> ## Documentation Index
> Fetch the complete documentation index at: https://docs.caveman.so/llms.txt
> Use this file to discover all available pages before exploring further.

# Prompt Cache Planner for Provider-Native Controls

> Caveman's cache planner adds provider-native prompt-cache controls where economics and request shape support them. Learn how it inspects requests, identifies stable prefix boundaries, and adds cache hints safely.

Caveman's cache planner adds provider-native prompt-cache controls where economics and request shape support them. It never caches model responses.

Cache planner inspects a request, identifies stable prefix boundaries, and adds provider-native cache hints. Planning and request optimization make no network calls.

Built-in planners cover Anthropic, OpenAI, Amazon Bedrock, and Google Gemini. Unknown providers pass through unchanged.

## Fail-safe cases

Planner keeps the original request when it sees any of the following:

* Record mode
* Unsupported billing tier
* Malformed or ambiguous JSON
* Duplicate JSON keys
* Unsupported provider behavior
* Volatile content at a candidate boundary
* Provider semantics that have drifted from registered capability data

Provider-specific parsers own exact request shape. Generic planning uses expected call count and provider rate units. It does not invent dollar savings when provider pricing evidence is absent.

## Provider observations

A cache hint does not prove a cache hit; provider response usage determines whether a cache read or write occurred. Local planning records remain inferred, and provider observations retain their own evidence basis.

## Benchmark boundary

Repository cache corpus tests measure safety gates and planner behavior. They do not establish a universal provider savings rate or market ranking. Provider features and prices change; recheck capability data and public documentation before publishing current claims.


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