fp-backend
Functional programming patterns for Node.js/Deno backend development using fp-ts, ReaderTaskEither, and functional dependency injection
What this skill does
# fp-ts Backend Patterns
Functional programming patterns for building type-safe, testable backend services using fp-ts.
## When to Use
- You are building or refactoring a Node.js or Deno backend with fp-ts.
- The task involves dependency injection, service composition, or typed backend errors with `ReaderTaskEither`.
- You need functional backend architecture patterns rather than isolated utility snippets.
## Core Concepts
### ReaderTaskEither (RTE)
The `ReaderTaskEither<R, E, A>` type is the backbone of functional backend development:
- **R** (Reader): Dependencies/environment (database, config, logger)
- **E** (Either left): Error type
- **A** (Either right): Success value
```typescript
import * as RTE from 'fp-ts/ReaderTaskEither'
import * as TE from 'fp-ts/TaskEither'
import { pipe } from 'fp-ts/function'
// Define your dependencies
type Deps = {
db: DatabaseClient
logger: Logger
config: Config
}
// Define domain errors
type AppError =
| { _tag: 'NotFound'; resource: string; id: string }
| { _tag: 'ValidationError'; message: string }
| { _tag: 'DatabaseError'; cause: unknown }
| { _tag: 'Unauthorized'; reason: string }
// A service function
const getUser = (id: string): RTE.ReaderTaskEither<Deps, AppError, User> =>
pipe(
RTE.ask<Deps>(),
RTE.flatMap(({ db, logger }) =>
pipe(
RTE.fromTaskEither(db.users.findById(id)),
RTE.mapLeft((e): AppError => ({ _tag: 'DatabaseError', cause: e })),
RTE.flatMap(user =>
user
? RTE.right(user)
: RTE.left({ _tag: 'NotFound', resource: 'User', id })
),
RTE.tap(user => RTE.fromIO(() => logger.info(`Found user: ${user.id}`)))
)
)
)
```
## Service Layer Patterns
### Defining Service Modules
Structure services as modules exporting RTE functions:
```typescript
// src/services/user.service.ts
import * as RTE from 'fp-ts/ReaderTaskEither'
import * as TE from 'fp-ts/TaskEither'
import * as A from 'fp-ts/Array'
import { pipe } from 'fp-ts/function'
type UserDeps = {
db: DatabaseClient
hasher: PasswordHasher
mailer: EmailService
}
type UserError =
| { _tag: 'UserNotFound'; id: string }
| { _tag: 'EmailExists'; email: string }
| { _tag: 'InvalidPassword' }
// Create user
export const create = (
input: CreateUserInput
): RTE.ReaderTaskEither<UserDeps, UserError, User> =>
pipe(
RTE.ask<UserDeps>(),
RTE.flatMap(({ db, hasher }) =>
pipe(
// Check email uniqueness
checkEmailUnique(input.email),
RTE.flatMap(() =>
RTE.fromTaskEither(hasher.hash(input.password))
),
RTE.flatMap(hashedPassword =>
RTE.fromTaskEither(
db.users.create({
...input,
password: hashedPassword,
})
)
)
)
)
)
// Find by ID
export const findById = (
id: string
): RTE.ReaderTaskEither<UserDeps, UserError, User> =>
pipe(
RTE.ask<UserDeps>(),
RTE.flatMap(({ db }) =>
pipe(
RTE.fromTaskEither(db.users.findUnique({ where: { id } })),
RTE.flatMap(user =>
user
? RTE.right(user)
: RTE.left({ _tag: 'UserNotFound' as const, id })
)
)
)
)
// Find many with pagination
export const findMany = (
params: PaginationParams
): RTE.ReaderTaskEither<UserDeps, UserError, PaginatedResult<User>> =>
pipe(
RTE.ask<UserDeps>(),
RTE.flatMap(({ db }) =>
RTE.fromTaskEither(
pipe(
TE.Do,
TE.bind('users', () => db.users.findMany({
skip: params.offset,
take: params.limit,
})),
TE.bind('total', () => db.users.count()),
TE.map(({ users, total }) => ({
data: users,
total,
...params,
}))
)
)
)
)
const checkEmailUnique = (
email: string
): RTE.ReaderTaskEither<UserDeps, UserError, void> =>
pipe(
RTE.ask<UserDeps>(),
RTE.flatMap(({ db }) =>
pipe(
RTE.fromTaskEither(db.users.findUnique({ where: { email } })),
RTE.flatMap(existing =>
existing
? RTE.left({ _tag: 'EmailExists' as const, email })
: RTE.right(undefined)
)
)
)
)
```
### Composing Services
```typescript
// src/services/order.service.ts
import * as UserService from './user.service'
import * as ProductService from './product.service'
import * as PaymentService from './payment.service'
type OrderDeps = UserService.UserDeps &
ProductService.ProductDeps &
PaymentService.PaymentDeps & {
db: DatabaseClient
}
export const createOrder = (
userId: string,
items: OrderItem[]
): RTE.ReaderTaskEither<OrderDeps, OrderError, Order> =>
pipe(
RTE.Do,
// Validate user exists
RTE.bind('user', () =>
pipe(
UserService.findById(userId),
RTE.mapLeft(toOrderError)
)
),
// Validate and get products
RTE.bind('products', () =>
pipe(
items,
A.traverse(RTE.ApplicativePar)(item =>
ProductService.findById(item.productId)
),
RTE.mapLeft(toOrderError)
)
),
// Calculate total
RTE.bind('total', ({ products }) =>
RTE.right(calculateTotal(products, items))
),
// Process payment
RTE.bind('payment', ({ user, total }) =>
pipe(
PaymentService.charge(user, total),
RTE.mapLeft(toOrderError)
)
),
// Create order
RTE.flatMap(({ user, products, total, payment }) =>
createOrderRecord(user, products, items, total, payment)
)
)
```
## Functional Dependency Injection
### Building the Dependency Container
```typescript
// src/deps.ts
import { pipe } from 'fp-ts/function'
import * as TE from 'fp-ts/TaskEither'
import * as RTE from 'fp-ts/ReaderTaskEither'
// Layer 0: Config (no dependencies)
type Config = {
database: { url: string; poolSize: number }
redis: { url: string }
jwt: { secret: string; expiresIn: string }
}
const loadConfig = (): TE.TaskEither<Error, Config> =>
TE.tryCatch(
async () => ({
database: {
url: process.env.DATABASE_URL!,
poolSize: parseInt(process.env.DB_POOL_SIZE || '10'),
},
redis: { url: process.env.REDIS_URL! },
jwt: {
secret: process.env.JWT_SECRET!,
expiresIn: process.env.JWT_EXPIRES || '1d',
},
}),
(e) => new Error(`Config error: ${e}`)
)
// Layer 1: Infrastructure (depends on config)
type Infrastructure = {
config: Config
db: PrismaClient
redis: RedisClient
logger: Logger
}
const buildInfrastructure = (
config: Config
): TE.TaskEither<Error, Infrastructure> =>
pipe(
TE.Do,
TE.bind('db', () =>
TE.tryCatch(
async () => {
const prisma = new PrismaClient({
datasources: { db: { url: config.database.url } },
})
await prisma.$connect()
return prisma
},
(e) => new Error(`Database error: ${e}`)
)
),
TE.bind('redis', () =>
TE.tryCatch(
async () => createRedisClient(config.redis.url),
(e) => new Error(`Redis error: ${e}`)
)
),
TE.bind('logger', () => TE.right(createLogger())),
TE.map(({ db, redis, logger }) => ({
config,
db,
redis,
logger,
}))
)
// Layer 2: Services (depends on infrastructure)
type Services = {
hasher: PasswordHasher
jwt: JwtService
mailer: EmailService
}
const buildServices = (infra: Infrastructure): Services => ({
hasher: createBcryptHasher(),
jwt: createJwtService(infra.config.jwt),
mailer: createEmailService(infra.config),
})
// Full application dependencies
export type AppDeps = Infrastructure & Services
export const buildDeps = (): TE.TaskEither<Error, AppDeps> =>
pipe(
loadConfig(),
TE.flatMap(buildInfrastructure),
TE.map(infra => ({
...infra,
...buildServices(infra),
}))
)
// Cleanup
exporRelated in Backend & APIs
jfrog
IncludedInteract with the JFrog Platform via the JFrog CLI and REST/GraphQL APIs. Use this skill when the user wants to manage Artifactory repositories, upload or download artifacts, manage builds, configure permissions, manage users and groups, work with access tokens, configure JFrog CLI servers, search artifacts, manage properties, set up replication, manage JFrog Projects, run security audits or scans, look up CVE details, query exposures scan results from JFrog Advanced Security, manage release bundles and lifecycle operations, aggregate or export platform data, or perform any JFrog Platform administration task. Also use when the user mentions jf, jfrog, artifactory, xray, distribution, evidence, apptrust, onemodel, graphql, workers, mission control, curation, advanced security, exposures, or any JFrog product name.
cupynumeric-migration-readiness
IncludedPre-migration readiness assessor for porting NumPy to cuPyNumeric. Use BEFORE substantial porting work begins when the user asks whether code will scale on GPU, whether they should migrate to cuPyNumeric, which NumPy patterns transfer cleanly, what must be refactored before porting, or mentions pre-port assessment, scaling analysis, or refactor planning. Inspect the user's source code, look up NumPy usage, cross-reference the cuPyNumeric API support manifest, and distinguish distributed-scaling-friendly patterns from blockers such as unsupported APIs, scalar synchronization, host round-trips, Python/object-heavy control flow, shape/data-dependent branching, and in-place mutation hazards. Produce a verdict of READY, LIGHT REFACTOR, SIGNIFICANT REFACTOR, or NOT RECOMMENDED, with concrete refactor pointers.
alibabacloud-data-agent-skill
IncludedInvoke Alibaba Cloud Apsara Data Agent for Analytics via CLI to perform natural language-driven data analysis on enterprise databases. Data Agent for Analytics is an intelligent data analysis agent developed by Alibaba Cloud Database team for enterprise users. It automatically completes requirement analysis, data understanding, analysis insights, and report generation based on natural language descriptions. This tool supports: discovering data resources (instances/databases/tables) managed in DMS, initiating query or deep analysis sessions, real-time progress tracking, and retrieving analysis conclusions and generated reports. Use this Skill when users need to query databases, analyze data trends, generate data reports, ask questions in natural language, or mention "Data Agent", "data analysis", "database query", "SQL analysis", "data insights".
token-optimizer
IncludedReduce OpenClaw token usage and API costs through smart model routing, heartbeat optimization, budget tracking, and native 2026.2.15 features (session pruning, bootstrap size limits, cache TTL alignment). Use when token costs are high, API rate limits are being hit, or hosting multiple agents at scale. The 4 executable scripts (context_optimizer, model_router, heartbeat_optimizer, token_tracker) are local-only — no network requests, no subprocess calls, no system modifications. Reference files (PROVIDERS.md, config-patches.json) document optional multi-provider strategies that require external API keys and network access if you choose to use them. See SECURITY.md for full breakdown.
resend-cli
IncludedUse this skill when the task is specifically about operating Resend from an AI agent, terminal session, or CI job via the official resend CLI: installing/authenticating the CLI, sending/listing/updating/cancelling emails, batch sends, domains and DNS, webhooks and local listeners, inbound receiving, contacts, topics, segments, broadcasts, templates, API keys, profiles, or debugging Resend CLI/API failures. Trigger on mentions of Resend CLI, `resend`, `resend doctor`, `resend emails send`, `resend domains`, `resend webhooks listen`, `resend emails receiving`, or agent-friendly terminal automation.
alibabacloud-odps-maxframe-coding
IncludedUse this skill for MaxFrame SDK development and documentation navigation on Alibaba Cloud MaxCompute (ODPS). Helps answer MaxFrame API, concept, official example, and supported pandas API questions; create data processing programs; read/write MaxCompute tables; debug jobs (remote or local); and build custom DPE runtime images. Trigger when users mention MaxFrame, MaxCompute with MaxFrame, ODPS table processing, DPE runtime, MaxFrame docs/examples, DataFrame/Tensor operations, or GPU runtime setup. Works for both English and Chinese queries about Alibaba Cloud data processing with MaxFrame.