LLM Caching

by BagelHole

LLM Caching is an AI Engineering skill for Claude Code, published by BagelHole in DevOps-Security-Agent-Skills.

709 stars89 forkson BagelHole/DevOps-Security-Agent-SkillsAdded 2026/08/24+1343% in starsRepository updated 2026/05/22

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Install in seconds

Install LLM Caching

Copy LLM Caching into your Claude Code skills folder. Run the command in your terminal, or review the source on GitHub before installing.

terminal

npx degit https://github.com/BagelHole/DevOps-Security-Agent-Skills/tree/main/devops/ai/llm-caching ~/.claude/skills/llm-caching

Requires Node.js. Downloads this skill only — not the rest of the repository — into your Claude Code skills folder.

Without Node.js

git clone https://github.com/BagelHole/DevOps-Security-Agent-Skills.git

Clones the whole repository, then copy the skill’s own directory into your skills folder yourself.

In this catalog

Source file: devops/ai/llm-caching/SKILL.md in BagelHole/DevOps-Security-Agent-Skills
Installs to: ~/.claude/skills/llm-caching
Collection: One of 25 skills cataloged from this repository
Category: AI Engineering — 2451 skills

What LLM Caching does

LLM Caching implements exact-match, semantic, and provider-side prompt caching for LLM calls. Use it when repeated or similar prompts need lower API cost, faster responses, or higher throughput.

LLM Caching is cataloged under AI Engineering on DirSkills. LLM Caching comes from a repository tagged agent-skills, agentic-ai, ai-agents, aws and cheatsheets.

Documentation

README

Excerpt

LLM Caching

Cut LLM costs and latency with exact match, semantic, and provider-side caching layers.

When to Use This Skill

Use this skill when:

The same or similar queries are asked repeatedly (FAQ bots, support tools)
LLM API costs are growing and you need immediate savings
Serving high request volumes where repeated queries cause bottlenecks
Implementing prompt caching for long system prompts (Anthropic/OpenAI)
Building offline-capable AI features that need response persistence

Caching Layers

Request → Exact Cache → Semantic Cache → Provider Cache → LLM API
             ↓ hit            ↓ hit             ↓ hit
           instant          ~5ms           50-80% cheaper

Layer 1: Exact Match Cache (Redis)

This is the opening of the README. Read the full README on GitHub.

Frequently asked about LLM Caching

What else does BagelHole publish alongside LLM Caching?
LLM Caching is one of 25 skills that DirSkills catalogs from BagelHole/DevOps-Security-Agent-Skills, the repository it ships in. Its siblings there include AI Pipeline Orchestration, AI SRE Incident Response and AWS CloudTrail. Each one is a separate skill with its own page in this directory, installs the same way LLM Caching does, and is maintained by BagelHole in that same repository. The rest of the collection is listed on the BagelHole/DevOps-Security-Agent-Skills page.
How does LLM Caching compare to other AI Engineering skills?
LLM Caching ranks #1708 by stars among the 2451 AI Engineering skills in this catalog. The most-starred ones next to it are Architecture Decision Records, AI-First Engineering and Agentic OS. DirSkills ranks by the star count of the repository each skill ships in, so that order reflects how popular those repositories are rather than any review of LLM Caching against them. Open each page to compare what they document and how they install.