Expo Native Data Fetching Skill

Publisher: Expo plugin in openai/plugins · Editorial profile by AI Tools Ratings · Review method

What task is this skill designed for?

Use it to turn a happy-path request into a user-facing flow that handles slow networks and account changes. Separate retry-safe reads from mutations that could create duplicate records.

What input and output should you expect?

Input: An Expo screen or data hook, endpoint contract, authentication method and expected offline behavior. Use synthetic response examples rather than live user records.

Output: A proposed request layer or hook, loading and error states, cache-key decisions and a failure-focused verification checklist.

What does it need to run?

An Expo or React Native project and the selected fetching/cache dependencies. Router-specific loader guidance has platform and SDK prerequisites that must match the project.

Published in the OpenAI Codex plugins repository. Compatibility evidence is the plugin package and its source instructions; this is not a claim of identical behavior in other agent clients.

How should you approach installation?

1. Open the pinned source and review the complete skill folder, including referenced helpers and license, before enabling it.
2. Use the corresponding plugin in a compatible Codex environment; preserve the skill folder structure rather than copying only SKILL.md. Confirm current plugin availability in your client.
3. Start with a disposable project and the trial prompt below. Grant only the stated access, inspect the proposed diff, and require separate approval for remote writes or publishing.

Installation guide: discovery, dependencies and runtime checks

What files, accounts or data can it access?

Code changes may affect API traffic and local token storage. Live trials send data to configured endpoints; keep privileged credentials off the client and avoid real account mutations.

What does the skill cost?

The source guidance is MIT licensed. Client usage, backend requests and any third-party API fees remain separate; retries can increase request volume.

What are its limits and alternatives?

Retry examples are not automatically safe for POST requests. A cache can leak previous-user data if keys or logout cleanup are wrong; web loaders should not be assumed to work identically on native.

Use the API client documentation for a single endpoint; use the Expo upgrade skill when the failure is caused by SDK or dependency incompatibility.

What could you ask in a small trial?

Try this with a small sample:

Review a profile screen that caches results and retries failed requests. Handle logout, account switching, offline mode and a delayed response. Produce a diff and mock-response tests; do not call the real API.

How would you verify the result?

1. Switching users cannot display the previous user cache.
2. A late response cannot overwrite newer state.
3. Retrying a mutation cannot create duplicate records.
4. Loading, empty, denied and offline states are distinct.

Use a baseline and record acceptance evidence before treating a successful task as a reliable workflow.

Which source and license were checked?

Read the reviewed SKILL.md at its pinned commit · Complete reviewed folder

Repository and current publisher guidance

Checked: 2026-10-30

MIT License evidence

Report an error, license concern or request a new review.