caching-strategy-advisor

Solid

Recommends the right caching layer, TTL strategy, and invalidation approach for any application bottleneck.

AI & Automation 9 stars 1 forks Updated 6 days ago MIT

Install

View on GitHub

Quality Score: 85/100

Stars 20%
33
Recency 20%
100
Frontmatter 20%
70
Documentation 15%
100
Issue Health 10%
80
License 10%
100
Description 5%
100

Skill Content

# Caching Strategy Advisor ## What this skill does This skill analyzes a performance bottleneck, a slow query, or an expensive operation and recommends the right caching strategy for it — which cache layer to use, what TTL to set, how to handle cache invalidation, and what to watch out for. It covers in-memory caches, Redis, HTTP caching headers, CDN caching, and database query caching, and explains the trade-offs of each recommendation. Use this when you have a slow API, a database that's under heavy read load, a page that's slow to load, or any operation that's expensive and called frequently. ## How to use ### Claude Code / Cline Copy this file to `.agents/skills/caching-strategy-advisor/SKILL.md` in your project root. Then ask: - *"Use the Caching Strategy Advisor skill — our product listing API is slow and called thousands of times per minute."* - *"We have a heavy database query that runs on every page load. Use the Caching Strategy Advisor skill to recommend a caching approach."* Provide: - What operation is slow (SQL query, API call, computation, file read) - How often it's called and by how many users - How often the underlying data changes - Your current tech stack (language, framework, existing infrastructure) - What consistency guarantees you need (is stale data for a few seconds OK?) ### Cursor Add the instructions below to your `.cursorrules` or paste them into the Cursor AI pane with the context above. ### Codex Provide the operation description and...

Details

Author
Notysoty
Repository
Notysoty/openagentskills
Created
5 months ago
Last Updated
6 days ago
Language
JavaScript
License
MIT

Integrates with

Similar Skills

Semantically similar based on skill content — not just same category