docs: replace model experience tables with sections

packages/llm/llm-deepseek/README.md

@@ -44,10 +44,17 @@ Unit suites run against a local `node:http` mock SSE server (no network). Real-A
 
 ## Model Experience
 
-| Context surface | What the model sees | Token effect |
-|---|---|---|
-| DeepSeek request | The selected DeepSeek model receives the harness system prompt, message history, tool schemas, stop sequences, and call config without adapter-authored prompt prose. On a prior assistant turn with tool calls, its reasoning content is passed back as required; reasoning from tool-call-free turns is omitted. | 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. |
-| DeepSeek response | Reasoning, text, and raw-string tool arguments are translated into harness chunks for the loop to log and assemble. | Generated tokens follow provider thinking and effort settings plus the request's `maxTokens`; only loop-retained blocks affect later input. |
+### DeepSeek request
+
+**What the model sees**: The selected DeepSeek model receives the harness system prompt, message history, tool schemas, stop sequences, and call config without adapter-authored prompt prose. On a prior assistant turn with tool calls, its reasoning content is passed back as required; reasoning from tool-call-free turns is omitted.
+
+**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.
+
+### 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.
 
 ## Known Limitations and Deferred Work
 

packages/llm/llm-pi-ai/README.md

@@ -39,10 +39,17 @@ Unit suites run against a local `node:http` mock SSE server (pi-ai's openai SDK
 
 ## Model Experience
 
-| Context surface | What the model sees | Token effect |
-|---|---|---|
-| DeepSeek request through pi-ai | The selected model receives the same logical system prompt, history, tools, stop sequences, and raw replayed tool arguments as the hand-written adapter. This package adds no prompt prose and removes pi-ai's own per-tool `strict` default to preserve that contract. | Provider tokenization governs exact input. Reasoning level changes generated and passback content; pi-ai reports reasoning inside output usage rather than as a separate count. |
-| DeepSeek response | pi-ai events become harness reasoning, text, tool-call, usage, and finish chunks; parsed tool arguments are restored to raw JSON strings at the harness boundary. | Generated content affects later inputs only after the loop records it; adapter conversion adds no model-visible text. |
+### DeepSeek request through pi-ai
+
+**What the model sees**: The selected model receives the same logical system prompt, history, tools, stop sequences, and raw replayed tool arguments as the hand-written adapter. This package adds no prompt prose and removes pi-ai's own per-tool `strict` default to preserve that contract.
+
+**Token effect**: Provider tokenization governs exact input. Reasoning level changes generated and passback content; pi-ai reports reasoning inside output usage rather than as a separate count.
+
+### DeepSeek response
+
+**What the model sees**: pi-ai events become harness reasoning, text, tool-call, usage, and finish chunks; parsed tool arguments are restored to raw JSON strings at the harness boundary.
+
+**Token effect**: Generated content affects later inputs only after the loop records it; adapter conversion adds no model-visible text.
 
 ## Known Limitations and Deferred Work
 

packages/llm/llm/README.md

@@ -50,10 +50,17 @@ Two adapters implement `LlmAdapter` against this vocabulary, deliberately built
 
 ## Model Experience
 
-| Context surface | What the model sees | Token effect |
-|---|---|---|
-| Provider request transport | This service adds no system text, schema, or message. It routes the already-assembled frozen `GenerateOptions` to one adapter, while `llm/stream` listeners may cache, retry, or replace the stream without mutating that request. | Zero direct context tokens. The selected adapter and provider tokenizer determine billing, cache accounting, and serialization overhead for the existing content. |
-| Streamed model output | Text, reasoning, and tool-call chunks are exposed to the loop, which decides what becomes retained assistant history. | Output usage is provider-reported; later input cost arises only after the loop records assembled content. |
+### Provider request transport
+
+**What the model sees**: This service adds no system text, schema, or message. It routes the already-assembled frozen `GenerateOptions` to one adapter, while `llm/stream` listeners may cache, retry, or replace the stream without mutating that request.
+
+**Token effect**: Zero direct context tokens. The selected adapter and provider tokenizer determine billing, cache accounting, and serialization overhead for the existing content.
+
+### Streamed model output
+
+**What the model sees**: Text, reasoning, and tool-call chunks are exposed to the loop, which decides what becomes retained assistant history.
+
+**Token effect**: Output usage is provider-reported; later input cost arises only after the loop records assembled content.
 
 ## Known Limitations and Deferred Work