feat(cccl): integrate missing CCCL directories — python/, ci/, .agent/, docs/, test/

Sparse-checkout from NVIDIA/cccl main branch to complete cccl_upstream:

Added:
- python/cuda_cccl/ (226 files) — Python bindings for device-level algorithms
  Critical for muh toolchain: cuda.compute.reduce_into, scan, radix_sort, etc.
  Includes 204 .py files with full test coverage for all 27 algorithms
- ci/ (163 files) — Build/test infrastructure
  build_cub.sh, test_cub.sh, build_and_test_targets.sh, matrix.yaml
  Directly maps to our [INFRA-CI] and [INFRA-BUILD] items
- .agent/skills/ (7 files) — NVIDIA's own agent skills for CCCL
  cccl-style/SKILL.md, cccl-test/SKILL.md, sass-diff/SKILL.md
- docs/ (491 files) — Official CCCL documentation
  CI references, CMake guides, Python compute docs, libcudacxx PTX docs
- test/ (12 files) — Top-level integration tests (cuda_smoke, stdpar)
- Root configs: .clang-format, .clang-tidy, CONTRIBUTING.md, pyproject.toml
- CLAUDE.md symlink → AGENTS.md (NVIDIA's standard)

cccl_upstream now mirrors full NVIDIA/cccl structure:
  Before: 42M (cub + thrust + libcudacxx + cudax + c + examples + benchmarks)
  After:  53M (+python +ci +docs +.agent +test +configs)

This completes the CCCL base needed for:
- [muh-bench] items: ci/util/build_and_test_targets.sh for targeted builds
- [CCCL-verify] items: python/cuda_cccl/tests/ as reference implementations
- [CCCL-test] items: ci/test_cub.sh, ci/test_thrust.sh
- Agent workflow: .agent/skills/ for consistent style and test patterns

cccl_upstream/docs/libcudacxx/setup/building_and_testing.rst

@@ -0,0 +1,44 @@
+.. _libcudacxx-setup-building:
+
+Building & Testing libcu++
+==========================
+
+libcu++ can be build and tested as shown in our `contributor guidelines <https://github.com/NVIDIA/cccl/blob/main/CONTRIBUTING.md#building-and-testing>`_.
+
+However, often only a small subset of the full test suite needs to be run during development. For that we rely on ``lit``.
+After libcu++ has been configured either through the build scripts or directly via a cmake preset one can then run.
+
+.. code:: bash
+
+   cd build
+   lit libcudacxx/RELATIVE_PATH_TO_TEST_OR_SUBFOLDER -sv
+
+This will build and run all tests within ``RELATIVE_PATH_TO_TEST_OR_SUBFOLDER`` which must be a valid path within the CCCL.
+Note that the name of the top level folder is the same as the name of the preset. For the build script the default is
+``libcudacxx``. As an example this is how to run all tests for ``cuda::std::span``, which are located in
+``libcudacxx/test/libcudacxx/std/containers/views/views.span``
+
+.. code:: bash
+
+   cd build
+
+   # Builds all tests within libcudacxx/test/libcudacxx/std/containers/views/views.span
+   lit libcudacxx/libcudacxx/test/libcudacxx/std/containers/views/views.span -sv
+
+   # Builds the individual test array.pass.cpp
+   lit libcudacxx/libcudacxx/test/libcudacxx/std/containers/views/views.span/span.cons/array.pass.cpp -sv
+
+If only building the tests and not running them is desired one can pass ``-Dexecutor="NoopExecutor()"`` to the lit invocation.
+This is especially useful if the machine has no GPU or testing a different architecture
+
+.. code:: bash
+
+   cd build
+   lit libcudacxx/RELATIVE_PATH_TO_TEST_OR_SUBFOLDER -sv -Dexecutor="NoopExecutor()"
+
+Finally different standard modes can be tested by passing e.g ``--param=std=c++20``
+
+.. code:: bash
+
+   cd build
+   lit libcudacxx/RELATIVE_PATH_TO_TEST_OR_SUBFOLDER -sv --param=std=c++20

cccl_upstream/docs/libcudacxx/setup/getting.rst

@@ -0,0 +1,18 @@
+.. _libcudacxx-setup-getting:
+
+Getting libcu++
+===============
+
+NVIDIA HPC SDK or CUDA Toolkit
+------------------------------
+
+libcu++ is included in the NVIDIA HPC SDK and the CUDA Toolkit. It is on
+the default include path. Today, there is no shared library component to
+libcu++; it's all header-only. No additional compiler flags are needed.
+
+GitHub
+------
+
+libcu++ is an open source project developed on GitHub, which is where
+you'll find the latest versions and the development branch. Our GitHub
+repository is `github.com/nvidia/cccl <https://github.com/nvidia/cccl>`_.