docs: document package KV cache effects

packages/llm/llm-deepseek/README.md

@@ -56,12 +56,16 @@ Unit suites run against a local `node:http` mock SSE server (no network). Real-A
 
 **Token effect**: Provider tokenization governs exact input. Conditional reasoning passback increases tool-round-trip context, while dropping other reasoning avoids paying those tokens again; cache-read usage is reported when available.
 
+**KV Cache effect**: An unchanged assembled prefix is eligible for DeepSeek cache reuse, which this adapter reports in usage. A model-route change or any upstream prompt, schema, prefix, or history change may prevent reuse from the first changed token; reasoning passback appends during tool round trips.
+
 ### DeepSeek response
 
 **What the model sees**: Reasoning, text, and raw-string tool arguments are translated into harness chunks for the loop to log and assemble.
 
 **Token effect**: Generated tokens follow provider thinking and effort settings plus the request's `maxTokens`; only loop-retained blocks affect later input.
 
+**KV Cache effect**: Loop-retained response blocks append to the next request and preserve its earlier reusable prefix; dropped blocks have no later cache effect. Changing the provider or model selects a different cache domain.
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 ## Known Limitations and Deferred Work
 
 - **`tool_choice` is not mapped** — not part of the core vocabulary (MVP cut, shared with the pi-ai twin).