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readme][improvement][init-sort][sort imports alphabetically in
  init][improvement][version-bump][bump version to
  0.3.0][feat][tokenizer-class][add MythosTokenizer to init
  exports][feat][test-tokenizer][add tokenizer test suite with printed output]

tests/test_tokenizer.py

@@ -0,0 +1,75 @@
+import pytest
+from open_mythos.tokenizer import MythosTokenizer
+
+
+@pytest.fixture(scope="module")
+def tokenizer():
+    tok = MythosTokenizer()
+    print(f"\nLoaded tokenizer: {tok.tokenizer.name_or_path}")
+    return tok
+
+
+def test_loads(tokenizer):
+    assert tokenizer is not None
+    print(f"Tokenizer: {tokenizer}")
+
+
+def test_vocab_size(tokenizer):
+    size = tokenizer.vocab_size
+    print(f"Vocab size: {size:,}")
+    assert size > 0
+
+
+def test_encode_returns_list_of_ints(tokenizer):
+    ids = tokenizer.encode("Hello, world!")
+    print(f"encode('Hello, world!') → {ids}")
+    assert isinstance(ids, list)
+    assert all(isinstance(i, int) for i in ids)
+    assert len(ids) > 0
+
+
+def test_encode_empty_string(tokenizer):
+    ids = tokenizer.encode("")
+    print(f"encode('') → {ids}")
+    assert isinstance(ids, list)
+
+
+def test_decode_returns_string(tokenizer):
+    ids = tokenizer.encode("Hello, world!")
+    text = tokenizer.decode(ids)
+    print(f"decode({ids}) → '{text}'")
+    assert isinstance(text, str)
+
+
+def test_roundtrip(tokenizer):
+    original = "The quick brown fox jumps over the lazy dog."
+    ids = tokenizer.encode(original)
+    recovered = tokenizer.decode(ids)
+    print(f"original:  '{original}'")
+    print(f"token ids: {ids}")
+    print(f"recovered: '{recovered}'")
+    assert original in recovered or recovered in original
+
+
+def test_encode_long_text(tokenizer):
+    text = "OpenMythos is a recurrent depth transformer. " * 100
+    ids = tokenizer.encode(text)
+    print(f"Long text ({len(text)} chars) → {len(ids)} tokens")
+    assert len(ids) > 100
+
+
+def test_custom_model_id():
+    tok = MythosTokenizer(model_id="openai/gpt-oss-20b")
+    print(f"Custom model_id vocab size: {tok.vocab_size:,}")
+    assert tok.vocab_size > 0
+
+
+def test_vocab_size_consistent(tokenizer):
+    outer = tokenizer.vocab_size
+    inner = tokenizer.tokenizer.vocab_size
+    print(f"vocab_size property: {outer:,}  |  inner tokenizer.vocab_size: {inner:,}")
+    assert outer == inner
+
+
+if __name__ == "__main__":
+    pytest.main([__file__, "--verbose", "-s"])