Can I control the cache duration?

Yes, the skill provides implementation patterns for using Effect.cachedWithTTL and the Cache service to set specific expiration times for your data.

Does it support manual cache invalidation?

Absolutely, it includes patterns for Effect.cachedInvalidateWithTTL to allow programmatic cache clearing when data becomes stale.

Does it prevent duplicate concurrent requests?

Yes, it implements request deduplication to ensure that multiple parts of your application requesting the same resource at the same time only trigger a single execution.

How does this skill help with the N+1 problem?

It guides you in creating RequestResolvers that automatically group multiple individual requests into a single batched API call, preventing excessive round-trips to your database or API.

Is this compatible with any API or database?

Yes, it uses Effect's standard Request and RequestResolver abstractions which can wrap fetch, database clients, or any other data source regardless of the protocol.

Effect Batching & Caching

Name: Effect Batching & Caching
Author: andrueandersoncs

byandrueandersoncs

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API Development

Optimizes API calls and data fetching in Effect TS applications by implementing automated request batching, smart caching, and N+1 query resolution.

This skill provides specialized guidance for implementing high-performance data fetching patterns using the Effect ecosystem. It helps developers eliminate N+1 query problems through automated request batching, reduce redundant network traffic with intelligent caching (including TTL and manual invalidation), and manage concurrent request deduplication. Whether you are building complex microservices or data-heavy frontends, this skill ensures your Effect-based applications handle external requests efficiently and reliably by providing optimized RequestResolver and Cache service implementation patterns.

Key Features

013 GitHub stars

02Configurable caching with TTL (Time-To-Live) and manual invalidation

03Integrated Cache service for high-performance data management

04Custom RequestResolver implementations for complex API integrations

05Automated N+1 query resolution through request batching

06Request-level deduplication for concurrent API calls

Use Cases

01Implementing standardized data loader patterns for GraphQL or REST backends

02Optimizing multiple database lookups in a loop into a single batch query

03Reducing API costs and latency by caching expensive computation results

What are Skills?·How to Install

Install with 🐟 Skill.Fish

npx skillfish add andrueandersoncs/claude-skill-effect-ts batching-caching

For use in Claude.ai and ChatGPT

Download Skill