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/cub/block_wide.rst

@@ -0,0 +1,26 @@
+.. _block-module:
+
+Block-Wide "Collective" Primitives
+==================================================
+
+.. toctree::
+   :glob:
+   :hidden:
+   :maxdepth: 2
+
+   api/block
+
+CUB block-level algorithms are specialized for execution by threads in the same CUDA thread block:
+
+* :cpp:class:`cub::BlockAdjacentDifference` computes the difference between adjacent items partitioned across a CUDA thread block
+* :cpp:class:`cub::BlockDiscontinuity` flags discontinuities within an ordered set of items partitioned across a CUDA thread block
+* :cpp:struct:`cub::BlockExchange` rearranges data partitioned across a CUDA thread block
+* :cpp:class:`cub::BlockHistogram` constructs block-wide histograms from data samples partitioned across a CUDA thread block
+* :cpp:class:`cub::BlockLoad` loads a linear segment of items from memory into a CUDA thread block
+* :cpp:class:`cub::BlockMergeSort` sorts items partitioned across a CUDA thread block
+* :cpp:class:`cub::BlockRadixSort` sorts items partitioned across a CUDA thread block using radix sorting method
+* :cpp:struct:`cub::BlockReduce` computes reduction of items partitioned across a CUDA thread block
+* :cpp:class:`cub::BlockRunLengthDecode` decodes a run-length encoded sequence partitioned across a CUDA thread block
+* :cpp:struct:`cub::BlockScan` computes a prefix scan of items partitioned across a CUDA thread block
+* :cpp:struct:`cub::BlockShuffle` shifts items partitioned across a CUDA thread block
+* :cpp:class:`cub::BlockStore` stores items partitioned across a CUDA thread block to a linear segment of memory