tanstack-query

TanStack Query v5 performance optimization for data fetching, caching, mutations, and query patterns. This skill should be used when using useQuery, useMutation, queryClient, prefetch patterns, or TanStack Query caching. This skill does NOT cover generating query hooks from OpenAPI (use orval skill) or mocking API responses in tests (use test-msw skill).

Jump to install

Repository: pproenca/dot-skills
Last source activity: May 14, 2026 at 18:16
Detected SKILL.md language: English
Stars: 194
Forks: 17

Install options

The review-first prompt is selected by default. You can switch to a direct command or download a local copy.

Install with Codex or Claude Copy this prompt, paste it into Codex, Claude, or another assistant, and let it review the skill page and install it for you.

A direct command skips the review prompt. Inspect the source before running it.

npx skills add https://github.com/pproenca/dot-skills --skill tanstack-query

The command stays on one line. Scroll horizontally to inspect it before copying.

Prefer a local copy? Download the files currently available to SkillsMP.

Review the source files

Read SKILL.md and any companion files shown by SkillsMP before deciding whether to install.

File Explorer

45 files

SKILL.md

Source instructions · Read-only preview

Back to search Back to installation

drizzle-nextjs-postgres

Drizzle ORM against PostgreSQL inside a Next.js App Router app. Covers client construction (globalThis singleton across HMR, serverless pool sizing, `prepare:false` behind PgBouncer/Supavisor, driver choice when you need interactive transactions, `server-only`), reads in Server Components under Next.js 16 Cache Components (`use cache` superseding `unstable_cache` and the `revalidate`/`dynamic` segment configs, Suspense boundaries, React `cache()` dedupe), Server Actions (authorization inside the action, `updateTag` vs `revalidateTag`, `after()`), Postgres schema types (timestamptz, identity vs serial, jsonb, numeric-as-string, bigint modes), drizzle-kit migrations (generate vs push, CONCURRENTLY outside the migrator, NOT VALID constraints, rename prompts), transactions and pooled connections, and Postgres query traps (keyset pagination, count cost, driver-dependent `db.execute()` shape, NOT IN nulls, prepared statements). Use when writing or reviewing Drizzle + Postgres code in Next.js.

2026-07-24

relational-data-modeling

Corrects the wrong defaults a model has when designing a relational schema — the DDL decisions an experienced engineer makes differently. Use when creating or reviewing tables, migrations, ER models, or ORM schema definitions. Covers identity and keys (surrogate vs natural, identity vs serial, uuidv7, composite keys that make cross-tenant references impossible), relationships (polymorphic foreign keys the database cannot enforce, referential actions, unindexed FK columns, disjoint subtypes), invariants the engine can prove instead of application code (EXCLUDE, partial unique indexes, CHECK limits, deferrable cycles, NOT VALID), types (timestamptz, exact money, range types, enum vs lookup table), derived and encoded data (generated columns, JSONB as an escape hatch), and time (events vs in-place updates, soft-delete flags that silently disable constraints, temporal keys). NOT for query tuning, index selection for read paths, or connection pooling.

2026-07-23

relational-database-design

Distills a logical relational-database design methodology into rules an agent applies while designing or reviewing a schema. Covers the design sequence (mission → tables → fields → keys → relationships → business rules → views → integrity review), one-subject-per-table decomposition, atomic single-valued fields, candidate/primary/foreign keys, relationship types with deletion rules and participation, the four levels of data integrity, database-vs-application business rules, validation tables, views for derived data, and the flat-file / spreadsheet / RDBMS-driven antipatterns to avoid. The structure is logical and RDBMS-agnostic, and normalized by construction. Use when designing a new relational schema, reviewing or refactoring an existing one, resolving redundant or repeating data, choosing keys, modeling relationships, or deciding where a constraint belongs.

2026-07-23

View all from this repository

name	tanstack-query
description	TanStack Query v5 performance optimization for data fetching, caching, mutations, and query patterns. This skill should be used when using useQuery, useMutation, queryClient, prefetch patterns, or TanStack Query caching. This skill does NOT cover generating query hooks from OpenAPI (use orval skill) or mocking API responses in tests (use test-msw skill).
license	MIT
metadata	{"author":"community","version":"1.0.0"}

TanStack Query Best Practices

Comprehensive performance optimization guide for TanStack Query v5 applications. Contains 40 rules across 8 categories, prioritized by impact to guide automated refactoring and code generation.

When to Apply

Reference these guidelines when:

Writing new queries, mutations, or data fetching logic
Implementing caching strategies (staleTime, gcTime)
Reviewing code for performance issues or request waterfalls
Refactoring existing TanStack Query code
Implementing infinite queries, Suspense, or optimistic updates

Rule Categories by Priority

Priority	Category	Impact	Prefix
1	Query Key Structure	CRITICAL	`tquery-`
2	Caching Configuration

tanstack-query

Install options

Review the source files

TanStack Query Best Practices

When to Apply

Rule Categories by Priority

TanStack Query Best Practices

When to Apply

Rule Categories by Priority

Quick Reference

1. Query Key Structure (CRITICAL)

2. Caching Configuration (CRITICAL)

3. Mutation Patterns (HIGH)

4. Prefetching & Waterfalls (HIGH)

5. Infinite Queries (MEDIUM)

6. Suspense Integration (MEDIUM)

7. Error & Retry Handling (MEDIUM)

8. Render Optimization (LOW-MEDIUM)

How to Use

Related Skills

Full Compiled Document

tanstack-query

Source facts

Install options

Review the source files

More from this repository

More from this repository

TanStack Query Best Practices

When to Apply

Rule Categories by Priority

TanStack Query Best Practices

When to Apply

Rule Categories by Priority

Quick Reference

1. Query Key Structure (CRITICAL)

2. Caching Configuration (CRITICAL)

3. Mutation Patterns (HIGH)

4. Prefetching & Waterfalls (HIGH)

5. Infinite Queries (MEDIUM)

6. Suspense Integration (MEDIUM)

7. Error & Retry Handling (MEDIUM)

8. Render Optimization (LOW-MEDIUM)

How to Use

Related Skills

Full Compiled Document