diff --git a/lib/node_modules/@stdlib/ndarray/every/test/test.assign.js b/lib/node_modules/@stdlib/ndarray/every/test/test.assign.js
new file mode 100644
index 000000000000..9b448db0720d
--- /dev/null
+++ b/lib/node_modules/@stdlib/ndarray/every/test/test.assign.js
@@ -0,0 +1,382 @@
+/**
+* @license Apache-2.0
+*
+* Copyright (c) 2025 The Stdlib Authors.
+*
+* Licensed under the Apache License, Version 2.0 (the "License");
+* you may not use this file except in compliance with the License.
+* You may obtain a copy of the License at
+*
+*    http://www.apache.org/licenses/LICENSE-2.0
+*
+* Unless required by applicable law or agreed to in writing, software
+* distributed under the License is distributed on an "AS IS" BASIS,
+* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+* See the License for the specific language governing permissions and
+* limitations under the License.
+*/
+
+'use strict';
+
+// MODULES //
+
+var tape = require( 'tape' );
+var Float64Array = require( '@stdlib/array/float64' );
+var ndarray = require( '@stdlib/ndarray/ctor' );
+var empty = require( '@stdlib/ndarray/empty' );
+var ndarray2array = require( '@stdlib/ndarray/to-array' );
+var assign = require( './../lib/assign.js' );
+
+
+// TESTS //
+
+tape( 'main export is a function', function test( t ) {
+	t.ok( true, __filename );
+	t.strictEqual( typeof assign, 'function', 'main export is a function' );
+	t.end();
+});
+
+tape( 'the function throws an error if provided a first argument which is not an ndarray-like object', function test( t ) {
+	var values;
+	var y;
+	var i;
+
+	y = empty( [], {
+		'dtype': 'bool'
+	});
+
+	values = [
+		'5',
+		5,
+		NaN,
+		true,
+		false,
+		null,
+		void 0,
+		{},
+		[],
+		function noop() {}
+	];
+
+	for ( i = 0; i < values.length; i++ ) {
+		t.throws( badValue( values[ i ] ), TypeError, 'throws an error when provided ' + values[ i ] );
+	}
+	t.end();
+
+	function badValue( value ) {
+		return function badValue() {
+			assign( value, y );
+		};
+	}
+});
+
+tape( 'the function throws an error if provided a first argument which is not an ndarray-like object (options)', function test( t ) {
+	var values;
+	var y;
+	var i;
+
+	y = empty( [], {
+		'dtype': 'bool'
+	});
+
+	values = [
+		'5',
+		5,
+		NaN,
+		true,
+		false,
+		null,
+		void 0,
+		{},
+		[],
+		function noop() {}
+	];
+
+	for ( i = 0; i < values.length; i++ ) {
+		t.throws( badValue( values[ i ] ), TypeError, 'throws an error when provided ' + values[ i ] );
+	}
+	t.end();
+
+	function badValue( value ) {
+		return function badValue() {
+			assign( value, y, {} );
+		};
+	}
+});
+
+tape( 'the function throws an error if provided a second argument which is not an ndarray-like object', function test( t ) {
+	var values;
+	var x;
+	var i;
+
+	x = empty( [ 2, 2 ], {
+		'dtype': 'float64'
+	});
+
+	values = [
+		'5',
+		5,
+		NaN,
+		true,
+		false,
+		null,
+		void 0,
+		{},
+		[],
+		function noop() {}
+	];
+
+	for ( i = 0; i < values.length; i++ ) {
+		t.throws( badValue( values[ i ] ), TypeError, 'throws an error when provided ' + values[ i ] );
+	}
+	t.end();
+
+	function badValue( value ) {
+		return function badValue() {
+			assign( x, value );
+		};
+	}
+});
+
+tape( 'the function throws an error if provided a second argument which is not an ndarray-like object (options)', function test( t ) {
+	var values;
+	var x;
+	var i;
+
+	x = empty( [ 2, 2 ], {
+		'dtype': 'float64'
+	});
+
+	values = [
+		'5',
+		5,
+		NaN,
+		true,
+		false,
+		null,
+		void 0,
+		{},
+		[],
+		function noop() {}
+	];
+
+	for ( i = 0; i < values.length; i++ ) {
+		t.throws( badValue( values[ i ] ), TypeError, 'throws an error when provided ' + values[ i ] );
+	}
+	t.end();
+
+	function badValue( value ) {
+		return function badValue() {
+			assign( x, value, {} );
+		};
+	}
+});
+
+tape( 'the function throws an error if provided an options argument which is not an object', function test( t ) {
+	var values;
+	var x;
+	var y;
+	var i;
+
+	x = empty( [ 2, 2 ], {
+		'dtype': 'float64'
+	});
+	y = empty( [ 2 ], {
+		'dtype': 'bool'
+	});
+
+	values = [
+		'5',
+		5,
+		NaN,
+		true,
+		false,
+		null,
+		void 0,
+		[],
+		function noop() {}
+	];
+
+	for ( i = 0; i < values.length; i++ ) {
+		t.throws( badValue( values[ i ] ), TypeError, 'throws an error when provided ' + values[ i ] );
+	}
+	t.end();
+
+	function badValue( value ) {
+		return function badValue() {
+			assign( x, y, value );
+		};
+	}
+});
+
+tape( 'the function throws an error if provided an options argument with an invalid `dims` property', function test( t ) {
+	var values;
+	var x;
+	var y;
+	var i;
+
+	x = empty( [ 2, 2 ], {
+		'dtype': 'float64'
+	});
+	y = empty( [ 2 ], {
+		'dtype': 'bool'
+	});
+
+	values = [
+		'5',
+		NaN,
+		true,
+		false,
+		null,
+		void 0,
+		{}
+	];
+
+	for ( i = 0; i < values.length; i++ ) {
+		t.throws( badValue( values[ i ] ), TypeError, 'throws an error when provided ' + values[ i ] );
+	}
+	t.end();
+
+	function badValue( value ) {
+		return function badValue() {
+			var opts = {
+				'dims': value
+			};
+			assign( x, y, opts );
+		};
+	}
+});
+
+tape( 'the function tests whether every element along one or more ndarray dimensions is truthy (row-major)', function test( t ) {
+	var expected;
+	var actual;
+	var x;
+	var y;
+
+	x = new ndarray( 'float64', new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] ), [ 4 ], [ 1 ], 0, 'row-major' );
+	y = empty( [], {
+		'dtype': 'bool'
+	});
+
+	actual = assign( x, y );
+	expected = true;
+
+	t.strictEqual( actual, y, 'returns expected value' );
+	t.strictEqual( actual.get(), expected, 'returns expected value' );
+
+	x = new ndarray( 'float64', new Float64Array( [ 1.0, 0.0, 3.0, 0.0 ] ), [ 4 ], [ 1 ], 0, 'row-major' );
+	y = empty( [], {
+		'dtype': 'bool'
+	});
+
+	actual = assign( x, y );
+	expected = false;
+
+	t.strictEqual( actual, y, 'returns expected value' );
+	t.strictEqual( actual.get(), expected, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function tests whether every element along one or more ndarray dimensions is truthy (column-major)', function test( t ) {
+	var expected;
+	var actual;
+	var x;
+	var y;
+
+	x = new ndarray( 'float64', new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] ), [ 4 ], [ 1 ], 0, 'column-major' );
+	y = empty( [], {
+		'dtype': 'bool'
+	});
+
+	actual = assign( x, y );
+	expected = true;
+
+	t.strictEqual( actual, y, 'returns expected value' );
+	t.strictEqual( actual.get(), expected, 'returns expected value' );
+
+	x = new ndarray( 'float64', new Float64Array( [ 1.0, 0.0, 3.0, 0.0 ] ), [ 4 ], [ 1 ], 0, 'column-major' );
+	y = empty( [], {
+		'dtype': 'bool'
+	});
+
+	actual = assign( x, y );
+	expected = false;
+
+	t.strictEqual( actual, y, 'returns expected value' );
+	t.strictEqual( actual.get(), expected, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function supports specifying reduction dimensions (row-major)', function test( t ) {
+	var expected;
+	var actual;
+	var opts;
+	var x;
+	var y;
+
+	x = new ndarray( 'float64', new Float64Array( [ 1.0, 2.0, 3.0, 4.0, -5.0, 6.0, -7.0, 8.0 ] ), [ 2, 4 ], [ 4, 1 ], 0, 'row-major' );
+
+	opts = {
+		'dims': [ 0 ]
+	};
+	y = empty( [ 4 ], {
+		'dtype': 'bool'
+	});
+	actual = assign( x, y, opts );
+	expected = [ true, true, true, true ];
+	t.strictEqual( actual, y, 'returns expected value' );
+	t.deepEqual( ndarray2array( actual ), expected, 'returns expected value' );
+
+	x = new ndarray( 'float64', new Float64Array( [ 1.0, 0.0, 3.0, 0.0, -5.0, 0.0, -7.0, 0.0 ] ), [ 2, 4 ], [ 4, 1 ], 0, 'row-major' );
+
+	opts = {
+		'dims': [ 0 ]
+	};
+	y = empty( [ 4 ], {
+		'dtype': 'bool'
+	});
+	actual = assign( x, y, opts );
+	expected = [ true, false, true, false ];
+	t.strictEqual( actual, y, 'returns expected value' );
+	t.deepEqual( ndarray2array( actual ), expected, 'returns expected value' );
+	t.end();
+});
+
+tape( 'the function supports specifying reduction dimensions (column-major)', function test( t ) {
+	var expected;
+	var actual;
+	var opts;
+	var x;
+	var y;
+
+	x = new ndarray( 'float64', new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ] ), [ 2, 4 ], [ 1, 2 ], 0, 'column-major' );
+
+	opts = {
+		'dims': [ 1 ]
+	};
+	y = empty( [ 2 ], {
+		'dtype': 'bool'
+	});
+	actual = assign( x, y, opts );
+	expected = [ true, true ];
+
+	t.strictEqual( actual, y, 'returns expected value' );
+	t.deepEqual( ndarray2array( actual ), expected, 'returns expected value' );
+
+	x = new ndarray( 'float64', new Float64Array( [ 1.0, 0.0, 3.0, 0.0, 5.0, 0.0, 7.0, 0.0 ] ), [ 2, 4 ], [ 1, 2 ], 0, 'column-major' );
+
+	opts = {
+		'dims': [ 1 ]
+	};
+	y = empty( [ 2 ], {
+		'dtype': 'bool'
+	});
+	actual = assign( x, y, opts );
+	expected = [ true, false ];
+
+	t.strictEqual( actual, y, 'returns expected value' );
+	t.deepEqual( ndarray2array( actual ), expected, 'returns expected value' );
+	t.end();
+});
diff --git a/lib/node_modules/@stdlib/ndarray/every/test/test.main.js b/lib/node_modules/@stdlib/ndarray/every/test/test.main.js
new file mode 100644
index 000000000000..ca247c62a068
--- /dev/null
+++ b/lib/node_modules/@stdlib/ndarray/every/test/test.main.js
@@ -0,0 +1,421 @@
+/**
+* @license Apache-2.0
+*
+* Copyright (c) 2025 The Stdlib Authors.
+*
+* Licensed under the Apache License, Version 2.0 (the "License");
+* you may not use this file except in compliance with the License.
+* You may obtain a copy of the License at
+*
+*    http://www.apache.org/licenses/LICENSE-2.0
+*
+* Unless required by applicable law or agreed to in writing, software
+* distributed under the License is distributed on an "AS IS" BASIS,
+* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+* See the License for the specific language governing permissions and
+* limitations under the License.
+*/
+
+'use strict';
+
+// MODULES //
+
+var tape = require( 'tape' );
+var Float64Array = require( '@stdlib/array/float64' );
+var ndarray = require( '@stdlib/ndarray/ctor' );
+var empty = require( '@stdlib/ndarray/empty' );
+var ndarray2array = require( '@stdlib/ndarray/to-array' );
+var every = require( './../lib' );
+
+
+// TESTS //
+
+tape( 'main export is a function', function test( t ) {
+	t.ok( true, __filename );
+	t.strictEqual( typeof every, 'function', 'main export is a function' );
+	t.end();
+});
+
+tape( 'the function throws an error if provided a first argument which is not an ndarray-like object', function test( t ) {
+	var values;
+	var i;
+
+	values = [
+		'5',
+		5,
+		NaN,
+		true,
+		false,
+		null,
+		void 0,
+		{},
+		[],
+		function noop() {}
+	];
+
+	for ( i = 0; i < values.length; i++ ) {
+		t.throws( badValue( values[ i ] ), TypeError, 'throws an error when provided ' + values[ i ] );
+	}
+	t.end();
+
+	function badValue( value ) {
+		return function badValue() {
+			every( value );
+		};
+	}
+});
+
+tape( 'the function throws an error if provided a first argument which is not an ndarray-like object (options)', function test( t ) {
+	var values;
+	var i;
+
+	values = [
+		'5',
+		5,
+		NaN,
+		true,
+		false,
+		null,
+		void 0,
+		{},
+		[],
+		function noop() {}
+	];
+
+	for ( i = 0; i < values.length; i++ ) {
+		t.throws( badValue( values[ i ] ), TypeError, 'throws an error when provided ' + values[ i ] );
+	}
+	t.end();
+
+	function badValue( value ) {
+		return function badValue() {
+			every( value, {} );
+		};
+	}
+});
+
+tape( 'the function throws an error if provided an options argument which is not an object', function test( t ) {
+	var values;
+	var x;
+	var i;
+
+	x = empty( [ 2, 2 ], {
+		'dtype': 'float64'
+	});
+
+	values = [
+		'5',
+		5,
+		NaN,
+		true,
+		false,
+		null,
+		void 0,
+		[],
+		function noop() {}
+	];
+
+	for ( i = 0; i < values.length; i++ ) {
+		t.throws( badValue( values[ i ] ), TypeError, 'throws an error when provided ' + values[ i ] );
+	}
+	t.end();
+
+	function badValue( value ) {
+		return function badValue() {
+			every( x, value );
+		};
+	}
+});
+
+tape( 'the function throws an error if provided an options argument with an invalid `dims` property', function test( t ) {
+	var values;
+	var x;
+	var i;
+
+	x = empty( [ 2, 2 ], {
+		'dtype': 'float64'
+	});
+
+	values = [
+		'5',
+		NaN,
+		true,
+		false,
+		null,
+		void 0,
+		{},
+		function noop() {}
+	];
+
+	for ( i = 0; i < values.length; i++ ) {
+		t.throws( badValue( values[ i ] ), TypeError, 'throws an error when provided ' + values[ i ] );
+	}
+	t.end();
+
+	function badValue( value ) {
+		return function badValue() {
+			var opts = {
+				'dims': value
+			};
+			every( x, opts );
+		};
+	}
+});
+
+tape( 'the function throws an error if provided an options argument with a `dims` property which contains out-of-bounds dimensions', function test( t ) {
+	var values;
+	var x;
+	var i;
+
+	x = empty( [ 2, 2 ], {
+		'dtype': 'float64'
+	});
+
+	values = [
+		[ 1, 3 ],
+		[ 3, 0 ],
+		[ 0, 2 ]
+	];
+
+	for ( i = 0; i < values.length; i++ ) {
+		t.throws( badValue( values[ i ] ), RangeError, 'throws an error when provided ' + values[ i ] );
+	}
+	t.end();
+
+	function badValue( value ) {
+		return function badValue() {
+			var opts = {
+				'dims': value
+			};
+			every( x, opts );
+		};
+	}
+});
+
+tape( 'the function throws an error if provided an options argument with a `dims` property which contains duplicate dimensions', function test( t ) {
+	var values;
+	var x;
+	var i;
+
+	x = empty( [ 2, 2 ], {
+		'dtype': 'float64'
+	});
+
+	values = [
+		[ 0, 0 ],
+		[ 1, 1 ]
+	];
+
+	for ( i = 0; i < values.length; i++ ) {
+		t.throws( badValue( values[ i ] ), Error, 'throws an error when provided ' + values[ i ] );
+	}
+	t.end();
+
+	function badValue( value ) {
+		return function badValue() {
+			var opts = {
+				'dims': value
+			};
+			every( x, opts );
+		};
+	}
+});
+
+tape( 'the function throws an error if provided an options argument with a `dims` property which contains more dimensions than are present in the input ndarray', function test( t ) {
+	var values;
+	var x;
+	var i;
+
+	x = empty( [ 2, 2 ], {
+		'dtype': 'float64'
+	});
+
+	values = [
+		[ 0, 1, 2 ],
+		[ 0, 1, 2, 3 ],
+		[ 0, 1, 2, 3, 4 ]
+	];
+
+	for ( i = 0; i < values.length; i++ ) {
+		t.throws( badValue( values[ i ] ), RangeError, 'throws an error when provided ' + values[ i ] );
+	}
+	t.end();
+
+	function badValue( value ) {
+		return function badValue() {
+			var opts = {
+				'dims': value
+			};
+			every( x, opts );
+		};
+	}
+});
+
+tape( 'the function throws an error if provided an options argument with an invalid `keepdims` property', function test( t ) {
+	var values;
+	var x;
+	var i;
+
+	x = empty( [ 2, 2 ], {
+		'dtype': 'float64'
+	});
+
+	values = [
+		'5',
+		5,
+		NaN,
+		null,
+		void 0,
+		{},
+		[],
+		function noop() {}
+	];
+
+	for ( i = 0; i < values.length; i++ ) {
+		t.throws( badValue( values[ i ] ), TypeError, 'throws an error when provided ' + values[ i ] );
+	}
+	t.end();
+
+	function badValue( value ) {
+		return function badValue() {
+			var opts = {
+				'keepdims': value
+			};
+			every( x, opts );
+		};
+	}
+});
+
+tape( 'the function tests whether every element along one or more ndarray dimensions is truthy (row-major)', function test( t ) {
+	var expected;
+	var actual;
+	var x;
+
+	x = new ndarray( 'float64', new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] ), [ 4 ], [ 1 ], 0, 'row-major' );
+
+	actual = every( x );
+	expected = true;
+
+	t.strictEqual( actual.get(), expected, 'returns expected value' );
+
+	x = new ndarray( 'float64', new Float64Array( [ 1.0, 0.0, 3.0, -4.0 ] ), [ 4 ], [ 1 ], 0, 'row-major' );
+
+	actual = every( x );
+	expected = false;
+
+	t.strictEqual( actual.get(), expected, 'returns expected value' );
+	t.end();
+});
+
+tape( 'the function tests whether every element along one or more ndarray dimensions is truthy (column-major)', function test( t ) {
+	var expected;
+	var actual;
+	var x;
+
+	x = new ndarray( 'float64', new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] ), [ 4 ], [ 1 ], 0, 'column-major' );
+
+	actual = every( x );
+	expected = true;
+
+	t.strictEqual( actual.get(), expected, 'returns expected value' );
+
+	x = new ndarray( 'float64', new Float64Array( [ 1.0, 0.0, 3.0, -4.0 ] ), [ 4 ], [ 1 ], 0, 'column-major' );
+
+	actual = every( x );
+	expected = false;
+
+	t.strictEqual( actual.get(), expected, 'returns expected value' );
+	t.end();
+});
+
+tape( 'the function supports specifying reduction dimensions (row-major)', function test( t ) {
+	var expected;
+	var actual;
+	var opts;
+	var x;
+
+	x = new ndarray( 'float64', new Float64Array( [ 1.0, 2.0, 3.0, 4.0, -5.0, 6.0, -7.0, 8.0 ] ), [ 2, 4 ], [ 4, 1 ], 0, 'row-major' );
+
+	opts = {
+		'dims': [ 0 ]
+	};
+	actual = every( x, opts );
+	expected = [ true, true, true, true ];
+	t.deepEqual( ndarray2array( actual ), expected, 'returns expected value' );
+
+	opts = {
+		'dims': [ 0 ],
+		'keepdims': true
+	};
+	actual = every( x, opts );
+	expected = [ [ true, true, true, true ] ];
+
+	t.deepEqual( ndarray2array( actual ), expected, 'returns expected value' );
+
+	x = new ndarray( 'float64', new Float64Array( [ 1.0, 0.0, 3.0, 0.0, -5.0, 0.0, -7.0, 0.0 ] ), [ 2, 4 ], [ 4, 1 ], 0, 'row-major' );
+
+	opts = {
+		'dims': [ 0 ]
+	};
+	actual = every( x, opts );
+	expected = [ true, false, true, false ];
+	t.deepEqual( ndarray2array( actual ), expected, 'returns expected value' );
+
+	opts = {
+		'dims': [ 0 ],
+		'keepdims': true
+	};
+	actual = every( x, opts );
+	expected = [ [ true, false, true, false ] ];
+
+	t.deepEqual( ndarray2array( actual ), expected, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function supports specifying reduction dimensions (column-major)', function test( t ) {
+	var expected;
+	var actual;
+	var opts;
+	var x;
+
+	x = new ndarray( 'float64', new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ] ), [ 2, 4 ], [ 1, 2 ], 0, 'column-major' );
+
+	opts = {
+		'dims': [ 1 ]
+	};
+	actual = every( x, opts );
+	expected = [ true, true ];
+
+	t.deepEqual( ndarray2array( actual ), expected, 'returns expected value' );
+
+	opts = {
+		'dims': [ 1 ],
+		'keepdims': true
+	};
+	actual = every( x, opts );
+	expected = [ [ true ], [ true ] ];
+
+	t.deepEqual( ndarray2array( actual ), expected, 'returns expected value' );
+
+	x = new ndarray( 'float64', new Float64Array( [ 1.0, 0.0, 3.0, 0.0, 5.0, 0.0, 7.0, 0.0 ] ), [ 2, 4 ], [ 1, 2 ], 0, 'column-major' );
+
+	opts = {
+		'dims': [ 1 ]
+	};
+	actual = every( x, opts );
+	expected = [ true, false ];
+
+	t.deepEqual( ndarray2array( actual ), expected, 'returns expected value' );
+
+	opts = {
+		'dims': [ 1 ],
+		'keepdims': true
+	};
+	actual = every( x, opts );
+	expected = [ [ true ], [ false ] ];
+
+	t.deepEqual( ndarray2array( actual ), expected, 'returns expected value' );
+
+	t.end();
+});