signalize-memos

Create cached derived signals that recompute when dependencies change.

30|1|Updated Sep 16, 2021

Search Tags:#dependencies #reactivity #memoization #memo #signalize #derived-signal

Ready to run

npx skills add https://github.com/spearwolf/signalize --skill signalize-memos

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: signalize-memos
Source: https://github.com/spearwolf/signalize/tree/main/skills/signalize-memos
Command: npx skills add https://github.com/spearwolf/signalize --skill signalize-memos

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Memos provide cached, derived signals that automatically recompute when their source signals change, reducing recomputation and simplifying state logic in reactive apps.

Core Features & Use Cases

Derived data with createMemo that caches results for efficient reads
Chaining memos to compose complex reactive computations
Support for lazy option to defer computation until read, and lifecycle attachment via SignalGroup

Quick Start

Create a memo with createMemo(() => base.get() * 2) and read its value to obtain the derived result.

Frequently Asked Questions about signalize-memos

High-intent search queries and answers about installing and using this skill.

FAQPage Schema

What is memoization in reactive programming and when do I need it?▼

Memoization in reactive programming caches derived values so they only recompute when dependencies change. You need it when reading derived data frequently and want to avoid redundant calculations in your reactive data flows.

How do I create a cached derived signal that auto-updates?▼

To create a cached derived signal, use createMemo(() => base.get() * 2). This memo caches the computed result and automatically recalculates only when the underlying base signal value changes, ensuring efficient reactive updates.

Can I chain multiple derived signals to compose complex reactive computations?▼

Yes, you can chain multiple derived signals by creating memos that read from other memos. This allows you to compose complex reactive computations layer by layer while maintaining efficient cached updates throughout the dependency chain.

Does lazy memoization work with lifecycle attachment in SignalGroup?▼

Yes, lazy memoization works with SignalGroup lifecycle attachment. The lazy option defers computation until the memo is read, while SignalGroup integration manages the memo's lifecycle, naming, and priority within the reactive system.

Why does my derived signal recompute unnecessarily during state updates?▼

Derived signals recompute unnecessarily when not wrapped in a memo. Using createMemo caches the result and ensures recomputation only occurs when specific dependencies change, preventing redundant calculations during unrelated state updates.