The primary model path is the provider-neutral maka_computer function tool through AiSdkBackend. The model observes an Accessibility tree, then uses click_element, set_value, or another semantic action with IDs from that observation.
This matches the recovered Codex layering:
model function/tool call -> Computer Use facade -> observed AX element identity -> stale-element refetch and uniqueness checks -> element executor -> AXPick / AXPress / AXValue when supported -> synthetic event fallback only inside the native executor
Codex does not currently expose a top-level native computer tool in the captured production request. Its deferred Computer Use wrapper exposes the AX facade. Accessibility-first dispatch happens inside element execution, not by implicitly turning every model coordinate into an AX element.
Maka keeps the same separation:
maka_computer is the primary model-facing path;computer_call loop is an observation-only experimental path by default;No provider adapter may infer a missing observation ID or silently bind an action to the current frame.
The local Azure Responses bridge at 127.0.0.1:8538 and coproxy Anthropic endpoint at 127.0.0.1:8537 were used without persisting credentials or raw provider responses.
gpt-5.6-sol completed:
list_apps -> observe -> set_value -> verified finish
The standalone provider loop completed in four to five turns. The full product path also passed:
getAIModel -> OpenAI Responses model -> AiSdkBackend / streamText -> ToolRuntime -> maka_computer -> synthetic AX semantic backend
The product path persisted tool calls and results, emitted permission-safe telemetry, and reached the verified final value.
The same deployment accepted the GA native computer tool. Under observation-only instructions it returned only screenshot, and the bounded transport/codec loop completed the screenshot continuation in two turns.
claude-sonnet-4-6 completed the same semantic task through coproxy.
One run omitted observation_id from set_value. The harness returned a typed tool error requiring another observation; the model recovered instead of the executor guessing a frame. This behavior is a required regression scenario for future provider adapters.
No live Kimi or MiniMax credential is configured on this machine. Their product paths are covered as hermetic protocol evidence, not real-provider evidence.
Both kimi-coding-plan and minimax-coding-plan complete the same multi-step semantic loop through their exact Anthropic-compatible URL/auth contracts:
getAIModel -> streaming tool_use -> AiSdkBackend -> ToolRuntime -> maka_computer -> list_apps -> observe -> set_value -> final response
OpenAI strict function schemas require every property to be listed in required. Optional fields must be represented as nullable. Because one function schema serves several action variants, the model can populate known fields that are irrelevant to the selected action.
The OpenAI adapter therefore:
The core maka_computer parser remains strict and provider neutral.
This foundation does not: