typescript-best-practices
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Provides TypeScript patterns for type-first development, making illegal states unrepresentable, exhaustive handling, and runtime validation. Must use when reading or writing TypeScript/JavaScript files.
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TypeScript Best Practices
Pair with React Best Practices
When working with React components (, files or imports), always load alongside this skill. This skill covers TypeScript fundamentals; React-specific patterns (effects, hooks, refs, component design) are in the dedicated React skill.
.tsx.jsx@reactreact-best-practicesType-First Development
Types define the contract before implementation. Follow this workflow:
- Define the data model - types, interfaces, and schemas first
- Define function signatures - input/output types before logic
- Implement to satisfy types - let the compiler guide completeness
- Validate at boundaries - runtime checks where data enters the system
Make Illegal States Unrepresentable
Use the type system to prevent invalid states at compile time.
Discriminated unions for mutually exclusive states:
ts
// Good: only valid combinations possible
type RequestState<T> =
| { status: 'idle' }
| { status: 'loading' }
| { status: 'success'; data: T }
| { status: 'error'; error: Error };
// Bad: allows invalid combinations like { loading: true, error: Error }
type RequestState<T> = {
loading: boolean;
data?: T;
error?: Error;
};Branded types for domain primitives:
ts
type UserId = string & { readonly __brand: 'UserId' };
type OrderId = string & { readonly __brand: 'OrderId' };
// Compiler prevents passing OrderId where UserId expected
function getUser(id: UserId): Promise<User> { /* ... */ }
function createUserId(id: string): UserId {
return id as UserId;
}Const assertions for literal unions:
ts
const ROLES = ['admin', 'user', 'guest'] as const;
type Role = typeof ROLES[number]; // 'admin' | 'user' | 'guest'
// Array and type stay in sync automatically
function isValidRole(role: string): role is Role {
return ROLES.includes(role as Role);
}Required vs optional fields - be explicit:
ts
// Creation: some fields required
type CreateUser = {
email: string;
name: string;
};
// Update: all fields optional
type UpdateUser = Partial<CreateUser>;
// Database row: all fields present
type User = CreateUser & {
id: UserId;
createdAt: Date;
};Module Structure
Prefer smaller, focused files: one component, hook, or utility per file. Split when a file handles multiple concerns or exceeds ~200 lines. Colocate tests with implementation ( alongside ). Group related files by feature rather than by type.
foo.test.tsfoo.tsFunctional Patterns
- Prefer over
const; useletandreadonlyfor immutable data.Readonly<T> - Use over
array.map/filter/reduceloops; chain transformations in pipelines.for - Write pure functions for business logic; isolate side effects in dedicated modules.
- Avoid mutating function parameters; return new objects/arrays instead.
Instructions
- Enable mode; model data with interfaces and types. Strong typing catches bugs at compile time.
strict - Every code path returns a value or throws; use exhaustive with
switchchecks in default. Unhandled cases become compile errors.never - Propagate errors with context; catching requires re-throwing or returning a meaningful result. Hidden failures delay debugging.
- Handle edge cases explicitly: empty arrays, null/undefined inputs, boundary values. Defensive checks prevent runtime surprises.
- Use for async calls; wrap external calls with contextual error messages. Unhandled rejections crash Node processes.
await - Add or update focused tests when changing logic; test behavior, not implementation details.
Examples
Explicit failure for unimplemented logic:
ts
export function buildWidget(widgetType: string): never {
throw new Error(`buildWidget not implemented for type: ${widgetType}`);
}Exhaustive switch with never check:
ts
type Status = "active" | "inactive";
export function processStatus(status: Status): string {
switch (status) {
case "active":
return "processing";
case "inactive":
return "skipped";
default: {
const _exhaustive: never = status;
throw new Error(`unhandled status: ${_exhaustive}`);
}
}
}Wrap external calls with context:
ts
export async function fetchWidget(id: string): Promise<Widget> {
const response = await fetch(`/api/widgets/${id}`);
if (!response.ok) {
throw new Error(`fetch widget ${id} failed: ${response.status}`);
}
return response.json();
}Debug logging with namespaced logger:
ts
import debug from "debug";
const log = debug("myapp:widgets");
export function createWidget(name: string): Widget {
log("creating widget: %s", name);
const widget = { id: crypto.randomUUID(), name };
log("created widget: %s", widget.id);
return widget;
}Runtime Validation with Zod (v4)
- Define schemas as single source of truth; infer TypeScript types with . Avoid duplicating types and schemas.
z.infer<> - Use for user input where failure is expected; use
safeParseat trust boundaries where invalid data is a bug.parse - Compose schemas with ,
.extend(),.pick(),.omit()for DRY definitions..merge() - Add for data normalization at parse time (trim strings, parse dates).
.transform() - Include descriptive error messages; use for custom validation logic.
.refine()
Zod 4 Top-Level Validators (REQUIRED for new code)
Prefer Zod 4 top-level validators over chained string methods:
ts
// ✅ Zod 4: top-level validators
z.email()
z.url()
z.uuid()
// ❌ Zod 3 legacy (still works but prefer the above)
z.string().email()
z.string().url()
z.string().uuid()Error messages use instead of :
errormessagets
// ✅ Zod 4
z.email({ error: "Invalid email format" })
z.string().min(1, { error: "Required" })
// ❌ Zod 3 legacy
z.string().email({ message: "Invalid email format" })Examples
Schema as source of truth with type inference:
ts
import { z } from "zod";
const UserSchema = z.object({
id: z.uuid(),
email: z.email(),
name: z.string().min(1),
createdAt: z.string().transform((s) => new Date(s)),
});
type User = z.infer<typeof UserSchema>;Return parse results to callers (never swallow errors):
ts
import { z, SafeParseReturnType } from "zod";
export function parseUserInput(raw: unknown): SafeParseReturnType<unknown, User> {
return UserSchema.safeParse(raw);
}
// Caller handles both success and error:
const result = parseUserInput(formData);
if (!result.success) {
setErrors(result.error.flatten().fieldErrors);
return;
}
await submitUser(result.data);Strict parsing at trust boundaries:
ts
export async function fetchUser(id: string): Promise<User> {
const response = await fetch(`/api/users/${id}`);
if (!response.ok) {
throw new Error(`fetch user ${id} failed: ${response.status}`);
}
const data = await response.json();
return UserSchema.parse(data); // throws if API contract violated
}Schema composition:
ts
const CreateUserSchema = UserSchema.omit({ id: true, createdAt: true });
const UpdateUserSchema = CreateUserSchema.partial();
const UserWithPostsSchema = UserSchema.extend({
posts: z.array(PostSchema),
});Configuration
- Load config from environment variables at startup; validate with Zod before use. Invalid config should crash immediately.
- Define a typed config object as single source of truth; avoid accessing throughout the codebase.
process.env - Use sensible defaults for development; require explicit values for production secrets.
Examples
Typed config with Zod validation:
ts
import { z } from "zod";
const ConfigSchema = z.object({
PORT: z.coerce.number().default(3000),
DATABASE_URL: z.url(),
API_KEY: z.string().min(1),
NODE_ENV: z.enum(["development", "production", "test"]).default("development"),
});
export const config = ConfigSchema.parse(process.env);Access config values (not process.env directly):
ts
import { config } from "./config";
const server = app.listen(config.PORT);
const db = connect(config.DATABASE_URL);Optional: type-fest
For advanced type utilities beyond TypeScript builtins, consider type-fest:
- - cleaner branded types than manual
Opaque<T, Token>pattern& { __brand } - - recursive partial for nested objects
PartialDeep<T> - - recursive readonly for immutable data
ReadonlyDeep<T> - - literals with autocomplete + string fallback
LiteralUnion<Literals, Fallback> - /
SetRequired<T, K>- targeted field modificationsSetOptional<T, K> - - flatten complex intersection types in IDE tooltips
Simplify<T>
ts
import type { Opaque, PartialDeep, SetRequired } from 'type-fest';
// Branded type (cleaner than manual approach)
type UserId = Opaque<string, 'UserId'>;
// Deep partial for patch operations
type UserPatch = PartialDeep<User>;
// Make specific fields required
type UserWithEmail = SetRequired<Partial<User>, 'email'>;