diff --git a/.github/workflows/ci.yml b/.github/workflows/ci.yml
index 13b376c..784a327 100644
--- a/.github/workflows/ci.yml
+++ b/.github/workflows/ci.yml
@@ -46,4 +46,11 @@ jobs:
         run: uv sync --dev
 
       - name: Run unit tests
-        run: uv run pytest tests/ -v --tb=short
+        run: uv run pytest tests/ -v --tb=short --cov=igenbench --cov-report=term-missing --cov-report=xml
+
+      - name: Upload coverage report
+        if: matrix.python-version == '3.12'
+        uses: actions/upload-artifact@v4
+        with:
+          name: coverage-report
+          path: coverage.xml
diff --git a/AGENTS.md b/AGENTS.md
index e6452c8..48e2f92 100644
--- a/AGENTS.md
+++ b/AGENTS.md
@@ -146,5 +146,5 @@ outputs/
 - **Never** add API keys to source files. Use environment variables (see `.env.example`).
 - `VISItem.from_dict(path)` takes a **file path**, not a dict.
 - `EvalEntry.judgments` is a list — multiple (gen_model, eval_model) pairs can coexist on the same question (multi-model comparison).
-- The `Question` dataclass in `vis_item.py` is **deprecated**; use `EvalEntry` instead.
+- The `Question` dataclass in `vis_item.py` is **deprecated** and will be removed in a future version. Migrate to `EvalEntry`: replace `q` → `question`, `q_ground` → `ground`, `q_type` → `question_type`, and use `VISItem.evaluation: list[EvalEntry]` instead of a separate JSONL questions file.
 - When editing CLI commands, register them via `igenbench/cli/main.py` imports (side-effect import pattern).
diff --git a/igenbench/cli/batch_cli.py b/igenbench/cli/batch_cli.py
index 93cded4..6cc0323 100644
--- a/igenbench/cli/batch_cli.py
+++ b/igenbench/cli/batch_cli.py
@@ -27,7 +27,7 @@ def cmd_batch_gen(
         "--resume/--no-resume",
         help="Resume from existing state, skipping already generated images",
     ),
-):
+) -> None:
     """Batch generate infographic images for all VISItem JSON files in a directory."""
     json_files = sorted(Path(data_dir).glob("*.json"))
 
@@ -79,7 +79,7 @@ def cmd_batch_eval(
         "--resume/--no-resume",
         help="Resume from existing state, skipping already evaluated questions",
     ),
-):
+) -> None:
     """Batch evaluate generated images for all VISItem JSON files in a directory."""
     json_files = sorted(Path(data_dir).glob("*.json"))
 
diff --git a/igenbench/cli/eval_cli.py b/igenbench/cli/eval_cli.py
index 6a32ee9..f4b3320 100644
--- a/igenbench/cli/eval_cli.py
+++ b/igenbench/cli/eval_cli.py
@@ -33,7 +33,7 @@ def cmd_run_evaluation(
         "--resume",
         help="Resume from output directory to skip already processed items",
     ),
-):
+) -> None:
     """Run evaluation on a generated image using pre-generated questions.
 
     Evaluates the generated image on all questions in the VISItem.
diff --git a/igenbench/cli/gen_cli.py b/igenbench/cli/gen_cli.py
index 4c3fd7c..ed27769 100644
--- a/igenbench/cli/gen_cli.py
+++ b/igenbench/cli/gen_cli.py
@@ -25,7 +25,7 @@ def cmd_gen(
         "--resume",
         help="Resume from output directory to skip already generated images",
     ),
-):
+) -> None:
     """Generate image from text prompt using text-to-image model.
 
     Reads the VISItem and generates an image based on the t2i_prompt field.
diff --git a/igenbench/cli/main.py b/igenbench/cli/main.py
index 1e59a6f..e5c5687 100644
--- a/igenbench/cli/main.py
+++ b/igenbench/cli/main.py
@@ -11,7 +11,7 @@
 import igenbench.cli.score_cli  # noqa: E402, F401
 
 
-def main():
+def main() -> None:
     """Entry point for the IGenBench CLI."""
     app()
 
diff --git a/igenbench/cli/score_cli.py b/igenbench/cli/score_cli.py
index fb931a8..dafd65c 100644
--- a/igenbench/cli/score_cli.py
+++ b/igenbench/cli/score_cli.py
@@ -32,7 +32,7 @@ def cmd_score(
         "--by-type/--no-by-type",
         help="Show accuracy breakdown by question type",
     ),
-):
+) -> None:
     """Aggregate and display evaluation accuracy scores from the output directory."""
     output_path = Path(output_dir)
 
diff --git a/igenbench/engine/eval_engine.py b/igenbench/engine/eval_engine.py
index e8aeb13..40d1180 100644
--- a/igenbench/engine/eval_engine.py
+++ b/igenbench/engine/eval_engine.py
@@ -49,11 +49,18 @@ def judge_entry(
             model=eval_model, image_path=image_path, prompt=question_judgment_prompt
         )
 
+        if isinstance(response, dict):
+            analysis = response.get("analysis", "")
+            answer = response.get("answer", "")
+        else:
+            analysis = str(response) if response is not None else ""
+            answer = ""
+
         judgment = Judgment(
             eval_model=eval_model,
             gen_model=gen_model,
-            analysis=response.get("analysis", ""),
-            answer=response.get("answer", ""),
+            analysis=analysis,
+            answer=answer,
         )
 
         return judgment
diff --git a/igenbench/engine/gen_engine.py b/igenbench/engine/gen_engine.py
index b5799a2..79c09ca 100644
--- a/igenbench/engine/gen_engine.py
+++ b/igenbench/engine/gen_engine.py
@@ -1,3 +1,5 @@
+from PIL.Image import Image as PILImage
+
 from igenbench.engine.base_engine import BaseEngine
 from igenbench.utils.llm.client import LLMClient
 from igenbench.vis_item import VISItem
@@ -9,7 +11,7 @@ class GenEngine(BaseEngine):
     def __init__(self, llm_client: LLMClient, model: str):
         super().__init__(llm_client, model)
 
-    def text2image(self, item: VISItem):
+    def text2image(self, item: VISItem) -> PILImage:
         """Generate image from text prompt.
 
         Args:
diff --git a/igenbench/utils/io.py b/igenbench/utils/io.py
index b3e0293..6100b1a 100644
--- a/igenbench/utils/io.py
+++ b/igenbench/utils/io.py
@@ -100,8 +100,22 @@ def get_model_name_from_image_path(image_path: Path | str) -> str:
     return stem.split("_")[-1]
 
 
-def split_senmantic_and_data_in_t2i_prompt(t2i_prompt: str) -> tuple[str, str]:
-    """
-    Split the semantic and data parts of the T2I prompt.
+def split_semantic_and_data_in_t2i_prompt(t2i_prompt: str) -> tuple[str, str]:
+    """Split a T2I prompt into semantic description and data sections.
+
+    Expects the prompt to contain the separator "The given data is:".
+    Returns a (semantic_part, data_part) tuple.
+
+    Raises:
+        ValueError: If the separator is not found in the prompt.
     """
-    return t2i_prompt.split("The given data is:")
+    if not t2i_prompt:
+        raise ValueError("Prompt cannot be empty or None.")
+    separator = "The given data is:"
+    if separator not in t2i_prompt:
+        raise ValueError(
+            f"Prompt does not contain expected separator '{separator}'. "
+            "Cannot split semantic and data sections."
+        )
+    parts = t2i_prompt.split(separator, maxsplit=1)
+    return parts[0], parts[1]
diff --git a/igenbench/utils/llm/caller_registry.py b/igenbench/utils/llm/caller_registry.py
index 01ac799..4e04d8a 100644
--- a/igenbench/utils/llm/caller_registry.py
+++ b/igenbench/utils/llm/caller_registry.py
@@ -1,4 +1,4 @@
-from typing import Dict, Type, TYPE_CHECKING
+from typing import Callable, Dict, Type, TYPE_CHECKING
 
 if TYPE_CHECKING:
     from .llm_caller import LLMCaller
@@ -6,8 +6,19 @@
 CALLER_REGISTRY: Dict[str, Type["LLMCaller"]] = {}
 
 
-def register_caller(name: str):
-    def wrapper(cls: "LLMCaller") -> "LLMCaller":
+def register_caller(name: str) -> Callable[[Type["LLMCaller"]], Type["LLMCaller"]]:
+    """Class decorator that registers an LLMCaller implementation under *name*.
+
+    Usage::
+
+        @register_caller("google")
+        class GoogleCaller(LLMCaller): ...
+
+    Raises:
+        ValueError: If *name* is already registered.
+    """
+
+    def wrapper(cls: Type["LLMCaller"]) -> Type["LLMCaller"]:
         if name in CALLER_REGISTRY:
             raise ValueError(f"Caller {name} already registered")
         CALLER_REGISTRY[name] = cls
diff --git a/igenbench/utils/llm/client.py b/igenbench/utils/llm/client.py
index 1d83724..a6f5494 100644
--- a/igenbench/utils/llm/client.py
+++ b/igenbench/utils/llm/client.py
@@ -21,17 +21,38 @@ def _get_caller(self, provider: str) -> LLMCaller:
     def call_text_generation(
         self, model: str, prompt: str, **kwargs: Any
     ) -> Union[dict, str]:
+        """Generate text and parse any fenced code block / JSON in the response.
+
+        Returns:
+            Parsed dict if the response contains valid JSON, otherwise a plain string.
+            Returns an empty string if the provider returns None or an empty response.
+        """
         text_response = self._caller.generate_text(model, prompt, **kwargs)
+        if not text_response:
+            return ""
         return extract_from_markdown(text_response)
 
     def call_image_understanding(
         self, model: str, prompt: str, image_path: str, **kwargs: Any
     ) -> Union[dict, str]:
+        """Analyse an image and parse any fenced code block / JSON in the response.
+
+        Returns:
+            Parsed dict if the response contains valid JSON, otherwise a plain string.
+            Returns an empty string if the provider returns None or an empty response.
+        """
         text_response = self._caller.understand_image(
             model, prompt, image_path, **kwargs
         )
+        if not text_response:
+            return ""
         return extract_from_markdown(text_response)
 
     def call_image_generation(self, model: str, prompt: str, **kwargs: Any) -> PILImage:
+        """Generate an image and return it as a PIL Image.
+
+        Returns:
+            PIL Image object of the generated image.
+        """
         pil_image = self._caller.generate_image(model, prompt, **kwargs)
         return pil_image
diff --git a/igenbench/utils/llm/llm_caller.py b/igenbench/utils/llm/llm_caller.py
index 3741bbe..87a5eae 100644
--- a/igenbench/utils/llm/llm_caller.py
+++ b/igenbench/utils/llm/llm_caller.py
@@ -41,17 +41,54 @@ def base64_to_PILImage(base64_image_url: str) -> PILImage:
 
 
 class LLMCaller:
+    """Abstract base class for LLM provider integrations.
+
+    Subclasses must implement all three methods and register themselves with
+    ``@register_caller("<provider_name>")``.
+    """
+
     def generate_text(self, model: str, prompt: str, **kwargs: Any) -> str:
+        """Generate plain text from a text prompt.
+
+        Args:
+            model: Provider-specific model identifier.
+            prompt: Text prompt.
+            **kwargs: Additional provider-specific parameters.
+
+        Returns:
+            Generated text string.
+        """
         raise NotImplementedError
 
     def understand_image(
         self, model: str, prompt: str, image_path: str, **kwargs: Any
     ) -> str:
+        """Analyse an image and return a text response.
+
+        Args:
+            model: Provider-specific model identifier.
+            prompt: Instruction / question about the image.
+            image_path: Absolute or relative path to the image file.
+            **kwargs: Additional provider-specific parameters.
+
+        Returns:
+            Model's text response.
+        """
         raise NotImplementedError
 
     def generate_image(
         self, model: str, prompt: str, **kwargs: Any
     ) -> GoogleImage | PILImage:
+        """Generate an image from a text prompt.
+
+        Args:
+            model: Provider-specific model identifier.
+            prompt: Text description of the desired image.
+            **kwargs: Additional provider-specific parameters.
+
+        Returns:
+            Generated image as a Google ``Image`` or PIL ``Image`` object.
+        """
         raise NotImplementedError
 
 
diff --git a/igenbench/vis_item.py b/igenbench/vis_item.py
index e4a7830..9f02370 100644
--- a/igenbench/vis_item.py
+++ b/igenbench/vis_item.py
@@ -156,7 +156,7 @@ class VISItem:
     chart_type: Optional[str] = None
 
     # generation result: {model_name: image_path}
-    generation: Optional[dict] = field(default_factory=dict)
+    generation: Dict[str, Any] = field(default_factory=dict)
 
     # evaluation result: List[EvalEntry] with source field
     # Each entry has: source ("prompt" or "seed"), ground, question, question_type, judgments
diff --git a/prompts/gen_text2image.py b/prompts/gen_text2image.py
index da17bf7..b146502 100644
--- a/prompts/gen_text2image.py
+++ b/prompts/gen_text2image.py
@@ -1,4 +1,4 @@
-from nanochart.vis_item import VISItem
+from igenbench.vis_item import VISItem
 
 
 def get_prompt_text2image(item: VISItem) -> str:
diff --git a/pyproject.toml b/pyproject.toml
index 7af4ab3..b9f7d21 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -1,10 +1,33 @@
 [project]
 name = "igenbench"
 version = "0.1.0"
-description = "IGenBench - Benchmark for Infographic Generation"
+description = "IGenBench - Benchmark for evaluating the reliability of text-to-infographic generation"
 readme = "README.md"
 license = {text = "MIT"}
 requires-python = ">=3.10"
+authors = [
+    {name = "MisterBrookT", email = "yinghaotang2001@gmail.com"},
+]
+keywords = [
+    "benchmark",
+    "infographic",
+    "text-to-image",
+    "evaluation",
+    "multimodal",
+    "LLM",
+    "generative-ai",
+]
+classifiers = [
+    "Development Status :: 3 - Alpha",
+    "Intended Audience :: Science/Research",
+    "License :: OSI Approved :: MIT License",
+    "Programming Language :: Python :: 3",
+    "Programming Language :: Python :: 3.10",
+    "Programming Language :: Python :: 3.11",
+    "Programming Language :: Python :: 3.12",
+    "Topic :: Scientific/Engineering :: Artificial Intelligence",
+    "Topic :: Software Development :: Libraries :: Python Modules",
+]
 dependencies = [
     "google-genai>=1.49.0",
     "pillow>=12.0.0",
@@ -13,6 +36,11 @@ dependencies = [
     "requests>=2.31.0",
 ]
 
+[project.urls]
+Homepage = "https://github.com/MisterBrookT/IGenBench"
+Repository = "https://github.com/MisterBrookT/IGenBench"
+"Bug Tracker" = "https://github.com/MisterBrookT/IGenBench/issues"
+
 [project.optional-dependencies]
 replicate = ["replicate>=0.34.0"]
 
@@ -37,6 +65,7 @@ dev = [
     "commitizen>=4.10.0",
     "pre-commit>=4.5.0",
     "pytest>=9.0.1",
+    "pytest-cov>=6.0.0",
     "ruff>=0.14.6",
 ]
 
diff --git a/tests/test_caller_registry.py b/tests/test_caller_registry.py
new file mode 100644
index 0000000..7ba6462
--- /dev/null
+++ b/tests/test_caller_registry.py
@@ -0,0 +1,56 @@
+"""Unit tests for the @register_caller decorator and CALLER_REGISTRY."""
+
+import pytest
+
+from igenbench.utils.llm.caller_registry import CALLER_REGISTRY, register_caller
+from igenbench.utils.llm.llm_caller import LLMCaller
+
+
+def test_register_caller_adds_to_registry():
+    name = "_test_provider_add"
+    try:
+
+        @register_caller(name)
+        class _DummyCaller(LLMCaller):
+            pass
+
+        assert name in CALLER_REGISTRY
+        assert CALLER_REGISTRY[name] is _DummyCaller
+    finally:
+        CALLER_REGISTRY.pop(name, None)
+
+
+def test_register_caller_duplicate_raises():
+    name = "_test_provider_dup"
+    try:
+
+        @register_caller(name)
+        class _First(LLMCaller):
+            pass
+
+        with pytest.raises(ValueError, match="already registered"):
+
+            @register_caller(name)
+            class _Second(LLMCaller):
+                pass
+
+    finally:
+        CALLER_REGISTRY.pop(name, None)
+
+
+def test_register_caller_returns_class_unchanged():
+    name = "_test_provider_ret"
+    try:
+
+        @register_caller(name)
+        class _MyProvider(LLMCaller):
+            pass
+
+        assert _MyProvider.__name__ == "_MyProvider"
+    finally:
+        CALLER_REGISTRY.pop(name, None)
+
+
+def test_built_in_providers_registered():
+    for provider in ("google", "openrouter", "replicate"):
+        assert provider in CALLER_REGISTRY, f"{provider} not found in registry"
diff --git a/tests/test_cli_score.py b/tests/test_cli_score.py
new file mode 100644
index 0000000..1d06703
--- /dev/null
+++ b/tests/test_cli_score.py
@@ -0,0 +1,104 @@
+"""Unit tests for the `igenbench score` CLI command — no API keys required."""
+
+import json
+from pathlib import Path
+
+from typer.testing import CliRunner
+
+from igenbench.cli.main import app
+
+runner = CliRunner()
+
+
+def _make_result_file(tmp_path: Path, item_id: str, judgments: list) -> None:
+    """Write a minimal VISItem JSON with the given judgments."""
+    item_dir = tmp_path / item_id
+    item_dir.mkdir(parents=True, exist_ok=True)
+    data = {
+        "id": item_id,
+        "t2i_prompt": "A chart.",
+        "chart_type": "bar",
+        "reference_image_url": None,
+        "generation": {"my-gen-model": str(item_dir / "img.png")},
+        "evaluation": [
+            {
+                "source": "prompt",
+                "ground": "4",
+                "question": "How many bars?",
+                "question_type": "count",
+                "judgments": judgments,
+            }
+        ],
+    }
+    (item_dir / f"{item_id}.json").write_text(json.dumps(data))
+
+
+# ─── basic scoring ─────────────────────────────────────────────────────────────
+
+
+def test_score_shows_accuracy(tmp_path):
+    _make_result_file(
+        tmp_path,
+        "item-001",
+        [
+            {
+                "gen_model": "my-gen-model",
+                "eval_model": "my-eval-model",
+                "analysis": "",
+                "answer": "1",
+            }
+        ],
+    )
+    result = runner.invoke(app, ["score", "--output-dir", str(tmp_path)])
+    assert result.exit_code == 0
+    assert "100.0%" in result.output or "1/1" in result.output
+
+
+def test_score_no_results_exits_nonzero(tmp_path):
+    result = runner.invoke(app, ["score", "--output-dir", str(tmp_path)])
+    assert result.exit_code != 0
+
+
+def test_score_missing_dir_exits_nonzero(tmp_path):
+    result = runner.invoke(
+        app, ["score", "--output-dir", str(tmp_path / "nonexistent")]
+    )
+    assert result.exit_code != 0
+
+
+def test_score_filter_by_gen_model(tmp_path):
+    _make_result_file(
+        tmp_path,
+        "item-002",
+        [
+            {
+                "gen_model": "model-A",
+                "eval_model": "eval-M",
+                "analysis": "",
+                "answer": "1",
+            }
+        ],
+    )
+    # Correct filter — should find result
+    result = runner.invoke(
+        app, ["score", "--output-dir", str(tmp_path), "--gen-model", "model-A"]
+    )
+    assert result.exit_code == 0
+
+    # Wrong filter — should print "No evaluation results"
+    result2 = runner.invoke(
+        app, ["score", "--output-dir", str(tmp_path), "--gen-model", "model-B"]
+    )
+    assert result2.exit_code == 0
+    assert "No evaluation results" in result2.output
+
+
+def test_score_by_source_breakdown(tmp_path):
+    _make_result_file(
+        tmp_path,
+        "item-003",
+        [{"gen_model": "gm", "eval_model": "em", "analysis": "", "answer": "0"}],
+    )
+    result = runner.invoke(app, ["score", "--output-dir", str(tmp_path), "--by-source"])
+    assert result.exit_code == 0
+    assert "prompt" in result.output
diff --git a/tests/test_eval_engine.py b/tests/test_eval_engine.py
new file mode 100644
index 0000000..9247c9a
--- /dev/null
+++ b/tests/test_eval_engine.py
@@ -0,0 +1,81 @@
+"""Unit tests for EvalEngine — no API keys required (LLMClient is mocked)."""
+
+from unittest.mock import MagicMock
+
+import pytest
+
+from igenbench.engine.eval_engine import EvalEngine
+from igenbench.vis_item import EvalEntry, Judgment
+
+
+def _make_engine(response):
+    """Return an EvalEngine whose LLMClient returns *response* from call_image_understanding."""
+    client = MagicMock()
+    client.call_image_understanding.return_value = response
+    return EvalEngine(llm_client=client, model="eval-model")
+
+
+# ─── judge_entry: happy path ──────────────────────────────────────────────────
+
+
+def test_judge_entry_returns_judgment_with_dict_response():
+    engine = _make_engine({"analysis": "looks correct", "answer": "1"})
+    entry = EvalEntry(question="How many bars?", source="prompt", ground="4")
+    j = engine.judge_entry(entry, "gen-model", "eval-model", "/fake/image.png")
+    assert isinstance(j, Judgment)
+    assert j.analysis == "looks correct"
+    assert j.answer == "1"
+    assert j.gen_model == "gen-model"
+    assert j.eval_model == "eval-model"
+
+
+def test_judge_entry_handles_plain_string_response():
+    """When LLM returns a non-JSON string, analysis gets the text and answer is empty."""
+    engine = _make_engine("The chart shows 4 bars.")
+    entry = EvalEntry(question="How many bars?", source="prompt", ground="4")
+    j = engine.judge_entry(entry, "gen-model", "eval-model", "/fake/image.png")
+    assert j.analysis == "The chart shows 4 bars."
+    assert j.answer == ""
+
+
+def test_judge_entry_raises_on_empty_question():
+    engine = _make_engine({"analysis": "", "answer": "1"})
+    entry = EvalEntry(question="", source="prompt", ground="4")
+    with pytest.raises(ValueError, match="Question is required"):
+        engine.judge_entry(entry, "gen-model", "eval-model", "/fake/image.png")
+
+
+# ─── check helpers ───────────────────────────────────────────────────────────
+
+
+def test_check_eval_entry_being_judged_true():
+    engine = _make_engine({})
+    entry = EvalEntry(
+        question="Q?",
+        judgments=[Judgment(gen_model="gm", eval_model="em", analysis="", answer="1")],
+    )
+    assert engine.check_eval_entry_being_judged(entry, "gm", "em") is True
+
+
+def test_check_eval_entry_being_judged_false():
+    engine = _make_engine({})
+    entry = EvalEntry(question="Q?")
+    assert engine.check_eval_entry_being_judged(entry, "gm", "em") is False
+
+
+def test_check_fully_evaluated_delegates_to_vis_item():
+    from igenbench.vis_item import VISItem
+
+    engine = _make_engine({})
+    item = VISItem(
+        id="x",
+        evaluation=[
+            EvalEntry(
+                question="Q?",
+                judgments=[
+                    Judgment(gen_model="gm", eval_model="em", analysis="", answer="1")
+                ],
+            )
+        ],
+    )
+    assert engine.check_fully_evaluated(item, "gm", "em") is True
diff --git a/tests/test_io.py b/tests/test_io.py
new file mode 100644
index 0000000..8d689d8
--- /dev/null
+++ b/tests/test_io.py
@@ -0,0 +1,83 @@
+"""Unit tests for igenbench.utils.io — no API keys required."""
+
+import json
+
+import pytest
+
+from igenbench.utils.io import (
+    extract_from_markdown,
+    split_semantic_and_data_in_t2i_prompt,
+)
+
+
+# ─── extract_from_markdown ────────────────────────────────────────────────────
+
+
+def test_extract_plain_json_string():
+    text = '{"analysis": "good", "answer": "1"}'
+    result = extract_from_markdown(text)
+    assert result == {"analysis": "good", "answer": "1"}
+
+
+def test_extract_fenced_json_block():
+    text = '```json\n{"analysis": "ok", "answer": "0"}\n```'
+    result = extract_from_markdown(text)
+    assert result == {"analysis": "ok", "answer": "0"}
+
+
+def test_extract_fenced_block_no_lang():
+    text = "```\nhello world\n```"
+    result = extract_from_markdown(text)
+    assert result == "hello world"
+
+
+def test_extract_plain_text_fallback():
+    text = "Just some plain text with no code block."
+    result = extract_from_markdown(text)
+    assert result == text
+
+
+def test_extract_nested_json_array():
+    payload = [{"key": "value"}]
+    text = f"```json\n{json.dumps(payload)}\n```"
+    result = extract_from_markdown(text)
+    assert result == payload
+
+
+# ─── split_semantic_and_data_in_t2i_prompt ────────────────────────────────────
+
+
+def test_split_returns_two_parts():
+    prompt = "Draw a bar chart. The given data is: Q1=10, Q2=20"
+    semantic, data = split_semantic_and_data_in_t2i_prompt(prompt)
+    assert semantic == "Draw a bar chart. "
+    assert data == " Q1=10, Q2=20"
+
+
+def test_split_strips_nothing_extra():
+    prompt = "Semantic part.The given data is:data part"
+    semantic, data = split_semantic_and_data_in_t2i_prompt(prompt)
+    assert "Semantic" in semantic
+    assert "data part" in data
+
+
+def test_split_raises_when_separator_missing():
+    with pytest.raises(ValueError, match="separator"):
+        split_semantic_and_data_in_t2i_prompt("No separator here.")
+
+
+def test_split_raises_on_empty_string():
+    with pytest.raises(ValueError, match="empty or None"):
+        split_semantic_and_data_in_t2i_prompt("")
+
+
+def test_split_raises_on_none():
+    with pytest.raises((ValueError, TypeError)):
+        split_semantic_and_data_in_t2i_prompt(None)  # type: ignore[arg-type]
+
+
+def test_split_only_splits_on_first_occurrence():
+    prompt = "A.The given data is:B.The given data is:C"
+    semantic, data = split_semantic_and_data_in_t2i_prompt(prompt)
+    assert semantic == "A."
+    assert "B.The given data is:C" in data
diff --git a/uv.lock b/uv.lock
index de4a401..c56c2c1 100644
--- a/uv.lock
+++ b/uv.lock
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 ]
 
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+]
+
+[package.optional-dependencies]
+toml = [
+    { name = "tomli", marker = "python_full_version <= '3.11'" },
+]
+
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 version = "0.6.3"
@@ -371,6 +489,7 @@ dev = [
     { name = "commitizen" },
     { name = "pre-commit" },
     { name = "pytest" },
+    { name = "pytest-cov" },
     { name = "ruff" },
 ]
 
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     { name = "pre-commit", specifier = ">=4.5.0" },
     { name = "pytest", specifier = ">=9.0.1" },
+    { name = "pytest-cov", specifier = ">=6.0.0" },
     { name = "ruff", specifier = ">=0.14.6" },
 ]
 
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 ]
 
+[[package]]
+name = "pytest-cov"
+version = "7.1.0"
+source = { registry = "https://pypi.org/simple" }
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 name = "pyyaml"
 version = "6.0.3"