relay-best-practices

Relay Best Practices

Relay is a GraphQL client for React that enforces colocated, composable, and type-safe data fetching. Its core insight is that each component should declare exactly what data it needs via GraphQL fragments, and Relay handles the rest — fetching, caching, consistency, and updates.

This skill provides opinionated guidance on which patterns to prefer. For detailed API documentation, read the relevant page from the doc map below.

Documentation

Relay ships LLM-friendly docs in node_modules/relay-runtime/llm-docs/ (available after v20.1.1). For older versions, fetch the same files from https://raw.githubusercontent.com/facebook/relay/main/website/docs/.

Paths below are relative to this directory (<llm-docs>/). Read the relevant page before writing Relay code. Key docs:

For performance-specific guidance (query placement, @defer, pagination, fetch policies, caching, fragment granularity), see the companion relay-performance skill.

Core Philosophy

These principles are the foundation of every decision below. When in doubt, refer back to them.

• Co-location: Each component declares its own data requirements via a GraphQL fragment, right next to the rendering code. Data needs travel with the component, not separately.
• Data masking: A component can only access the fields it explicitly selected in its own fragment. Parents cannot see child fragment data, and vice versa. This prevents implicit coupling between components.
• Composition: Fragments compose into parent fragments and ultimately into queries, forming a tree that mirrors the component tree. The compiler flattens this into a single network request per query.
• Render-as-you-fetch: Start fetching data before the component that needs it renders. This avoids sequential request waterfalls.
• Normalized store: Relay maintains a flat, ID-keyed cache. When a mutation returns updated data, every component reading that data re-renders automatically. You do not need to manually propagate changes.

Compiler Workflow

Relay uses an ahead-of-time compiler that reads graphql tagged template literals in your code and generates runtime artifacts and TypeScript/Flow types.

Finding the config

The compiler looks for its config in these locations (checked in order):

• relay.config.{json,js,mjs,ts} in the project root
• A "relay" key in package.json

See <llm-docs>/getting-started/compiler-config.mdx for the full config schema. You can also emit a JSON Schema for the config by running npx relay-compiler config-json-schema.

Running the compiler

Run npx relay-compiler after any change to the contents of a graphql tagged template literal or the docblock of a Relay Resolver. Some projects add this as a script in package.json (e.g., yarn relay). The compiler also supports watch mode (--watch), but avoid using it in non-interactive contexts since the process never exits.

Generated files go into __generated__/ directories next to the source files. Never edit these files — they are overwritten on every compiler run. If you see type errors about missing generated types, run the compiler first — the types are likely just out of date.

Lint Rules

Relay's ESLint plugin (eslint-plugin-relay) is a key part of the developer experience. Two rules are especially important:

• relay/unused-fields — detects GraphQL fields that are selected in a fragment but never read in the component. This prevents the "append-only query" problem where fragments accumulate unused fields over time, fetching data no component actually needs.
• relay/no-future-added-value — prevents explicitly handling the "%future added value" enum placeholder that Relay inserts to ensure you handle the possibility of new enum variants being added by the server.

See <llm-docs>/getting-started/lint-rules.mdx for installation and configuration.

Decision Rules

Queries belong at roots — never in hooks

Queries belong at route entrypoints (the top-level component for a URL). Hooks are leaves — reused across many components. A query inside a hook fires late (after the hook's host renders) AND duplicates across every caller. The fix is always: accept a fragment key as a parameter, use useFragment.

Use usePreloadedQuery + useQueryLoader (or loadQuery). Start the fetch in an event handler, route transition, or during app initialization — before the component renders. useLazyLoadQuery does not start fetching until render, creating waterfalls. See <llm-docs>/guided-tour/rendering/queries.mdx for the full pattern.

Before fixing where a query lives, ask if it should exist

loadQuery in useEffect is worse than useLazyLoadQuery

useEffect runs after paint, so the fetch starts even later than useLazyLoadQuery (which at least starts during render). Call loadQuery in event handlers, route transitions, or app initialization — never in effects.

Walking the ancestor tree for useFragment

When deciding whether useFragment can replace a query, walk up the component tree from your component. Stop at: route boundaries, feature gates, conditional renders, or user-triggered interactions. Keep walking through: unconditional renders, layout/wrapper components, context providers.

If any ancestor already queries the GraphQL type you need, useFragment is the answer. Threading fragment keys through several layers of props is fine — it IS the correct pattern.

Don't default query variables to empty values

Never default a query variable to '', 0, or null when the real value is unavailable. This fires the query with bad data, returning wrong results or errors. Instead, use conditional rendering (if (!id) return null) or @include/@skip directives to omit the field entirely.

Data flow: Always use fragments

Every component that displays server data should declare a fragment and receive a fragment reference (the $key type) as a prop. The parent spreads the child's fragment in its own query or fragment and passes the result down. See the "Maintain fragment co-location" anti-pattern below for an example.

Mutations: Spread fragments into responses

Spread the consuming component's fragment into the mutation response rather than selecting fields individually. This keeps them in sync automatically. See the anti-pattern example below.

Error handling: Use @throwOnFieldError and @catch

The recommended approach for handling field errors and nullability is to add @throwOnFieldError to your fragment or query. This causes Relay to throw a JavaScript exception if a field error is encountered, which can be caught by a React error boundary. It also enables non-null types for @semanticNonNull fields, eliminating unnecessary null checks. Note that this pattern depends on React error boundaries being configured in your application — proceed with caution if error boundaries are not set up robustly.

For fields where you want to handle errors locally instead of throwing, use @catch to receive errors inline as { ok: true, value: T } | { ok: false, errors: [...] }.

@required is also available for declaring that specific fields must be non-null, but @throwOnFieldError + @catch is the preferred pattern for new code.

See <llm-docs>/guides/throw-on-field-error-directive.mdx, <llm-docs>/guides/catch-directive.mdx, and <llm-docs>/guides/semantic-nullability.mdx.

Pagination: Use the three-directive pattern

Always use @argumentDefinitions (for cursor/count variables), @refetchable (to auto-generate the pagination query), and @connection (to identify the connection for store management) together. Never write manual pagination queries. See <llm-docs>/guided-tour/list-data/pagination.mdx.

Client state: Prefer Relay Resolvers

When multiple components need to read client-side data, use Relay Resolvers to define client-only fields on the GraphQL schema rather than prop-drilling or React context. This gives client state the same composability and caching guarantees as server data. Use useClientQuery for queries that read only resolver-defined fields.

See <llm-docs>/guides/relay-resolvers/introduction.mdx for how to define resolvers.

Critical Anti-Patterns

Never copy Relay data into React state

This is the single most important rule. Do not read data from useFragment and copy it into useState, and do not update that state manually in mutation onCompleted callbacks.

// WRONG: Copying Relay data into React state
function UserProfile({userKey}) {
  const data = useFragment(UserProfileFragment, userKey);
  const [name, setName] = useState(data.name); 

Why this is wrong: Relay's normalized store is the single source of truth. When a mutation returns updated data with a matching id, Relay automatically updates every component reading that data via useFragment. By copying into useState, you create a second source of truth that Relay cannot update. The component will show stale data whenever the record is updated by another mutation, subscription, or refetch elsewhere in the app.

Similarly, do not store a fragment key (the $key prop) in React state. Relay garbage collects data that is no longer retained by a mounted query component — if the component that originally fetched the data unmounts, a stashed key may point to data that is no longer in the store.

Maintain fragment co-location

Do not fetch all data in a parent's query and pass raw data objects as props to children. This defeats data masking and creates tight coupling — adding a field to a child component requires editing the parent's query. Note that the relay/unused-fields lint rule will flag fields selected in the parent that are only used by children — this is a good signal that you need to extract a fragment.

Spread fragments into mutation responses

Do not select fields individually in both a fragment and a mutation response — they will drift out of sync. Spread the fragment instead:

Correctness

Use optimisticUpdater for store-dependent values

If an optimistic value depends on current store state (e.g., incrementing a like count), use optimisticUpdater instead of optimisticResponse. Multiple overlapping optimistic responses can compound incorrectly — two simultaneous "like" mutations both read count=5 and set count=6, instead of 5→6→7. When one rolls back, the store is left in an inconsistent state.

Invalidate data after wide-effect mutations

When a mutation has side effects too broad to capture in a single response payload, use invalidateRecord() for targeted invalidation or invalidateStore() for global invalidation. Pair with useSubscribeToInvalidationState on mounted components to trigger refetches for stale data automatically.

Handle staleness explicitly

Relay treats cached data as fresh indefinitely by default. Two approaches:

• Time-based: Set queryCacheExpirationTime on the Relay Store to automatically mark data stale after a duration.
• Event-based: Call invalidateRecord() after mutations whose side effects extend beyond the mutation response payload.

Without explicit staleness handling, components can display arbitrarily old data after the user returns to a previously visited screen.

Single artifact directory for type safety

Without setting artifactDirectory in the compiler config, fragment references may default to any, losing type safety. Set it and align your bundler's module resolution accordingly. See <llm-docs>/getting-started/compiler-config.mdx.

Use @updatable for store manipulation

Prefer typesafe updatable queries/fragments over raw store manipulation with string-based field access (e.g., store.get(id).setValue(newName, 'name')). Updatable fragments provide getters and setters, reducing the risk of typos and type mismatches.

Avoid unnecessary refetches after mutations

Do not call refetch() or fetchQuery() after mutations when spreading component fragments in the mutation response would auto-update the store. Each unnecessary refetch is a wasted network request and delays the UI update.

Reserve manual refetches for cases where the mutation's side effects are too broad to capture in the response payload — and in those cases, prefer invalidateRecord() (see above).

Use subscriptions for real-time data

Prefer GraphQL Subscriptions over polling (setInterval + fetchQuery) or manual refresh buttons for data that must stay current. Subscriptions push updates only when data changes and integrate with Relay's normalized store automatically.

Naming Conventions

Relay enforces that operation names match the module (file) they are defined in. Mismatched names cause compiler errors, not just style warnings.

The module name is the filename stripped of all extensions (.react.js, .tsx, etc.). UserCard.react.js → module name UserCard.

Renaming operations when extracting to a new file

When moving a component to a new file, rename only the operations defined in that file to match the new filename. Do NOT rename fragment spreads that reference fragments owned by other modules — those names belong to their defining component.

Renaming an operation also changes its generated type name (e.g., UserCard_user$key → ProfileCard_user$key), so update all downstream imports of those generated types.

Never hand-edit __generated__/ files

The next compiler run overwrites any manual edits. If you see type errors about missing generated types, run the compiler first — the types are just out of date, not missing.

Verify mutation variable keys after auto-formatting

Auto-formatters and linters can rename variables in ways that silently break mutation calls. After running lint auto-fix, verify that variable keys in commit({ variables: { ... } }) still match the generated Mutation$variables type (check for data vs input mismatches in particular).