Cache stable prompt elements to reduce input costs in repeated AI loops.
npx skills add https://github.com/Archive228/loopkit --skill prompt-caching-archive228
Please help me install this Agent Skill. Skill: prompt-caching Source: https://github.com/Archive228/loopkit/tree/main/skills/prompt-caching Command: npx skills add https://github.com/Archive228/loopkit --skill prompt-caching-archive228
This Skill reduces the cost of long-running loops by caching stable parts of prompts, improving efficiency and cost-effectiveness.
Cache the stable parts of your prompts to improve loop performance.
High-intent search queries and answers about installing and using this skill.
Prompt caching reduces AI costs in long-running loops by storing and reusing stable prompt elements like system prompts and tool definitions, avoiding repeated processing of identical input contexts.
You should implement prompt caching for AI workflows that rely on repeated prompts with stable contexts, such as long-running loops using consistent system prompts, tool definitions, or reference documents.
To cache stable parts of a prompt and improve loop performance, identify cache breakpoints in content like system prompts and tool definitions, allowing the AI to reuse these stable elements across repeated iterations.
A limitation of using prompt caching for repeated contexts is that it is only effective when prompt elements remain stable; dynamic or frequently changing prompt components cannot be cached and will not yield cost reductions.
Prompt caching is not effective for scenarios with dynamic tool definitions, as the mechanism relies on caching stable content; changing tool definitions break the cache and prevent input cost reduction.
The best way to optimize input costs for stable system prompts is to use prompt caching, which stores the unchanged system prompt content to significantly reduce the input costs of repeated contexts in long-running loops.
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