Individual skill

openrouter-caching-strategy

Implement caching for OpenRouter API responses to reduce cost and latency. Use when optimizing repeat queries, building RAG systems, or reducing API spend. Triggers: 'openrouter cache', 'cache llm responses', 'openrouter caching', 'reduce openrouter cost'.

skills/.curated/openrouter-caching-strategy/SKILL.md

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# OpenRouter Caching Strategy

## Overview

OpenRouter charges per token, so caching identical or similar requests can dramatically cut costs. Deterministic requests (`temperature=0`) with the same model and messages produce identical outputs -- these are safe to cache. This skill covers in-memory caching, persistent caching with TTL, and Anthropic prompt caching via OpenRouter.

## Prerequisites

- An OpenRouter API key (`sk-or-v1-...`) exported as `OPENROUTER_API_KEY` — see the `openrouter-install-auth` skill for setup
- Python 3.8+ with the OpenAI SDK, plus the `redis` client package for the persistent cache; Node.js 18+ with the OpenAI SDK for the TypeScript variant in the references
- A Redis server reachable at `localhost:6379` for Persistent Cache with Redis (the in-memory `LLMCache` needs no infrastructure)
- Deterministic request settings — caching is only safe at `temperature=0`

## Instructions
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