Agent skill

effect-ts

Effect-TS (Effect) comprehensive development guide for TypeScript. Use when building, debugging, reviewing, or generating Effect code. Covers typed error modeling (expected errors vs defects), structured concurrency (fibers), dependency injection (ServiceMap/Context + Layers), resource management (Scope), retry/scheduling (Schedule), streams, Schema validation, observability (OpenTelemetry), HTTP client/server, Effect AI (LLM integration), and MCP servers. Critical for AI code generation: includes exhaustive wrong-vs-correct API tables preventing hallucinated Effect code. Supports both Effect v3 (stable) and v4 (beta). Use this skill whenever code imports from 'effect', '@effect/platform', '@effect/ai', or the user mentions Effect-TS, typed errors with Effect, functional TypeScript with Effect, ServiceMap, Layer, or Schema from Effect. Also trigger when generating new TypeScript projects that could benefit from Effect patterns, even if the user doesn't explicitly name the library.

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npx add-skill https://github.com/tenequm/skills/tree/main/skills/effect-ts

SKILL.md

Effect-TS

Effect is a TypeScript library for building production-grade software with typed errors, structured concurrency, dependency injection, and built-in observability.

Version Detection

Before writing Effect code, detect which version the user is on:

bash
# Check installed version
cat package.json | grep '"effect"'
  • v3.x (stable, most production codebases): Context.Tag, Effect.catchAll, Effect.fork, Data.TaggedError
  • v4.x (beta, Feb 2026+): ServiceMap.Service, Effect.catch, Effect.forkChild, Schema.TaggedErrorClass

If the version is unclear, ask the user. Default to v3 patterns for existing codebases, v4 for new projects.

Primary Documentation Sources

AI Guardrails: Critical Corrections

LLM outputs frequently contain incorrect Effect APIs. Verify every API against the reference docs before using it.

Common hallucinations (both versions):

Wrong (AI often generates) Correct
Effect.cachedWithTTL(...) Cache.make({ capacity, timeToLive, lookup })
Effect.cachedInvalidateWithTTL(...) cache.invalidate(key) / cache.invalidateAll()
Effect.mapError(effect, fn) Effect.mapError(fn) in pipe, or use Effect.catchTag
import { Schema } from "@effect/schema" import { Schema } from "effect" (v3.10+ and all v4)
import { JSONSchema } from "@effect/schema" import { JSONSchema } from "effect" (v3.10+)
JSON Schema Draft 2020-12 Effect Schema generates Draft-07
"thread-local storage" "fiber-local storage" via FiberRef (v3) / ServiceMap.Reference (v4)
fibers are "cancelled" fibers are "interrupted"
all queues have back-pressure only bounded queues; sliding/dropping do not
new MyError("message") new MyError({ message: "..." }) (Schema errors take objects)

v3-specific hallucinations:

Wrong Correct (v3)
Effect.Service (function call) class Foo extends Effect.Service<Foo>()("id", {})
Effect.match(effect, { ... }) Effect.match(effect, { onSuccess, onFailure })
Effect.provide(layer1, layer2) Effect.provide(Layer.merge(layer1, layer2))

v4-specific hallucinations (AI may mix v3/v4):

Wrong (v3 API used in v4 code) Correct (v4)
Context.Tag("X") ServiceMap.Service<X>(id) or class syntax
Effect.catchAll(fn) Effect.catch(fn)
Effect.fork(effect) Effect.forkChild(effect)
Effect.forkDaemon(effect) Effect.forkDetach(effect)
Data.TaggedError Schema.TaggedErrorClass
FiberRef.get(ref) yield* References.X (ServiceMap.Reference)
yield* ref (Ref as Effect) yield* Ref.get(ref) (Ref is no longer an Effect)
yield* fiber (Fiber as Effect) yield* Fiber.join(fiber) (Fiber is no longer Effect)
Logger.Default / Logger.Live Logger.layer (v4 naming convention)
Schema.TaggedError Schema.TaggedErrorClass

Read references/llm-corrections.md for the exhaustive corrections table.

Progressive Disclosure

Read only the reference files relevant to your task:

  • Error modeling or typed failures → references/error-modeling.md
  • Services, DI, or Layer wiring → references/dependency-injection.md
  • Retries, timeouts, or backoff → references/retry-scheduling.md
  • Fibers, forking, or parallel work → references/concurrency.md
  • Streams, queues, or SSE → references/streams.md
  • Resource lifecycle or cleanup → references/resource-management.md
  • Schema validation or decoding → references/schema.md
  • Logging, metrics, or tracing → references/observability.md
  • HTTP clients or API calls → references/http.md
  • HTTP API servers → references/http.md (covers both client and server)
  • LLM/AI integration → references/effect-ai.md
  • Testing Effect code → references/testing.md
  • Migrating from async/await → references/migration-async.md
  • Migrating from v3 to v4 → references/migration-v4.md
  • Core types, gen, pipe, running → references/core-patterns.md
  • Full wrong-vs-correct API table → references/llm-corrections.md

Core Workflow

  1. Detect version from package.json before writing any code
  2. Clarify boundaries: identify where IO happens, keep core logic as Effect values
  3. Choose style: use Effect.gen for sequential logic, pipelines for simple transforms. In v4, prefer Effect.fn("name") for named functions
  4. Model errors explicitly: type expected errors in the E channel; treat bugs as defects
  5. Model dependencies with services and layers; keep interfaces free of construction logic
  6. Manage resources with Scope when opening/closing things (files, connections, etc.)
  7. Provide layers and run effects only at program edges (NodeRuntime.runMain or ManagedRuntime)
  8. Verify APIs exist before using them - consult https://tim-smart.github.io/effect-io-ai/ or source docs

Starter Function Set

Start with these ~20 functions (the official recommended set):

Creating effects: Effect.succeed, Effect.fail, Effect.sync, Effect.tryPromise

Composition: Effect.gen (+ Effect.fn in v4), Effect.andThen, Effect.map, Effect.tap, Effect.all

Running: Effect.runPromise, NodeRuntime.runMain (preferred for entry points)

Error handling: Effect.catchTag, Effect.catchAll (v3) / Effect.catch (v4), Effect.orDie

Resources: Effect.acquireRelease, Effect.acquireUseRelease, Effect.scoped

Dependencies: Effect.provide, Effect.provideService

Key modules: Effect, Schema, Layer, Option, Either (v3) / Result (v4), Array, Match

Import Patterns

Always use barrel imports from "effect":

typescript
import { Effect, Schema, Layer, Option, Stream } from "effect"

For companion packages, import from the package name:

typescript
import { NodeRuntime } from "@effect/platform-node"
import { NodeSdk } from "@effect/opentelemetry"

Avoid deep module imports (effect/Effect) unless your bundler requires it for tree-shaking.

Output Standards

  • Show imports in every code example
  • Prefer Effect.gen (imperative) for multi-step logic; pipelines for transforms
  • In v4, use Effect.fn("name") instead of bare Effect.gen for named functions
  • Never call Effect.runPromise / Effect.runSync inside library code - only at program edges
  • Use NodeRuntime.runMain for CLI/server entry points (handles SIGINT gracefully)
  • Use ManagedRuntime when integrating Effect into non-Effect frameworks (Hono, Express, etc.)
  • Always return yield* when raising an error in a generator (ensures TS understands control flow)
  • Avoid point-free/tacit usage: write Effect.map((x) => fn(x)) not Effect.map(fn) (generics get erased)
  • Keep dependency graphs explicit (services, layers, tags)
  • State the Effect<A, E, R> shape when it helps design decisions

Agent Quality Checklist

Before outputting Effect code, verify:

  • Every API exists (check against tim-smart API list or source docs)
  • Imports are from "effect" (not @effect/schema, @effect/io, etc.)
  • Version matches the user's codebase (v3 vs v4 syntax)
  • Expected errors are typed in E; unexpected failures are defects
  • run* is called only at program edges, not inside library code
  • Resources opened with acquireRelease are wrapped in Effect.scoped
  • Layers are provided before running (no missing R requirements)
  • Generator bodies use yield* (not yield without *)
  • Error raises in generators use return yield* pattern

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