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/python/cuda_cccl/benchmarks/compute/README.md

@@ -0,0 +1,147 @@
+# cuda.compute Benchmarks
+
+Compare Python `cuda.compute` performance against C++ CUB implementations.
+
+## Setup
+
+This project uses [pixi](https://pixi.sh) to manage environments and dependencies.
+
+Two environments are available:
+
+- **`wheel`** - Uses the released `cuda-cccl` package
+- **`source`** - Builds `cuda-cccl` from the local repository
+
+### Build C++ Benchmarks
+
+Build CUB benchmarks using the CI script (one-time, ~13 minutes):
+
+```bash
+cd /path/to/cccl
+./ci/build_cub.sh -arch 89  # Use your GPU arch (89=RTX 4090, 80=A100, 90=H100)
+```
+
+Binaries are built to: `build/cub/bin/`
+
+## Run Benchmarks
+
+### Using pixi tasks
+
+```bash
+# Run Python benchmarks (released cuda-cccl)
+pixi run -e wheel bench
+
+# Run Python benchmarks (local source build)
+pixi run -e source bench
+
+# Run Python benchmarks with reduced parameter set
+pixi run -e wheel bench-quick
+
+# Run just one benchmark
+pixi run -e wheel bench -b transform/fill
+
+# Run C++ benchmarks
+pixi run -e wheel bench-cpp
+
+# Run both Python and C++ benchmarks
+pixi run -e wheel bench-all
+```
+
+### Using run_benchmarks.py directly
+
+```bash
+# Run both C++ and Python (default)
+pixi run -e wheel python run_benchmarks.py -b transform/fill -d 0
+
+# Run only C++
+pixi run -e wheel python run_benchmarks.py -b transform/fill --cpp
+
+# Run only Python
+pixi run -e wheel python run_benchmarks.py -b transform/fill --py
+
+# Show help
+pixi run -e wheel python run_benchmarks.py --help
+```
+
+To run the benchmarks using the "quick" configuration:
+
+```bash
+pixi run -e wheel python run_benchmarks.py --quick
+```
+
+## Compare Results
+
+```bash
+pixi run -e wheel python analysis/python_vs_cpp_summary.py -b transform/fill
+```
+
+## Web Report
+
+A simple page used to visualize a set of results.
+
+- Requires `results/` to be populated with benchmark results.
+
+First generate a manifest:
+
+```bash
+pixi run -e wheel python analysis/generate_web_report_manifest.py \
+  --results-dir results \
+  --output results/manifest.json
+```
+
+Build the web report single file app:
+
+```bash
+cd analysis/web-report
+npm install
+npm run build
+```
+
+This will output a single file app to `analysis/web-report/dist/` copy it to the `results/` directory and:
+
+```bash
+cd results/
+python3 -m http.server
+```
+
+Now its possible to share the results directory as a zip/tar file.
+
+## Manual Usage
+
+### List benchmark configurations
+
+```bash
+# Python
+pixi run -e wheel python transform/fill.py --list
+
+# C++
+/path/to/cccl/build/cub/bin/cub.bench.transform.fill.base --list
+```
+
+### Run with custom options
+
+```bash
+# Python - specific type and size
+pixi run -e wheel python transform/fill.py --axis "T=I32" --axis "Elements[pow2]=20" --devices 0
+
+# C++ - save JSON
+/path/to/cccl/build/cub/bin/cub.bench.transform.fill.base \
+  --json results/transform/fill_cpp.json \
+  --devices 0
+```
+
+### Compare manually
+
+```bash
+pixi run -e wheel python analysis/python_vs_cpp_summary.py \
+  results/transform/fill_py.json \
+  results/transform/fill_cpp.json \
+  --device 0
+```
+
+## AI commands
+
+These are using the .opencode folder but can be moved to other Agents.
+
+### /migration-status
+
+Generates a report of the migration status for each benchmark in CUB.