diff --git a/.github/workflows/ci.yml b/.github/workflows/ci.yml
index 825631b..1ebc9dc 100644
--- a/.github/workflows/ci.yml
+++ b/.github/workflows/ci.yml
@@ -12,6 +12,7 @@
 jobs:
   standard:
     strategy:
+      fail-fast: false
       matrix:
         runs-on: [ubuntu-latest, windows-latest, macos-latest]
         arch: [x64]
@@ -103,6 +104,7 @@
       run: python -m pip install -r tests/requirements.txt --prefer-binary
 
     - name: Setup annotations
+      if: runner.os == 'Linux'
       run: python -m pip install pytest-github-actions-annotate-failures
 
     - name: Configure C++11 ${{ matrix.args }}
diff --git a/.pre-commit-config.yaml b/.pre-commit-config.yaml
index a046c6f..6863f4c 100644
--- a/.pre-commit-config.yaml
+++ b/.pre-commit-config.yaml
@@ -36,6 +36,14 @@
 
 - repo: local
   hooks:
+  - id: disallow-caps
+    name: Disallow improper capitalization
+    language: pygrep
+    entry: PyBind|Numpy|Cmake
+    exclude: .pre-commit-config.yaml
+
+- repo: local
+  hooks:
   - id: check-style
     name: Classic check-style
     language: system
diff --git a/docs/advanced/cast/eigen.rst b/docs/advanced/cast/eigen.rst
index 59ba08c..e01472d 100644
--- a/docs/advanced/cast/eigen.rst
+++ b/docs/advanced/cast/eigen.rst
@@ -274,7 +274,7 @@
 
 Eigen and numpy have fundamentally different notions of a vector.  In Eigen, a
 vector is simply a matrix with the number of columns or rows set to 1 at
-compile time (for a column vector or row vector, respectively).  Numpy, in
+compile time (for a column vector or row vector, respectively).  NumPy, in
 contrast, has comparable 2-dimensional 1xN and Nx1 arrays, but *also* has
 1-dimensional arrays of size N.
 
diff --git a/docs/changelog.rst b/docs/changelog.rst
index 461002e..ca025f9 100644
--- a/docs/changelog.rst
+++ b/docs/changelog.rst
@@ -628,7 +628,7 @@
   in reference cycles.
   `#856 <https://github.com/pybind/pybind11/pull/856>`_.
 
-* Numpy and buffer protocol related improvements:
+* NumPy and buffer protocol related improvements:
 
   1. Support for negative strides in Python buffer objects/numpy arrays. This
      required changing integers from unsigned to signed for the related C++ APIs.
@@ -1359,7 +1359,7 @@
 * Improved support for ``std::shared_ptr<>`` conversions
 * Initial support for ``std::set<>`` conversions
 * Fixed type resolution issue for types defined in a separate plugin module
-* Cmake build system improvements
+* CMake build system improvements
 * Factored out generic functionality to non-templated code (smaller code size)
 * Added a code size / compile time benchmark vs Boost.Python
 * Added an appveyor CI script
diff --git a/docs/faq.rst b/docs/faq.rst
index b685629..5f7866f 100644
--- a/docs/faq.rst
+++ b/docs/faq.rst
@@ -285,7 +285,7 @@
 Python detection in a system with several Python versions installed.
 
 This difference may cause inconsistencies and errors if *both* mechanisms are used in the same project. Consider the following
-Cmake code executed in a system with Python 2.7 and 3.x installed:
+CMake code executed in a system with Python 2.7 and 3.x installed:
 
 .. code-block:: cmake
 
diff --git a/docs/upgrade.rst b/docs/upgrade.rst
index 7c3f1c3..894c65f 100644
--- a/docs/upgrade.rst
+++ b/docs/upgrade.rst
@@ -32,7 +32,7 @@
   ``CMAKE_CXX_STANDARD=<number>`` instead, or any other valid CMake CXX or CUDA
   standard selection method, like ``target_compile_features``.
 
-* If you do not request a standard, PyBind11 targets will compile with the
+* If you do not request a standard, pybind11 targets will compile with the
   compiler default, but not less than C++11, instead of forcing C++14 always.
   If you depend on the old behavior, please use ``set(CMAKE_CXX_STANDARD 14)``
   instead.
diff --git a/tests/test_numpy_vectorize.cpp b/tests/test_numpy_vectorize.cpp
index a875a74..e76e462 100644
--- a/tests/test_numpy_vectorize.cpp
+++ b/tests/test_numpy_vectorize.cpp
@@ -37,7 +37,7 @@
     ));
 
     // test_type_selection
-    // Numpy function which only accepts specific data types
+    // NumPy function which only accepts specific data types
     m.def("selective_func", [](py::array_t<int, py::array::c_style>) { return "Int branch taken."; });
     m.def("selective_func", [](py::array_t<float, py::array::c_style>) { return "Float branch taken."; });
     m.def("selective_func", [](py::array_t<std::complex<float>, py::array::c_style>) { return "Complex float branch taken."; });