feat(llm): a request carries how much the model thinks, in each provider's field

LlmRequest.effort (LlmEffort: low, medium, high, xhigh, max, Anthropic's
names) goes as Anthropic's output_config.effort, as reasoning.effort to
the Responses API and OpenRouter, and as reasoning_effort to OpenAI's chat
completions, Gemini and any other host. endpoint.efforts says which
levels a host takes (Gemini low to high, Mistral none); send refuses
another before anything goes, the fake client too. LlmEffort.outputCeiling
gives the room for output each level wants, as thinking counts towards
the ceiling (Halkyon Learn's ADR 0021, D63).

Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
Signed-off-by: Tizian 「ティツィアーン」 <raisondetredev@pm.me>

packages/halkyon_llm/README.md

@@ -73,6 +73,15 @@ the local network, which may be shared.
   phase in `LlmText.extra`. Send the `LlmFinished.message` back unchanged.
 - **The person's opaque ID** (`LlmRequest.personId`) goes where the provider takes one:
   Anthropic's `metadata.user_id`, OpenAI's `safety_identifier`, OpenRouter's `user`.
+- **The effort** (`LlmRequest.effort`, `LlmEffort`: `low`, `medium`, `high`, `xhigh`,
+  `max`, Anthropic's names; null leaves it to the model) goes as Anthropic's
+  `output_config.effort`, the Responses API's and OpenRouter's `reasoning.effort`, and
+  `reasoning_effort` to OpenAI's chat completions, Gemini and any other host.
+  `endpoint.efforts` says which levels a host takes: Gemini's low to high, Mistral's
+  none, every one elsewhere; `send` throws an `ArgumentError` for another. Which levels a
+  model has is the model's, and its provider refuses one it lacks. The model's thinking
+  counts towards `maxOutputTokens`, so a higher effort wants a higher ceiling:
+  `LlmEffort.outputCeiling` (8,192 at low to 65,536 at max; 16,384 without an effort).
 
 ## Testing with it