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miskeyed-xr-agent

miskeyed-xr-agent is a small C++20 investigation into turning human XR input into deterministic, host-neutral spatial intent. OpenXR is an input backend, not the public data model. The project deliberately contains no renderer, scene graph, USD/Workbench/Kit dependency, network service, speech recognizer, computer vision system, or AI model.

Milestone 1

The first milestone provides:

  • host-neutral poses, rays, semantic pointing, capability snapshots, and intent frames;
  • a Khronos OpenXR 1.1 loader probe that enumerates runtime capabilities and creates select, aim_pose, and grip_pose semantic actions;
  • a host-owned-session OpenXR sampler that synchronizes semantic aim actions and locates head/aim poses at one XrTime;
  • a versioned JSONL recording draft and hardware-free tests; and
  • a bounded timeline that turns sparse final text into one spatially grounded event instead of repeating text on realtime frames; and
  • a documented boundary between portable XR input and host-owned scene queries.

If you are building miskeyed-xr-agent-usd or an Omniverse Kit extension, start with the concrete host integration pass. The included spatial-host-example proves the consumer path without OpenXR or headset hardware: intent ray in, host raycast, grounded intent out.

Python and agent-framework consumers can install the pybind11 package with python -m pip install miskeyed-xr-agent and import it as miskeyed.xr.agent. See the Python agent workflow for the intended USD-agent handoff and the reason an agent receives a plain, already-grounded dictionary instead of raw OpenXR objects.

Native embedders should read the OpenXR implementation contract. The separate Omniverse test app must reuse Kit's OpenXR lifecycle rather than create a competing XR session; no Kit extension code is shipped from this core. The CI/release contract describes the hardware-free gate and version-first, multi-platform TestPyPI/PyPI deployment. The realtime digital-twin vision explains how XR feedback, sparse language, live twin telemetry, simulation, and reviewed scene changes fit together—and lists what remains unimplemented. The milestone exit contract is the handoff checklist for the separate Omniverse application. The Kit app learning path provides a staged, version-conscious plan for that repository without adding Kit SDK ownership or dependencies here.

Normalized recordings are available after installation:

xr-agent-record session.jsonl < normalized-stream.jsonl
xr-agent-replay session.jsonl --speed 1

The command-line probe does not invent a headless session. A normal OpenXR session needs a platform graphics binding. The probe performs discovery without one, and reports that an embedding graphics host is required before live action synchronization and xrLocateViews/xrLocateSpace sampling. This keeps the prototype truthful and renderer-neutral.

Build

cmake -S . -B build
cmake --build build
ctest --test-dir build --output-on-failure
./build/xr-agent-probe

CMake first looks for an installed OpenXR::openxr_loader. By default it otherwise fetches the pinned official Khronos SDK source release. Use -DMISKEYED_XR_BUILD_OPENXR=OFF -DMISKEYED_XR_FETCH_OPENXR=OFF for a completely offline, core-only build.

Current answer

OpenXR 1.1 is a good portable runtime, tracking, and semantic action foundation. Head/view poses, reference spaces, action sets, pose actions, and extension discovery are core. Hand joints, hand-interaction bindings, and eye gaze are optional extensions and must remain optional. Scene meshes, depth, raycasts, passthrough/camera pixels, durable anchors, text, and voice are not one uniform core capability; the host or explicit adapters own those areas. See the capability matrix and architecture decisions.

Privacy

Eye gaze is opt-in. Capability detection is not consent, and raw gaze history must not be recorded by default.

Licensed under the MIT License.

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