Token导航 LogoToken导航TokenDH.com
开发需要联网github未标认证来源可访问许可证需确认审计未展示

db-core%2flive-queriesdb core%2flive 查询

Agent Skill

db-core%2flive-queries 用于处理 GitHub 仓库、Issue、Pull Request 和代码协作信息,适合在 Codex、Claude、Cursor、Gemini CLI 中需要围绕仓库状态、代码变更或协作事项进行整理时使用。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。

总安装

261

周安装

11

GitHub Stars

3,738

下载量

92
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

unknown

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:db-core%2flive-queries(db core%2flive 查询)
来源仓库:https://github.com/tanstack/db
仓库路径:skills/db-core%2Flive-queries
安装命令:
npx skills add https://github.com/tanstack/db --skill db-core/live-queries
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。

skills.shnpx skills
npx skills add https://github.com/tanstack/db --skill db-core/live-queries

简介

db-core/live-queries 提供 TanStack DB 的流式查询能力,支持 SQL 风格链式操作与增量视图维护。

  • 它自动追踪数据变化并仅重算受影响部分,实现低延迟响应,优于传统 JavaScript 过滤逻辑。
  • 使用时需先配置 collection,再通过 liveQuery 方法构建派生数据集,绑定 UI 渲染更新。
  • 建议优先选用内置聚合与字符串函数,减少手动循环带来的性能损耗与 token 开销。
  • db-core%2flive-queries 属于开发类 Skill,可作为该场景下的辅助能力补充。

SKILL.md

Live Queries

This skill builds on db-core.

TanStack DB live queries use a SQL-like fluent query builder to create reactive derived collections that automatically update when underlying data changes. The query engine compiles queries into incremental view maintenance (IVM) pipelines using differential dataflow (d2ts), so only deltas are recomputed.

All operators, string functions, math functions, and aggregates are incrementally maintained. Prefer them over equivalent JS code.

Setup

Minimal example using the core API (no framework hooks):

import {
  createCollection,
  createLiveQueryCollection,
  liveQueryCollectionOptions,
  eq,
} from '@tanstack/db'

// Assume usersCollection is already created via createCollection(...)

// Option 1: createLiveQueryCollection shorthand
const activeUsers = createLiveQueryCollection((q) =>
  q
    .from({ user: usersCollection })
    .where(({ user }) => eq(user.active, true))
    .select(({ user }) => ({
      id: user.id,
      name: user.name,
      email: user.email,
    })),
)

// Option 2: full options via liveQueryCollectionOptions
const activeUsers2 = createCollection(
  liveQueryCollectionOptions({
    query: (q) =>
      q
        .from({ user: usersCollection })
        .where(({ user }) => eq(user.active, true))
        .select(({ user }) => ({
          id: user.id,
          name: user.name,
        })),
    getKey: (user) => user.id,
  }),
)

// The result is a live collection -- iterate, subscribe, or use as source
for (const user of activeUsers) {
  console.log(user.name)
}

Core Patterns

1. Filtering with where + operators

Chain .where() calls (ANDed together) using expression operators. Use and(), or(), not() for complex logic.

import { eq, gt, or, and, not, inArray, like } from '@tanstack/db'

const results = createLiveQueryCollection((q) =>
  q
    .from({ user: usersCollection })
    .where(({ user }) => eq(user.active, true))
    .where(({ user }) =>
      and(
        gt(user.age, 18),
        or(eq(user.role, 'admin'), eq(user.role, 'moderator')),
        not(inArray(user.id, bannedIds)),
      ),
    ),
)

Boolean column references work directly:

.where(({ user }) => user.active)        // bare boolean ref
.where(({ user }) => not(user.suspended)) // negated boolean ref

2. Joining two collections

Join conditions must use eq() (equality only -- IVM constraint). Default join type is left. Convenience methods: leftJoin, rightJoin, innerJoin, fullJoin.

import { eq } from '@tanstack/db'

const userPosts = createLiveQueryCollection((q) =>
  q
    .from({ user: usersCollection })
    .innerJoin({ post: postsCollection }, ({ user, post }) =>
      eq(user.id, post.userId),
    )
    .select(({ user, post }) => ({
      userName: user.name,
      postTitle: post.title,
    })),
)

Multiple joins:

q.from({ user: usersCollection })
  .join({ post: postsCollection }, ({ user, post }) => eq(user.id, post.userId))
  .join({ comment: commentsCollection }, ({ post, comment }) =>
    eq(post.id, comment.postId),
  )

3. Aggregation with groupBy + having

Use groupBy to group rows, then aggregate in select. Filter groups with having. The $selected namespace lets having and orderBy reference fields defined in select.

import { count, sum, gt } from '@tanstack/db'

const topCustomers = createLiveQueryCollection((q) =>
  q
    .from({ order: ordersCollection })
    .groupBy(({ order }) => order.customerId)
    .select(({ order }) => ({
      customerId: order.customerId,
      totalSpent: sum(order.amount),
      orderCount: count(order.id),
    }))
    .having(({ $selected }) => gt($selected.totalSpent, 1000))
    .orderBy(({ $selected }) => $selected.totalSpent, 'desc')
    .limit(10),
)

Without groupBy, aggregates in select treat the entire collection as one group:

const stats = createLiveQueryCollection((q) =>
  q.from({ user: usersCollection }).select(({ user }) => ({
    totalUsers: count(user.id),
    avgAge: avg(user.age),
  })),
)

4. Standalone derived collection with createLiveQueryCollection

Derived collections are themselves collections. Use one as a source for another query to cache intermediate results:

// Base derived collection
const activeUsers = createLiveQueryCollection((q) =>
  q.from({ user: usersCollection }).where(({ user }) => eq(user.active, true)),
)

// Second query uses the derived collection as its source
const activeUserPosts = createLiveQueryCollection((q) =>
  q
    .from({ user: activeUsers })
    .join({ post: postsCollection }, ({ user, post }) =>
      eq(user.id, post.userId),
    )
    .select(({ user, post }) => ({
      userName: user.name,
      postTitle: post.title,
    })),
)

Create derived collections once at module scope and reuse them. Do not recreate on every render or navigation.

Virtual Properties

Live query results include computed, read-only virtual properties on every row:

  • $synced: true when the row is confirmed by sync; false when it is still optimistic.
  • $origin: "local" if the last confirmed change came from this client, otherwise "remote".
  • $key: the row key for the result.
  • $collectionId: the source collection ID.

These props are added automatically and can be used in where, select, and orderBy clauses. Do not persist them back to storage.

Includes (Subqueries in Select)

Embed a correlated subquery inside select() to produce hierarchical (nested) data. The subquery must contain a where with an eq() that correlates a parent field with a child field. Three materialization modes are available.

Collection includes (default)

Return a child Collection on each parent row:

import { eq, createLiveQueryCollection } from '@tanstack/db'

const projectsWithIssues = createLiveQueryCollection((q) =>
  q.from({ p: projectsCollection }).select(({ p }) => ({
    id: p.id,
    name: p.name,
    issues: q
      .from({ i: issuesCollection })
      .where(({ i }) => eq(i.projectId, p.id))
      .select(({ i }) => ({
        id: i.id,
        title: i.title,
      })),
  })),
)

// Each row's `issues` is a live Collection
for (const project of projectsWithIssues) {
  console.log(project.name, project.issues.toArray)
}

Array includes with toArray()

Wrap the subquery in toArray() to get a plain array of scalar values instead of a Collection:

import { eq, toArray, createLiveQueryCollection } from '@tanstack/db'

const messagesWithParts = createLiveQueryCollection((q) =>
  q.from({ m: messagesCollection }).select(({ m }) => ({
    id: m.id,
    contentParts: toArray(
      q
        .from({ c: chunksCollection })
        .where(({ c }) => eq(c.messageId, m.id))
        .orderBy(({ c }) => c.timestamp)
        .select(({ c }) => c.text),
    ),
  })),
)
// row.contentParts is string[]

Concatenated scalar with concat(toArray())

Wrap toArray() in concat() to join the scalar results into a single string:

import { eq, toArray, concat, createLiveQueryCollection } from '@tanstack/db'

const messagesWithContent = createLiveQueryCollection((q) =>
  q.from({ m: messagesCollection }).select(({ m }) => ({
    id: m.id,
    content: concat(
      toArray(
        q
          .from({ c: chunksCollection })
          .where(({ c }) => eq(c.messageId, m.id))
          .orderBy(({ c }) => c.timestamp)
          .select(({ c }) => c.text),
      ),
    ),
  })),
)
// row.content is a single concatenated string

Includes rules

  • The subquery must have a where clause with an eq() correlating a parent alias with a child alias. The library extracts this automatically as the join condition.
  • toArray() works with both scalar selects (e.g., select(({c}) => c.text)string[]) and object selects (e.g., select(({c}) => ({id: c.id, title: c.title}))Array<{id, title}>).
  • concat(toArray()) requires a scalar select to concatenate into a string.
  • Collection includes (bare subquery) require an object select.
  • Includes subqueries are compiled into the same incremental pipeline as the parent query -- they are not separate live queries.

One-Shot Queries with queryOnce

For non-reactive, one-time snapshots use queryOnce. It creates a live query collection, preloads it, extracts the results, and cleans up automatically.

import { eq, queryOnce } from '@tanstack/db'

const activeUsers = await queryOnce((q) =>
  q
    .from({ user: usersCollection })
    .where(({ user }) => eq(user.active, true))
    .select(({ user }) => ({ id: user.id, name: user.name })),
)

// With findOne — resolves to T | undefined
const user = await queryOnce((q) =>
  q
    .from({ user: usersCollection })
    .where(({ user }) => eq(user.id, userId))
    .findOne(),
)

Use queryOnce for scripts, loaders, data export, tests, or AI/LLM context building. For UI bindings and reactive updates, use live queries instead.

Reactive Effects (createEffect)

Reactive effects respond to query result *changes* without materializing the full result set. Effects fire callbacks when rows enter, exit, or update within a query result — like a database trigger on an arbitrary live query.

import { createEffect, eq } from '@tanstack/db'

const effect = createEffect({
  query: (q) =>
    q
      .from({ msg: messagesCollection })
      .where(({ msg }) => eq(msg.role, 'user')),
  skipInitial: true,
  onEnter: async (event, ctx) => {
    await processNewMessage(event.value, { signal: ctx.signal })
  },
  onExit: (event) => {
    console.log('Message left result set:', event.key)
  },
  onError: (error, event) => {
    console.error(`Failed to process ${event.key}:`, error)
  },
})

// Dispose when no longer needed
await effect.dispose()
Use caseApproach
Display query results in UILive query collection + useLiveQuery
React to changes (side effects)createEffect with onEnter / onUpdate / onExit
Inspect full batch of changescreateEffect with onBatch

Key options: id (optional), query, skipInitial (skip existing rows on init), onEnter, onUpdate, onExit, onBatch, onError, onSourceError. The ctx.signal aborts when the effect is disposed.

Common Mistakes

CRITICAL: Using === instead of eq()

JavaScript === in a where callback returns a boolean primitive, not an expression object. Throws InvalidWhereExpressionError.

// WRONG
q.from({ user: usersCollection }).where(({ user }) => user.active === true)

// CORRECT
q.from({ user: usersCollection }).where(({ user }) => eq(user.active, true))

CRITICAL: Filtering in JS instead of query operators

JS .filter() / .map() on the result array throws away incremental maintenance -- the JS code re-runs from scratch on every change.

// WRONG -- re-runs filter on every change
const { data } = useLiveQuery((q) => q.from({ todos: todosCollection }))
const active = data.filter((t) => t.completed === false)

// CORRECT -- incrementally maintained
const { data } = useLiveQuery((q) =>
  q
    .from({ todos: todosCollection })
    .where(({ todos }) => eq(todos.completed, false)),
)

HIGH: Not using the full operator set

The library provides string functions (upper, lower, length, concat), math (add), utility (coalesce), and aggregates (count, sum, avg, min, max). All are incrementally maintained. Prefer them over JS equivalents.

// WRONG
.fn.select((row) => ({
  name: row.user.name.toUpperCase(),
  total: row.order.price + row.order.tax,
}))

// CORRECT
.select(({ user, order }) => ({
  name: upper(user.name),
  total: add(order.price, order.tax),
}))

HIGH:.distinct() without.select()

distinct() deduplicates by the selected columns. Without select(), throws DistinctRequiresSelectError.

// WRONG
q.from({ user: usersCollection }).distinct()

// CORRECT
q.from({ user: usersCollection })
  .select(({ user }) => ({ country: user.country }))
  .distinct()

HIGH:.having() without.groupBy()

having filters aggregated groups. Without groupBy, there are no groups. Throws HavingRequiresGroupByError.

// WRONG
q.from({ order: ordersCollection }).having(({ order }) =>
  gt(count(order.id), 5),
)

// CORRECT
q.from({ order: ordersCollection })
  .groupBy(({ order }) => order.customerId)
  .having(({ order }) => gt(count(order.id), 5))

HIGH:.limit() /.offset() without.orderBy()

Without deterministic ordering, limit/offset results are non-deterministic and cannot be incrementally maintained. Throws LimitOffsetRequireOrderByError.

// WRONG
q.from({ user: usersCollection }).limit(10)

// CORRECT
q.from({ user: usersCollection })
  .orderBy(({ user }) => user.name)
  .limit(10)

HIGH: Join condition using non-eq() operator

The differential dataflow join operator only supports equality joins. Using gt(), like(), etc. throws JoinConditionMustBeEqualityError.

// WRONG
q.from({ user: usersCollection }).join(
  { post: postsCollection },
  ({ user, post }) => gt(user.id, post.userId),
)

// CORRECT
q.from({ user: usersCollection }).join(
  { post: postsCollection },
  ({ user, post }) => eq(user.id, post.userId),
)

MEDIUM: Passing source directly instead of {alias: collection}

from() and join() require sources wrapped as {alias: collection}. Passing the collection directly throws InvalidSourceTypeError.

// WRONG
q.from(usersCollection)

// CORRECT
q.from({ users: usersCollection })

Tension: Query expressiveness vs. IVM constraints

The query builder looks like SQL but has constraints that SQL does not:

  • Equality joins only -- eq() is the only allowed join condition operator.
  • orderBy required for limit/offset -- non-deterministic pagination cannot be incrementally maintained.
  • distinct requires select -- deduplication needs an explicit projection.
  • fn.select() cannot be used with groupBy() -- the compiler must statically analyze select to discover aggregate functions.

These constraints exist because the underlying d2ts differential dataflow engine requires them for correct incremental view maintenance.

See also: react-db/SKILL.md for React hooks (useLiveQuery, useLiveSuspenseQuery, useLiveInfiniteQuery).

References

适合场景

01

用户想查找某类 Agent Skill 时

02

需要根据任务场景推荐可安装能力包时

03

需要对比不同来源的安装命令和来源信息时

能力概览

能力 1

按任务关键词查找相关 Skills

能力 2

展示可复制的安装命令

能力 3

保留来源站点、仓库和原始说明,方便继续核验

安装后应在对应宿主中按原始 README 的触发条件使用;具体调用方式请以来源页面和 README 为准。

平台分布

Codex

35.17%
按下载量换算32

Claude

30.31%
按下载量换算28

Cursor

21.44%
按下载量换算20

Gemini CLI

10.3%
按下载量换算9

安全审计

暂无安全审计结果可展示。

权限和风险

需要联网

该 Skill 可能需要联网访问来源站点、仓库或外部 API;具体网络访问范围需要结合源码和 README 复核。

安装前确认

本站仅展示第三方公开信息,不托管安装包,不提供自动安装或运行环境。安装前应自行审查源码、依赖和命令行为。当前只有一个来源,正式发布前建议补源仓库或其他目录站核验。

来源信息

继续浏览同类 Skills