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batching-and-caching批处理和缓存

Agent Skill

batching-and-caching 用于查找、检索和筛选相关信息,适合在 Codex、Claude、Cursor、Gemini CLI 中需要根据关键词、任务场景或来源线索快速定位候选结果时使用。可结合来源仓库、安装命令和原始 README 继续核验具体用法。安装前建议确认权限范围、维护状态,以及是否会触发联网、命令执行或文件读写。

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CodexClaudeCursorGemini CLI

安装说明

本站只整理中文说明和来源信息,不托管安装包,也不代用户安装。

GitHub

来源数

2

许可证

MIT

最后核验

2026-05-01

来源状态

来源可访问

安装方式

通过对话安装

复制提示词发给支持本地命令或 Skills 的 AI 助手,先确认命令和权限,再让它执行。

请帮我安装这个 Agent Skill:batching-and-caching(批处理和缓存)
来源仓库:https://github.com/andrueandersoncs/claude-skill-effect-ts
仓库路径:skills/batching-and-caching
安装命令:
npx skills add andrueandersoncs/claude-skill-effect-ts --skill "batching-and-caching"
安装前请先检查当前环境是否支持对应 CLI,并向我确认将要执行的命令、安装目录、联网范围和文件读写权限;确认后再执行。

命令行安装

复制命令到本机终端执行。该命令会通过 npx skills 从第三方来源获取 Skill;本站只展示命令,不托管安装包,也不自动执行。

AgentSkills.tonpx skills
npx skills add andrueandersoncs/claude-skill-effect-ts --skill "batching-and-caching"

简介

batching-and-caching 用于查找、检索和筛选相关信息,适合在 Codex、Claude、Cursor、Gemini CLI 中需要根据关键词快速定位候选结果时使用。

  • 主要功能是发现并安装 AI 代理的技能。
  • 通过 github 安装,命令为 npx skills add andrueandersoncs/claude-skill-effect-ts --skill "batching-and-caching"。
  • 建议确认权限范围、维护状态,以及是否会触发联网、命令执行或文件读写。
  • 可结合来源仓库和原始 README 继续核验具体用法。

SKILL.md

Batching and Caching in Effect

Overview

Effect provides automatic optimization for API calls:

  • Batching - Combine multiple requests into single API calls
  • Caching - Avoid redundant requests with smart caching
  • Deduplication - Prevent duplicate concurrent requests

This solves the N+1 query problem automatically.

The Problem: N+1 Queries

const program = Effect.gen(function* () {
  const todos = yield* getTodos()

  const owners = yield* Effect.forEach(
    todos,
    (todo) => getUserById(todo.ownerId),
    { concurrency: "unbounded" }
  )
})

Effect's batching transforms this into optimized batch calls.

Request-Based Batching

Step 1: Define Request Types

import { Request } from "effect"

// Define request shape
interface GetUserById extends Request.Request<User, UserNotFound> {
  readonly _tag: "GetUserById"
  readonly id: number
}

// Create tagged constructor
const GetUserById = Request.tagged<GetUserById>("GetUserById")

Step 2: Create Resolver

import { RequestResolver, Effect } from "effect"

// Batched resolver - handles multiple requests at once
const GetUserByIdResolver = RequestResolver.makeBatched(
  (requests: ReadonlyArray<GetUserById>) =>
    Effect.gen(function* () {
      // Single batch API call
      const users = yield* Effect.tryPromise(() =>
        fetch("/api/users/batch", {
          method: "POST",
          body: JSON.stringify({ ids: requests.map((r) => r.id) })
        }).then((res) => res.json())
      )

      // Complete each request with its result
      yield* Effect.forEach(requests, (request, index) =>
        Request.completeEffect(
          request,
          Effect.succeed(users[index])
        )
      )
    })
)

Step 3: Define Query

const getUserById = (id: number) =>
  Effect.request(GetUserById({ id }), GetUserByIdResolver)

Step 4: Use with Automatic Batching

const program = Effect.gen(function* () {
  const todos = yield* getTodos()

  const owners = yield* Effect.forEach(
    todos,
    (todo) => getUserById(todo.ownerId),
    { concurrency: "unbounded" }
  )
})

Resolver Types

Standard Resolver (No Batching)

const SingleUserResolver = RequestResolver.fromEffect(
  (request: GetUserById) =>
    Effect.tryPromise(() =>
      fetch(`/api/users/${request.id}`).then((r) => r.json())
    )
)

Batched Resolver

const BatchedUserResolver = RequestResolver.makeBatched(
  (requests: ReadonlyArray<GetUserById>) =>
    // Handle all requests in one call
    batchFetch(requests)
)

Resolver with Context

const UserResolverWithContext = RequestResolver.makeBatched(
  (requests: ReadonlyArray<GetUserById>) =>
    Effect.gen(function* () {
      // Access services from context
      const httpClient = yield* HttpClient
      const logger = yield* Logger

      yield* logger.info(`Batching ${requests.length} user requests`)

      return yield* httpClient.post("/api/users/batch", {
        ids: requests.map((r) => r.id)
      })
    })
)

// Provide context to resolver
const ContextualResolver = UserResolverWithContext.pipe(
  RequestResolver.provideContext(context)
)

Caching

Effect.cached - Memoize Effect Result

import { Effect } from "effect"

const fetchConfig = Effect.promise(() =>
  fetch("/api/config").then((r) => r.json())
)

const cachedConfig = yield* Effect.cached(fetchConfig)

const config1 = yield* cachedConfig
const config2 = yield* cachedConfig

Effect.cachedWithTTL - Time-Based Expiry

const cachedUser = yield* Effect.cachedWithTTL(
  fetchCurrentUser,
  "5 minutes"
)

const user1 = yield* cachedUser
yield* Effect.sleep("6 minutes")
const user2 = yield* cachedUser

Effect.cachedInvalidateWithTTL - Manual Invalidation

const [cachedUser, invalidate] = yield* Effect.cachedInvalidateWithTTL(
  fetchCurrentUser,
  "5 minutes"
)

const user = yield* cachedUser
yield* invalidate
const freshUser = yield* cachedUser

Cache Service

For more control, use the Cache service:

import { Cache } from "effect"

const program = Effect.gen(function* () {
  const cache = yield* Cache.make({
    capacity: 100,
    timeToLive: "10 minutes",
    lookup: (userId: string) => fetchUser(userId)
  })

  const user1 = yield* cache.get("user-1")
  const user2 = yield* cache.get("user-1")

  const isCached = yield* cache.contains("user-1")

  yield* cache.invalidate("user-1")

  const stats = yield* cache.cacheStats
})

Request Caching

Requests are automatically cached within a query context:

const program = Effect.gen(function* () {
  const user1 = yield* getUserById(1)
  const user2 = yield* getUserById(1)

  const user3 = yield* getUserById(2)
})

Disabling Request Caching

const noCaching = getUserById(1).pipe(
  Effect.withRequestCaching(false)
)

Custom Cache for Requests

const customCache = yield* Request.makeCache({
  capacity: 1000,
  timeToLive: "30 minutes"
})

const program = getUserById(1).pipe(
  Effect.withRequestCache(customCache)
)

Disabling Batching

const noBatching = program.pipe(
  Effect.withRequestBatching(false)
)

Complete Example

import { Effect, Request, RequestResolver, Schema } from "effect"

// Error types
class UserNotFound extends Schema.TaggedError<UserNotFound>()(
  "UserNotFound",
  { id: Schema.Number }
) {}

// Request type
interface GetUserById extends Request.Request<User, UserNotFound> {
  readonly _tag: "GetUserById"
  readonly id: number
}
const GetUserById = Request.tagged<GetUserById>("GetUserById")

// Batched resolver
const UserResolver = RequestResolver.makeBatched(
  (requests: ReadonlyArray<GetUserById>) =>
    Effect.gen(function* () {
      const ids = requests.map((r) => r.id)

      const response = yield* Effect.tryPromise({
        try: () =>
          fetch("/api/users/batch", {
            method: "POST",
            headers: { "Content-Type": "application/json" },
            body: JSON.stringify({ ids })
          }).then((r) => r.json() as Promise<User[]>),
        catch: () => new Error("Batch fetch failed")
      })

      yield* Effect.forEach(requests, (request, index) => {
        const user = response[index]
        return user
          ? Request.completeEffect(request, Effect.succeed(user))
          : Request.completeEffect(
              request,
              Effect.fail(new UserNotFound({ id: request.id }))
            )
      })
    })
)

// Query function
const getUserById = (id: number) =>
  Effect.request(GetUserById({ id }), UserResolver)

// Usage - automatically batched
const program = Effect.gen(function* () {
  const todos = yield* getTodos()

  const owners = yield* Effect.forEach(
    todos,
    (todo) => getUserById(todo.ownerId),
    { concurrency: "unbounded" }
  )

  return owners
})

Best Practices

  1. Use batching for N+1 scenarios - Especially with databases/APIs
  2. Cache expensive computations - Use Effect.cached
  3. Set appropriate TTLs - Balance freshness vs performance
  4. Use Request deduplication - Automatic with Effect.request
  5. Batch at API boundaries - Group related requests

Additional Resources

For comprehensive batching and caching documentation, consult ${CLAUDE_PLUGIN_ROOT}/references/llms-full.txt.

Search for these sections:

  • "Batching" for complete batching guide
  • "Caching" for caching patterns
  • "Cache" for Cache service
  • "Caching Effects" for Effect.cached patterns

适合场景

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02

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03

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04

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