[FEATURE]:Clarify in the model doc whether sub-configurations for `variants` use camelCase or snake_case

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Describe the enhancement you want to request

• Clarify in the model doc whether sub-configurations for variants use camelCase or snake_case
• From my perspective, the explanation of the sub-configurations of variants at https://opencode.ai/docs/models/ is somewhat confusing.

        "gpt-5": {
          "variants": {
            "high": {
              "reasoningEffort": "high",
              "textVerbosity": "low",
              "reasoningSummary": "auto",
            },
            "low": {
              "reasoningEffort": "low",
              "textVerbosity": "low",
              "reasoningSummary": "auto",
            },
          },
        }

• When I check https://learn.microsoft.com/en-us/azure/foundry/openai/how-to/reasoning?tabs=REST%2Cgpt-5#reasoning-effort and https://developers.openai.com/api/docs/guides/latest-model?model=gpt-5#gpt-5-prompting-for-less-eagerness , I don't see reasoningEffort; I only see reasoning_effort.

curl -X POST "https://YOUR-RESOURCE-NAME.openai.azure.com/openai/v1/chat/completions" \
  -H "Content-Type: application/json" \
  -H "Authorization: Bearer $AZURE_OPENAI_AUTH_TOKEN" \
  -d '{
      "model": "gpt-5",
      "messages": [
        {"role": "developer", "content": "You are a helpful assistant."},
          {"role": "user", "content": "What steps should I think about when writing my first Python API?"}
      ],
      "max_completion_tokens": 1000,
      "reasoning_effort": "medium"
  }'

Switch to a lower reasoning_effort. This reduces exploration depth but improves efficiency and latency. Many workflows can be accomplished with consistent results at medium or even low reasoning_effort.

• If the actual behavior of OpenCode is that snake_case (like reasoning_effort) is invalid and only camelCase (like reasoningEffort) is supported, then I believe the documentation at https://opencode.ai/docs/models/ clearly requires further clarification.