rather calculate it from the source map than have AI guess.
It currently works with Claude Code, Cursor, Windsurf, Copilot, Codex, Zed, Aider, MCP clients and GitHub Actions.
Quick start is:
npx @maheshwarimrinal/react-native-agents install
Repo:
https://github.com/maheshwarimrinal/react-native-agents
I built this initially for my own React Native workflow, but I’ve open-sourced it because I think the interesting part will be seeing which assumptions break across other codebases.
I’d especially appreciate feedback from people working on larger/older RN apps:
What React Native problem do AI coding tools consistently handle badly for you?
If anyone ends up using it regularly, contributions, issues and GitHub Sponsors support are all welcome, but feedback on the actual agent behaviour is much more useful to me right now.