codeant-ai-for-open-source[bot] commented on code in PR #39922:
URL: https://github.com/apache/superset/pull/39922#discussion_r3482431779


##########
superset/mcp_service/chart/plugins/handlebars.py:
##########
@@ -0,0 +1,193 @@
+# Licensed to the Apache Software Foundation (ASF) under one
+# or more contributor license agreements.  See the NOTICE file
+# distributed with this work for additional information
+# regarding copyright ownership.  The ASF licenses this file
+# to you 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.
+
+"""Handlebars chart type plugin."""
+
+from __future__ import annotations
+
+from typing import Any
+
+from superset.mcp_service.chart.chart_utils import (
+    _handlebars_chart_what,
+    _summarize_filters,
+    map_handlebars_config,
+)
+from superset.mcp_service.chart.plugin import BaseChartPlugin
+from superset.mcp_service.chart.schemas import ColumnRef, HandlebarsChartConfig
+from superset.mcp_service.chart.validation.dataset_validator import 
DatasetValidator
+from superset.mcp_service.common.error_schemas import ChartGenerationError
+
+
+class HandlebarsChartPlugin(BaseChartPlugin):
+    """Plugin for handlebars chart type (custom HTML template charts)."""
+
+    chart_type = "handlebars"
+    display_name = "Handlebars (Custom Template)"
+    native_viz_types = {
+        "handlebars": "Custom Template Chart",
+    }
+
+    def pre_validate(
+        self,
+        config: dict[str, Any],
+    ) -> ChartGenerationError | None:
+        if "handlebars_template" not in config:
+            return ChartGenerationError(
+                error_type="missing_handlebars_template",
+                message="Handlebars chart missing required field: 
handlebars_template",
+                details=(
+                    "Handlebars charts require a 'handlebars_template' string "
+                    "containing Handlebars HTML template markup"
+                ),
+                suggestions=[
+                    "Add 'handlebars_template' with a Handlebars HTML 
template",
+                    "Data is available as {{data}} array in the template",
+                    "Example: '<ul>{{#each data}}<li>{{this.name}}: "
+                    "{{this.value}}</li>{{/each}}</ul>'",
+                ],
+                error_code="MISSING_HANDLEBARS_TEMPLATE",
+            )
+
+        template = config.get("handlebars_template")
+        if not isinstance(template, str) or not template.strip():
+            return ChartGenerationError(
+                error_type="invalid_handlebars_template",
+                message="Handlebars template must be a non-empty string",
+                details=(
+                    "The 'handlebars_template' field must be a non-empty 
string "
+                    "containing valid Handlebars HTML template markup"
+                ),
+                suggestions=[
+                    "Ensure handlebars_template is a non-empty string",
+                    "Example: '<ul>{{#each 
data}}<li>{{this.name}}</li>{{/each}}</ul>'",
+                ],
+                error_code="INVALID_HANDLEBARS_TEMPLATE",
+            )
+
+        query_mode = config.get("query_mode", "aggregate")
+        if query_mode not in ("aggregate", "raw"):
+            return ChartGenerationError(
+                error_type="invalid_query_mode",
+                message="Invalid query_mode for handlebars chart",
+                details="query_mode must be either 'aggregate' or 'raw'",
+                suggestions=[
+                    "Use 'aggregate' for aggregated data (default)",
+                    "Use 'raw' for individual rows",
+                ],
+                error_code="INVALID_QUERY_MODE",
+            )
+
+        if query_mode == "raw" and not config.get("columns"):
+            return ChartGenerationError(
+                error_type="missing_raw_columns",
+                message="Handlebars chart in 'raw' mode requires 'columns'",
+                details=(
+                    "When query_mode is 'raw', you must specify which columns "
+                    "to include in the query results"
+                ),
+                suggestions=[
+                    "Add 'columns': [{'name': 'column_name'}] for raw mode",
+                    "Or use query_mode='aggregate' with 'metrics' and optional 
'groupby'",  # noqa: E501
+                ],
+                error_code="MISSING_RAW_COLUMNS",
+            )
+
+        if query_mode == "aggregate" and not config.get("metrics"):
+            return ChartGenerationError(
+                error_type="missing_aggregate_metrics",
+                message="Handlebars chart in 'aggregate' mode requires 
'metrics'",
+                details=(
+                    "When query_mode is 'aggregate' (default), you must 
specify "
+                    "at least one metric with an aggregate function"
+                ),
+                suggestions=[
+                    "Add 'metrics': [{'name': 'column', 'aggregate': 'SUM'}]",
+                    "Or use query_mode='raw' with 'columns' for individual 
rows",
+                ],
+                error_code="MISSING_AGGREGATE_METRICS",
+            )
+
+        return None
+
+    def extract_column_refs(self, config: Any) -> list[ColumnRef]:
+        if not isinstance(config, HandlebarsChartConfig):
+            return []
+        refs: list[ColumnRef] = []
+        if config.columns:
+            refs.extend(config.columns)
+        if config.metrics:
+            refs.extend(config.metrics)
+        if config.groupby:
+            refs.extend(config.groupby)
+        if config.filters:
+            for f in config.filters:
+                refs.append(ColumnRef(name=f.column))
+        return refs
+
+    def to_form_data(
+        self, config: Any, dataset_id: int | str | None = None
+    ) -> dict[str, Any]:
+        return map_handlebars_config(config)
+
+    def generate_name(self, config: Any, dataset_name: str | None = None) -> 
str:
+        what = _handlebars_chart_what(config)
+        context = _summarize_filters(getattr(config, "filters", None))
+        return self._with_context(what, context)
+
+    def resolve_viz_type(self, config: Any) -> str:
+        return "handlebars"
+
+    def normalize_column_refs(self, config: Any, dataset_context: Any) -> Any:
+        config_dict = config.model_dump()
+
+        def _norm_list(key: str) -> None:
+            if config_dict.get(key):
+                for col in config_dict[key]:
+                    if col.get("saved_metric"):
+                        col["name"] = 
DatasetValidator._get_canonical_metric_name(
+                            col["name"], dataset_context
+                        )
+                    elif not col.get("sql_expression"):
+                        col["name"] = 
DatasetValidator._get_canonical_column_name(
+                            col["name"], dataset_context
+                        )
+
+        _norm_list("columns")
+        _norm_list("metrics")
+        _norm_list("groupby")
+        DatasetValidator._normalize_filters(config_dict, dataset_context)
+        return HandlebarsChartConfig.model_validate(config_dict)
+
+    def schema_error_hint(self) -> ChartGenerationError | None:

Review Comment:
   **Suggestion:** Add a docstring to `schema_error_hint` describing when this 
standardized validation error hint should be used. [custom_rule]
   
   **Severity Level:** Minor ⚠️
   <details>
   <summary><b>Why it matters? 🤔 </b></summary>
   
   This is a newly introduced method in the added file, and it has no 
docstring. The custom rule explicitly flags new Python functions and classes 
without docstrings, so the suggestion is verified.
   </details>
   
   [![Fix in 
Cursor](https://new-codeant-butcket.s3.us-west-1.amazonaws.com/badges/fix-in-cursor-flat.svg)](https://app.codeant.ai/fix-in-ide?tool=cursor&prompt_id=c5af1b3cd8f9495d81a9ed9d55ba5574&service=github&base_url=https%3A%2F%2Fgithub.com&org=apache&repo=apache%2Fsuperset)
 [![Fix in VSCode 
Claude](https://new-codeant-butcket.s3.us-west-1.amazonaws.com/badges/fix-in-vscode-claude-flat.svg)](https://app.codeant.ai/fix-in-ide?tool=vscode-claude&prompt_id=c5af1b3cd8f9495d81a9ed9d55ba5574&service=github&base_url=https%3A%2F%2Fgithub.com&org=apache&repo=apache%2Fsuperset)
   
   *(Use Cmd/Ctrl + Click for best experience)*
   <details>
   <summary><b>Prompt for AI Agent 🤖 </b></summary>
   
   ```mdx
   This is a comment left during a code review.
   
   **Path:** superset/mcp_service/chart/plugins/handlebars.py
   **Line:** 175:175
   **Comment:**
        *Custom Rule: Add a docstring to `schema_error_hint` describing when 
this standardized validation error hint should be used.
   
   Validate the correctness of the flagged issue. If correct, How can I resolve 
this? If you propose a fix, implement it and please make it concise.
   Once fix is implemented, also check other comments on the same PR, and ask 
user if the user wants to fix the rest of the comments as well. if said yes, 
then fetch all the comments validate the correctness and implement a minimal fix
   ```
   </details>
   <a 
href='https://app.codeant.ai/feedback?pr_url=https%3A%2F%2Fgithub.com%2Fapache%2Fsuperset%2Fpull%2F39922&comment_hash=c609cdb103af4ab9af13cee25bfc114a0230ce3e58ac2b1a03083603c86956b2&reaction=like'>👍</a>
 | <a 
href='https://app.codeant.ai/feedback?pr_url=https%3A%2F%2Fgithub.com%2Fapache%2Fsuperset%2Fpull%2F39922&comment_hash=c609cdb103af4ab9af13cee25bfc114a0230ce3e58ac2b1a03083603c86956b2&reaction=dislike'>👎</a>



##########
superset/mcp_service/chart/plugins/pie.py:
##########
@@ -0,0 +1,139 @@
+# Licensed to the Apache Software Foundation (ASF) under one
+# or more contributor license agreements.  See the NOTICE file
+# distributed with this work for additional information
+# regarding copyright ownership.  The ASF licenses this file
+# to you 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.
+
+"""Pie chart type plugin."""
+
+from __future__ import annotations
+
+from typing import Any
+
+from superset.mcp_service.chart.chart_utils import (
+    _pie_chart_what,
+    _summarize_filters,
+    map_pie_config,
+)
+from superset.mcp_service.chart.plugin import BaseChartPlugin
+from superset.mcp_service.chart.schemas import ColumnRef, PieChartConfig
+from superset.mcp_service.chart.validation.dataset_validator import 
DatasetValidator
+from superset.mcp_service.common.error_schemas import ChartGenerationError
+
+
+class PieChartPlugin(BaseChartPlugin):
+    """Plugin for pie chart type."""
+
+    chart_type = "pie"
+    display_name = "Pie / Donut Chart"
+    native_viz_types = {
+        "pie": "Pie Chart",
+    }
+
+    def pre_validate(
+        self,
+        config: dict[str, Any],
+    ) -> ChartGenerationError | None:
+        missing_fields = []

Review Comment:
   **Suggestion:** Add a docstring to this newly added method to describe its 
validation purpose, expected config shape, and returned error behavior. 
[custom_rule]
   
   **Severity Level:** Minor ⚠️
   <details>
   <summary><b>Why it matters? 🤔 </b></summary>
   
   This is a newly added method in a new Python file, and it has no docstring. 
The custom rule requires newly added Python functions and classes to be 
documented inline, so the suggestion correctly identifies a real violation.
   </details>
   
   [![Fix in 
Cursor](https://new-codeant-butcket.s3.us-west-1.amazonaws.com/badges/fix-in-cursor-flat.svg)](https://app.codeant.ai/fix-in-ide?tool=cursor&prompt_id=72cb70fc80ed43099db6ca19699df578&service=github&base_url=https%3A%2F%2Fgithub.com&org=apache&repo=apache%2Fsuperset)
 [![Fix in VSCode 
Claude](https://new-codeant-butcket.s3.us-west-1.amazonaws.com/badges/fix-in-vscode-claude-flat.svg)](https://app.codeant.ai/fix-in-ide?tool=vscode-claude&prompt_id=72cb70fc80ed43099db6ca19699df578&service=github&base_url=https%3A%2F%2Fgithub.com&org=apache&repo=apache%2Fsuperset)
   
   *(Use Cmd/Ctrl + Click for best experience)*
   <details>
   <summary><b>Prompt for AI Agent 🤖 </b></summary>
   
   ```mdx
   This is a comment left during a code review.
   
   **Path:** superset/mcp_service/chart/plugins/pie.py
   **Line:** 44:48
   **Comment:**
        *Custom Rule: Add a docstring to this newly added method to describe 
its validation purpose, expected config shape, and returned error behavior.
   
   Validate the correctness of the flagged issue. If correct, How can I resolve 
this? If you propose a fix, implement it and please make it concise.
   Once fix is implemented, also check other comments on the same PR, and ask 
user if the user wants to fix the rest of the comments as well. if said yes, 
then fetch all the comments validate the correctness and implement a minimal fix
   ```
   </details>
   <a 
href='https://app.codeant.ai/feedback?pr_url=https%3A%2F%2Fgithub.com%2Fapache%2Fsuperset%2Fpull%2F39922&comment_hash=a48a16599ccaa3588fbbd8bd2036d362a40ee2ed694d012e411eed96a36bdfcc&reaction=like'>👍</a>
 | <a 
href='https://app.codeant.ai/feedback?pr_url=https%3A%2F%2Fgithub.com%2Fapache%2Fsuperset%2Fpull%2F39922&comment_hash=a48a16599ccaa3588fbbd8bd2036d362a40ee2ed694d012e411eed96a36bdfcc&reaction=dislike'>👎</a>



##########
superset/mcp_service/chart/plugins/mixed_timeseries.py:
##########
@@ -0,0 +1,172 @@
+# Licensed to the Apache Software Foundation (ASF) under one
+# or more contributor license agreements.  See the NOTICE file
+# distributed with this work for additional information
+# regarding copyright ownership.  The ASF licenses this file
+# to you 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.
+
+"""Mixed timeseries chart type plugin."""
+
+from __future__ import annotations
+
+from typing import Any
+
+from superset.mcp_service.chart.chart_utils import (
+    _mixed_timeseries_what,
+    _summarize_filters,
+    map_mixed_timeseries_config,
+)
+from superset.mcp_service.chart.plugin import BaseChartPlugin
+from superset.mcp_service.chart.schemas import ColumnRef, 
MixedTimeseriesChartConfig
+from superset.mcp_service.chart.validation.dataset_validator import 
DatasetValidator
+from superset.mcp_service.common.error_schemas import ChartGenerationError
+
+
+class MixedTimeseriesChartPlugin(BaseChartPlugin):
+    """Plugin for mixed_timeseries chart type."""
+
+    chart_type = "mixed_timeseries"
+    display_name = "Mixed Timeseries"
+    native_viz_types = {
+        "mixed_timeseries": "Mixed Timeseries Chart",
+    }
+
+    def pre_validate(
+        self,
+        config: dict[str, Any],
+    ) -> ChartGenerationError | None:
+        missing_fields = []
+
+        if "x" not in config and "x_axis" not in config:
+            missing_fields.append("'x' (X-axis temporal column)")
+        if not config.get("y") and not config.get("metrics"):
+            missing_fields.append("'y' (primary Y-axis metrics)")
+        if not config.get("y_secondary") and not config.get("metrics_b"):
+            missing_fields.append("'y_secondary' (secondary Y-axis metrics)")
+
+        if missing_fields:
+            return ChartGenerationError(
+                error_type="missing_mixed_timeseries_fields",
+                message=(
+                    f"Mixed timeseries chart missing required fields: "
+                    f"{', '.join(missing_fields)}"
+                ),
+                details=(
+                    "Mixed timeseries charts require an x-axis, primary 
metrics, "
+                    "and secondary metrics"
+                ),
+                suggestions=[
+                    "Add 'x' field: {'name': 'date_column'}",
+                    "Add 'y' field: [{'name': 'revenue', 'aggregate': 'SUM'}]",
+                    "Add 'y_secondary': [{'name': 'orders', 'aggregate': 
'COUNT'}]",
+                    "Optional: 'primary_kind' and 'secondary_kind' for chart 
types",
+                ],
+                error_code="MISSING_MIXED_TIMESERIES_FIELDS",
+            )
+
+        for field_name in ["y", "y_secondary"]:
+            if not isinstance(config.get(field_name, []), list):
+                return ChartGenerationError(
+                    error_type=f"invalid_{field_name}_format",
+                    message=f"'{field_name}' must be a list of metrics",
+                    details=(
+                        f"The '{field_name}' field must be an array of metric "
+                        "specifications"
+                    ),
+                    suggestions=[
+                        f"Wrap in array: '{field_name}': "
+                        "[{'name': 'col', 'aggregate': 'SUM'}]",
+                    ],
+                    error_code=f"INVALID_{field_name.upper()}_FORMAT",
+                )
+
+        return None
+
+    def extract_column_refs(self, config: Any) -> list[ColumnRef]:
+        if not isinstance(config, MixedTimeseriesChartConfig):
+            return []
+        refs: list[ColumnRef] = [config.x]
+        refs.extend(config.y)
+        refs.extend(config.y_secondary)
+        if config.group_by:
+            refs.extend(config.group_by)
+        if config.group_by_secondary:
+            refs.extend(config.group_by_secondary)
+        if config.filters:
+            for f in config.filters:
+                refs.append(ColumnRef(name=f.column))
+        return refs
+
+    def to_form_data(
+        self, config: Any, dataset_id: int | str | None = None
+    ) -> dict[str, Any]:
+        return map_mixed_timeseries_config(config, dataset_id=dataset_id)
+
+    def generate_name(self, config: Any, dataset_name: str | None = None) -> 
str:
+        what = _mixed_timeseries_what(config)
+        context = _summarize_filters(config.filters)
+        return self._with_context(what, context)
+
+    def resolve_viz_type(self, config: Any) -> str:

Review Comment:
   **Suggestion:** Add a docstring that states this method's purpose and return 
value for visualization type resolution. [custom_rule]
   
   **Severity Level:** Minor ⚠️
   <details>
   <summary><b>Why it matters? 🤔 </b></summary>
   
   This is a new method with no docstring. The custom rule says newly added 
Python functions should be documented inline, so the suggestion is verified.
   </details>
   
   [![Fix in 
Cursor](https://new-codeant-butcket.s3.us-west-1.amazonaws.com/badges/fix-in-cursor-flat.svg)](https://app.codeant.ai/fix-in-ide?tool=cursor&prompt_id=c60b48d6e5b749aaa01787d9f41d003f&service=github&base_url=https%3A%2F%2Fgithub.com&org=apache&repo=apache%2Fsuperset)
 [![Fix in VSCode 
Claude](https://new-codeant-butcket.s3.us-west-1.amazonaws.com/badges/fix-in-vscode-claude-flat.svg)](https://app.codeant.ai/fix-in-ide?tool=vscode-claude&prompt_id=c60b48d6e5b749aaa01787d9f41d003f&service=github&base_url=https%3A%2F%2Fgithub.com&org=apache&repo=apache%2Fsuperset)
   
   *(Use Cmd/Ctrl + Click for best experience)*
   <details>
   <summary><b>Prompt for AI Agent 🤖 </b></summary>
   
   ```mdx
   This is a comment left during a code review.
   
   **Path:** superset/mcp_service/chart/plugins/mixed_timeseries.py
   **Line:** 120:120
   **Comment:**
        *Custom Rule: Add a docstring that states this method's purpose and 
return value for visualization type resolution.
   
   Validate the correctness of the flagged issue. If correct, How can I resolve 
this? If you propose a fix, implement it and please make it concise.
   Once fix is implemented, also check other comments on the same PR, and ask 
user if the user wants to fix the rest of the comments as well. if said yes, 
then fetch all the comments validate the correctness and implement a minimal fix
   ```
   </details>
   <a 
href='https://app.codeant.ai/feedback?pr_url=https%3A%2F%2Fgithub.com%2Fapache%2Fsuperset%2Fpull%2F39922&comment_hash=25a39505fc75f7481830ed172da6c1ec37b33f3ad9b54e39fd47597edaaa29b8&reaction=like'>👍</a>
 | <a 
href='https://app.codeant.ai/feedback?pr_url=https%3A%2F%2Fgithub.com%2Fapache%2Fsuperset%2Fpull%2F39922&comment_hash=25a39505fc75f7481830ed172da6c1ec37b33f3ad9b54e39fd47597edaaa29b8&reaction=dislike'>👎</a>



##########
superset/mcp_service/chart/plugins/pie.py:
##########
@@ -0,0 +1,139 @@
+# Licensed to the Apache Software Foundation (ASF) under one
+# or more contributor license agreements.  See the NOTICE file
+# distributed with this work for additional information
+# regarding copyright ownership.  The ASF licenses this file
+# to you 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.
+
+"""Pie chart type plugin."""
+
+from __future__ import annotations
+
+from typing import Any
+
+from superset.mcp_service.chart.chart_utils import (
+    _pie_chart_what,
+    _summarize_filters,
+    map_pie_config,
+)
+from superset.mcp_service.chart.plugin import BaseChartPlugin
+from superset.mcp_service.chart.schemas import ColumnRef, PieChartConfig
+from superset.mcp_service.chart.validation.dataset_validator import 
DatasetValidator
+from superset.mcp_service.common.error_schemas import ChartGenerationError
+
+
+class PieChartPlugin(BaseChartPlugin):
+    """Plugin for pie chart type."""
+
+    chart_type = "pie"
+    display_name = "Pie / Donut Chart"
+    native_viz_types = {
+        "pie": "Pie Chart",
+    }
+
+    def pre_validate(
+        self,
+        config: dict[str, Any],
+    ) -> ChartGenerationError | None:
+        missing_fields = []
+
+        if "dimension" not in config and "groupby" not in config:
+            missing_fields.append("'dimension' (category column for slices)")
+        if "metric" not in config:
+            missing_fields.append("'metric' (value metric for slice sizes)")
+
+        if missing_fields:
+            return ChartGenerationError(
+                error_type="missing_pie_fields",
+                message=(
+                    f"Pie chart missing required fields: {', 
'.join(missing_fields)}"
+                ),
+                details=(
+                    "Pie charts require a dimension (categories) and a metric 
(values)"
+                ),
+                suggestions=[
+                    "Add 'dimension' field: {'name': 'category_column'}",
+                    "Add 'metric' field: {'name': 'value_column', 'aggregate': 
'SUM'}",
+                    "Example: {'chart_type': 'pie', 'dimension': {'name': 
'product'}, "
+                    "'metric': {'name': 'revenue', 'aggregate': 'SUM'}}",
+                ],
+                error_code="MISSING_PIE_FIELDS",
+            )
+
+        return None
+
+    def extract_column_refs(self, config: Any) -> list[ColumnRef]:
+        if not isinstance(config, PieChartConfig):
+            return []
+        refs: list[ColumnRef] = [config.dimension, config.metric]
+        if config.filters:
+            for f in config.filters:
+                refs.append(ColumnRef(name=f.column))
+        return refs
+
+    def to_form_data(
+        self, config: Any, dataset_id: int | str | None = None
+    ) -> dict[str, Any]:
+        return map_pie_config(config)
+
+    def generate_name(self, config: Any, dataset_name: str | None = None) -> 
str:
+        what = _pie_chart_what(config)
+        context = _summarize_filters(config.filters)
+        return self._with_context(what, context)
+
+    def resolve_viz_type(self, config: Any) -> str:
+        return "pie"
+
+    def normalize_column_refs(self, config: Any, dataset_context: Any) -> Any:
+        config_dict = config.model_dump()

Review Comment:
   **Suggestion:** Add a docstring to this newly added method describing 
normalization steps, expected inputs, and the validated output object. 
[custom_rule]
   
   **Severity Level:** Minor ⚠️
   <details>
   <summary><b>Why it matters? 🤔 </b></summary>
   
   This is a newly added method without a docstring. The rule explicitly 
requires docstrings for newly added Python functions and classes, so the 
violation is real.
   </details>
   
   [![Fix in 
Cursor](https://new-codeant-butcket.s3.us-west-1.amazonaws.com/badges/fix-in-cursor-flat.svg)](https://app.codeant.ai/fix-in-ide?tool=cursor&prompt_id=82d7f7f300a04b2d8817d948a666b78d&service=github&base_url=https%3A%2F%2Fgithub.com&org=apache&repo=apache%2Fsuperset)
 [![Fix in VSCode 
Claude](https://new-codeant-butcket.s3.us-west-1.amazonaws.com/badges/fix-in-vscode-claude-flat.svg)](https://app.codeant.ai/fix-in-ide?tool=vscode-claude&prompt_id=82d7f7f300a04b2d8817d948a666b78d&service=github&base_url=https%3A%2F%2Fgithub.com&org=apache&repo=apache%2Fsuperset)
   
   *(Use Cmd/Ctrl + Click for best experience)*
   <details>
   <summary><b>Prompt for AI Agent 🤖 </b></summary>
   
   ```mdx
   This is a comment left during a code review.
   
   **Path:** superset/mcp_service/chart/plugins/pie.py
   **Line:** 97:98
   **Comment:**
        *Custom Rule: Add a docstring to this newly added method describing 
normalization steps, expected inputs, and the validated output object.
   
   Validate the correctness of the flagged issue. If correct, How can I resolve 
this? If you propose a fix, implement it and please make it concise.
   Once fix is implemented, also check other comments on the same PR, and ask 
user if the user wants to fix the rest of the comments as well. if said yes, 
then fetch all the comments validate the correctness and implement a minimal fix
   ```
   </details>
   <a 
href='https://app.codeant.ai/feedback?pr_url=https%3A%2F%2Fgithub.com%2Fapache%2Fsuperset%2Fpull%2F39922&comment_hash=c2281536d4fa3e3103854d71f8dd4e054492d084c4b7ce675be938d3f5f51e28&reaction=like'>👍</a>
 | <a 
href='https://app.codeant.ai/feedback?pr_url=https%3A%2F%2Fgithub.com%2Fapache%2Fsuperset%2Fpull%2F39922&comment_hash=c2281536d4fa3e3103854d71f8dd4e054492d084c4b7ce675be938d3f5f51e28&reaction=dislike'>👎</a>



##########
superset/mcp_service/chart/plugins/pie.py:
##########
@@ -0,0 +1,139 @@
+# Licensed to the Apache Software Foundation (ASF) under one
+# or more contributor license agreements.  See the NOTICE file
+# distributed with this work for additional information
+# regarding copyright ownership.  The ASF licenses this file
+# to you 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.
+
+"""Pie chart type plugin."""
+
+from __future__ import annotations
+
+from typing import Any
+
+from superset.mcp_service.chart.chart_utils import (
+    _pie_chart_what,
+    _summarize_filters,
+    map_pie_config,
+)
+from superset.mcp_service.chart.plugin import BaseChartPlugin
+from superset.mcp_service.chart.schemas import ColumnRef, PieChartConfig
+from superset.mcp_service.chart.validation.dataset_validator import 
DatasetValidator
+from superset.mcp_service.common.error_schemas import ChartGenerationError
+
+
+class PieChartPlugin(BaseChartPlugin):
+    """Plugin for pie chart type."""
+
+    chart_type = "pie"
+    display_name = "Pie / Donut Chart"
+    native_viz_types = {
+        "pie": "Pie Chart",
+    }
+
+    def pre_validate(
+        self,
+        config: dict[str, Any],
+    ) -> ChartGenerationError | None:
+        missing_fields = []
+
+        if "dimension" not in config and "groupby" not in config:
+            missing_fields.append("'dimension' (category column for slices)")
+        if "metric" not in config:
+            missing_fields.append("'metric' (value metric for slice sizes)")
+
+        if missing_fields:
+            return ChartGenerationError(
+                error_type="missing_pie_fields",
+                message=(
+                    f"Pie chart missing required fields: {', 
'.join(missing_fields)}"
+                ),
+                details=(
+                    "Pie charts require a dimension (categories) and a metric 
(values)"
+                ),
+                suggestions=[
+                    "Add 'dimension' field: {'name': 'category_column'}",
+                    "Add 'metric' field: {'name': 'value_column', 'aggregate': 
'SUM'}",
+                    "Example: {'chart_type': 'pie', 'dimension': {'name': 
'product'}, "
+                    "'metric': {'name': 'revenue', 'aggregate': 'SUM'}}",
+                ],
+                error_code="MISSING_PIE_FIELDS",
+            )
+
+        return None
+
+    def extract_column_refs(self, config: Any) -> list[ColumnRef]:
+        if not isinstance(config, PieChartConfig):
+            return []
+        refs: list[ColumnRef] = [config.dimension, config.metric]
+        if config.filters:
+            for f in config.filters:
+                refs.append(ColumnRef(name=f.column))
+        return refs
+
+    def to_form_data(
+        self, config: Any, dataset_id: int | str | None = None
+    ) -> dict[str, Any]:
+        return map_pie_config(config)
+
+    def generate_name(self, config: Any, dataset_name: str | None = None) -> 
str:
+        what = _pie_chart_what(config)
+        context = _summarize_filters(config.filters)
+        return self._with_context(what, context)
+
+    def resolve_viz_type(self, config: Any) -> str:
+        return "pie"
+
+    def normalize_column_refs(self, config: Any, dataset_context: Any) -> Any:
+        config_dict = config.model_dump()
+
+        if config_dict.get("dimension"):
+            config_dict["dimension"]["name"] = (
+                DatasetValidator._get_canonical_column_name(
+                    config_dict["dimension"]["name"], dataset_context
+                )
+            )
+        if config_dict.get("metric"):
+            if config_dict["metric"].get("sql_expression"):
+                pass
+            elif config_dict["metric"].get("saved_metric"):
+                config_dict["metric"]["name"] = (
+                    DatasetValidator._get_canonical_metric_name(
+                        config_dict["metric"]["name"], dataset_context
+                    )
+                )
+            else:
+                config_dict["metric"]["name"] = (
+                    DatasetValidator._get_canonical_column_name(
+                        config_dict["metric"]["name"], dataset_context
+                    )
+                )
+        DatasetValidator._normalize_filters(config_dict, dataset_context)
+        return PieChartConfig.model_validate(config_dict)
+
+    def schema_error_hint(self) -> ChartGenerationError | None:
+        return ChartGenerationError(

Review Comment:
   **Suggestion:** Add a docstring to this newly added method explaining when 
this error hint is used and what the returned structure represents. 
[custom_rule]
   
   **Severity Level:** Minor ⚠️
   <details>
   <summary><b>Why it matters? 🤔 </b></summary>
   
   The method is newly added and does not include a docstring. This matches the 
stated rule requiring documentation for newly added Python functions and 
classes.
   </details>
   
   [![Fix in 
Cursor](https://new-codeant-butcket.s3.us-west-1.amazonaws.com/badges/fix-in-cursor-flat.svg)](https://app.codeant.ai/fix-in-ide?tool=cursor&prompt_id=8f57bd54003544b0932cc33b6eb50f4d&service=github&base_url=https%3A%2F%2Fgithub.com&org=apache&repo=apache%2Fsuperset)
 [![Fix in VSCode 
Claude](https://new-codeant-butcket.s3.us-west-1.amazonaws.com/badges/fix-in-vscode-claude-flat.svg)](https://app.codeant.ai/fix-in-ide?tool=vscode-claude&prompt_id=8f57bd54003544b0932cc33b6eb50f4d&service=github&base_url=https%3A%2F%2Fgithub.com&org=apache&repo=apache%2Fsuperset)
   
   *(Use Cmd/Ctrl + Click for best experience)*
   <details>
   <summary><b>Prompt for AI Agent 🤖 </b></summary>
   
   ```mdx
   This is a comment left during a code review.
   
   **Path:** superset/mcp_service/chart/plugins/pie.py
   **Line:** 124:125
   **Comment:**
        *Custom Rule: Add a docstring to this newly added method explaining 
when this error hint is used and what the returned structure represents.
   
   Validate the correctness of the flagged issue. If correct, How can I resolve 
this? If you propose a fix, implement it and please make it concise.
   Once fix is implemented, also check other comments on the same PR, and ask 
user if the user wants to fix the rest of the comments as well. if said yes, 
then fetch all the comments validate the correctness and implement a minimal fix
   ```
   </details>
   <a 
href='https://app.codeant.ai/feedback?pr_url=https%3A%2F%2Fgithub.com%2Fapache%2Fsuperset%2Fpull%2F39922&comment_hash=f5abf87c78612113a3dbec881ada1ca6ee26a28a17e1fe4a2a7610f4b6741cbf&reaction=like'>👍</a>
 | <a 
href='https://app.codeant.ai/feedback?pr_url=https%3A%2F%2Fgithub.com%2Fapache%2Fsuperset%2Fpull%2F39922&comment_hash=f5abf87c78612113a3dbec881ada1ca6ee26a28a17e1fe4a2a7610f4b6741cbf&reaction=dislike'>👎</a>



##########
superset/mcp_service/chart/plugins/table.py:
##########
@@ -0,0 +1,135 @@
+# Licensed to the Apache Software Foundation (ASF) under one
+# or more contributor license agreements.  See the NOTICE file
+# distributed with this work for additional information
+# regarding copyright ownership.  The ASF licenses this file
+# to you 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.
+
+"""Table chart type plugin."""
+
+from __future__ import annotations
+
+from typing import Any
+
+from superset.mcp_service.chart.chart_utils import (
+    _summarize_filters,
+    _table_chart_what,
+    map_table_config,
+)
+from superset.mcp_service.chart.plugin import BaseChartPlugin
+from superset.mcp_service.chart.schemas import ColumnRef, TableChartConfig
+from superset.mcp_service.chart.validation.dataset_validator import 
DatasetValidator
+from superset.mcp_service.common.error_schemas import ChartGenerationError
+
+
+class TableChartPlugin(BaseChartPlugin):
+    """Plugin for table chart type."""
+
+    chart_type = "table"
+    display_name = "Table"
+    native_viz_types = {
+        "table": "Table",
+        "ag-grid-table": "Interactive Table",
+    }
+
+    def pre_validate(
+        self,
+        config: dict[str, Any],
+    ) -> ChartGenerationError | None:
+        columns = (
+            config.get("columns") or config.get("all_columns") or 
config.get("groupby")
+        )
+        if not columns:
+            return ChartGenerationError(
+                error_type="missing_columns",
+                message="Table chart missing required field: columns",
+                details=(
+                    "Table charts require a 'columns' array to specify which "
+                    "columns to display"
+                ),
+                suggestions=[
+                    "Add 'columns' field with array of column specifications",
+                    "Example: 'columns': [{'name': 'product'}, {'name': 
'sales', "
+                    "'aggregate': 'SUM'}]",
+                    "Each column can have optional 'aggregate' for metrics",
+                ],
+                error_code="MISSING_COLUMNS",
+            )
+
+        if not isinstance(columns, list):
+            return ChartGenerationError(
+                error_type="invalid_columns_format",
+                message="Columns must be a list",
+                details="The 'columns' field must be an array of column 
specifications",
+                suggestions=[
+                    "Ensure columns is an array: 'columns': [...]",
+                    "Each column should be an object with 'name' field",
+                ],
+                error_code="INVALID_COLUMNS_FORMAT",
+            )
+
+        return None
+
+    def extract_column_refs(self, config: Any) -> list[ColumnRef]:
+        if not isinstance(config, TableChartConfig):
+            return []
+        refs: list[ColumnRef] = list(config.columns)
+        if config.filters:
+            for f in config.filters:
+                refs.append(ColumnRef(name=f.column))
+        return refs
+
+    def to_form_data(
+        self, config: Any, dataset_id: int | str | None = None
+    ) -> dict[str, Any]:
+        return map_table_config(config)
+
+    def generate_name(self, config: Any, dataset_name: str | None = None) -> 
str:
+        what = _table_chart_what(config, dataset_name)
+        context = _summarize_filters(config.filters)

Review Comment:
   **Suggestion:** Add a method docstring describing how the generated chart 
name is derived from chart intent and filter context. [custom_rule]
   
   **Severity Level:** Minor ⚠️
   <details>
   <summary><b>Why it matters? 🤔 </b></summary>
   
   This newly added method has no docstring. Since the rule says new Python 
functions should include docstrings, the suggestion is valid and matches an 
actual violation.
   </details>
   
   [![Fix in 
Cursor](https://new-codeant-butcket.s3.us-west-1.amazonaws.com/badges/fix-in-cursor-flat.svg)](https://app.codeant.ai/fix-in-ide?tool=cursor&prompt_id=2718382e48ba4cee8e8a791fd421ccea&service=github&base_url=https%3A%2F%2Fgithub.com&org=apache&repo=apache%2Fsuperset)
 [![Fix in VSCode 
Claude](https://new-codeant-butcket.s3.us-west-1.amazonaws.com/badges/fix-in-vscode-claude-flat.svg)](https://app.codeant.ai/fix-in-ide?tool=vscode-claude&prompt_id=2718382e48ba4cee8e8a791fd421ccea&service=github&base_url=https%3A%2F%2Fgithub.com&org=apache&repo=apache%2Fsuperset)
   
   *(Use Cmd/Ctrl + Click for best experience)*
   <details>
   <summary><b>Prompt for AI Agent 🤖 </b></summary>
   
   ```mdx
   This is a comment left during a code review.
   
   **Path:** superset/mcp_service/chart/plugins/table.py
   **Line:** 97:99
   **Comment:**
        *Custom Rule: Add a method docstring describing how the generated chart 
name is derived from chart intent and filter context.
   
   Validate the correctness of the flagged issue. If correct, How can I resolve 
this? If you propose a fix, implement it and please make it concise.
   Once fix is implemented, also check other comments on the same PR, and ask 
user if the user wants to fix the rest of the comments as well. if said yes, 
then fetch all the comments validate the correctness and implement a minimal fix
   ```
   </details>
   <a 
href='https://app.codeant.ai/feedback?pr_url=https%3A%2F%2Fgithub.com%2Fapache%2Fsuperset%2Fpull%2F39922&comment_hash=65892303a757db730736190e43002ffccec7a9f5aca522b19c99c7ec4da403b4&reaction=like'>👍</a>
 | <a 
href='https://app.codeant.ai/feedback?pr_url=https%3A%2F%2Fgithub.com%2Fapache%2Fsuperset%2Fpull%2F39922&comment_hash=65892303a757db730736190e43002ffccec7a9f5aca522b19c99c7ec4da403b4&reaction=dislike'>👎</a>



##########
superset/mcp_service/chart/plugins/pivot_table.py:
##########
@@ -0,0 +1,163 @@
+# Licensed to the Apache Software Foundation (ASF) under one
+# or more contributor license agreements.  See the NOTICE file
+# distributed with this work for additional information
+# regarding copyright ownership.  The ASF licenses this file
+# to you 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.
+
+"""Pivot table chart type plugin."""
+
+from __future__ import annotations
+
+from typing import Any
+
+from superset.mcp_service.chart.chart_utils import (
+    _pivot_table_what,
+    _summarize_filters,
+    map_pivot_table_config,
+)
+from superset.mcp_service.chart.plugin import BaseChartPlugin
+from superset.mcp_service.chart.schemas import ColumnRef, PivotTableChartConfig
+from superset.mcp_service.chart.validation.dataset_validator import 
DatasetValidator
+from superset.mcp_service.common.error_schemas import ChartGenerationError
+
+
+class PivotTableChartPlugin(BaseChartPlugin):
+    """Plugin for pivot_table chart type."""
+
+    chart_type = "pivot_table"
+    display_name = "Pivot Table"
+    native_viz_types = {
+        "pivot_table_v2": "Pivot Table",
+    }
+
+    def pre_validate(
+        self,
+        config: dict[str, Any],
+    ) -> ChartGenerationError | None:
+        missing_fields = []
+
+        if not (config.get("rows") or config.get("groupby") or 
config.get("dimension")):
+            missing_fields.append("'rows' (row grouping columns)")
+        if not config.get("metrics"):
+            missing_fields.append("'metrics' (aggregation metrics)")
+
+        if missing_fields:
+            return ChartGenerationError(
+                error_type="missing_pivot_fields",
+                message=(
+                    f"Pivot table missing required fields: {', 
'.join(missing_fields)}"
+                ),
+                details="Pivot tables require row groupings and metrics",
+                suggestions=[
+                    "Add 'rows' field: [{'name': 'category'}]",
+                    "Add 'metrics' field: [{'name': 'sales', 'aggregate': 
'SUM'}]",
+                    "Optional 'columns' for cross-tabulation: [{'name': 
'region'}]",
+                ],
+                error_code="MISSING_PIVOT_FIELDS",
+            )
+
+        rows_val = (
+            config.get("rows") or config.get("groupby") or 
config.get("dimension") or []
+        )
+        if not isinstance(rows_val, list):
+            return ChartGenerationError(
+                error_type="invalid_rows_format",
+                message="Rows must be a list of columns",
+                details="The 'rows' field must be an array of column 
specifications",
+                suggestions=[
+                    "Wrap row columns in array: 'rows': [{'name': 
'category'}]",
+                ],
+                error_code="INVALID_ROWS_FORMAT",
+            )
+
+        if not isinstance(config.get("metrics", []), list):
+            return ChartGenerationError(
+                error_type="invalid_metrics_format",
+                message="Metrics must be a list",
+                details="The 'metrics' field must be an array of metric 
specifications",
+                suggestions=[
+                    "Wrap metrics in array: 'metrics': [{'name': 'sales', "
+                    "'aggregate': 'SUM'}]",
+                ],
+                error_code="INVALID_METRICS_FORMAT",
+            )
+
+        return None
+
+    def extract_column_refs(self, config: Any) -> list[ColumnRef]:
+        if not isinstance(config, PivotTableChartConfig):
+            return []
+        refs: list[ColumnRef] = list(config.rows)
+        refs.extend(config.metrics)
+        if config.columns:
+            refs.extend(config.columns)
+        if config.filters:
+            for f in config.filters:
+                refs.append(ColumnRef(name=f.column))
+        return refs
+
+    def to_form_data(
+        self, config: Any, dataset_id: int | str | None = None
+    ) -> dict[str, Any]:
+        return map_pivot_table_config(config)
+
+    def generate_name(self, config: Any, dataset_name: str | None = None) -> 
str:
+        what = _pivot_table_what(config)
+        context = _summarize_filters(config.filters)
+        return self._with_context(what, context)

Review Comment:
   **Suggestion:** Add a docstring to this new naming method to describe how 
the chart title is derived from aggregation context and filters. [custom_rule]
   
   **Severity Level:** Minor ⚠️
   <details>
   <summary><b>Why it matters? 🤔 </b></summary>
   
   This newly added method lacks a docstring in the final file state. Since the 
rule explicitly requires docstrings for newly added Python functions and 
classes, this is a genuine violation.
   </details>
   
   [![Fix in 
Cursor](https://new-codeant-butcket.s3.us-west-1.amazonaws.com/badges/fix-in-cursor-flat.svg)](https://app.codeant.ai/fix-in-ide?tool=cursor&prompt_id=b8cdfe454fac4d9fa428c6a8cd704fa3&service=github&base_url=https%3A%2F%2Fgithub.com&org=apache&repo=apache%2Fsuperset)
 [![Fix in VSCode 
Claude](https://new-codeant-butcket.s3.us-west-1.amazonaws.com/badges/fix-in-vscode-claude-flat.svg)](https://app.codeant.ai/fix-in-ide?tool=vscode-claude&prompt_id=b8cdfe454fac4d9fa428c6a8cd704fa3&service=github&base_url=https%3A%2F%2Fgithub.com&org=apache&repo=apache%2Fsuperset)
   
   *(Use Cmd/Ctrl + Click for best experience)*
   <details>
   <summary><b>Prompt for AI Agent 🤖 </b></summary>
   
   ```mdx
   This is a comment left during a code review.
   
   **Path:** superset/mcp_service/chart/plugins/pivot_table.py
   **Line:** 115:118
   **Comment:**
        *Custom Rule: Add a docstring to this new naming method to describe how 
the chart title is derived from aggregation context and filters.
   
   Validate the correctness of the flagged issue. If correct, How can I resolve 
this? If you propose a fix, implement it and please make it concise.
   Once fix is implemented, also check other comments on the same PR, and ask 
user if the user wants to fix the rest of the comments as well. if said yes, 
then fetch all the comments validate the correctness and implement a minimal fix
   ```
   </details>
   <a 
href='https://app.codeant.ai/feedback?pr_url=https%3A%2F%2Fgithub.com%2Fapache%2Fsuperset%2Fpull%2F39922&comment_hash=c3bced350dd7cdaba73005078ef89ab36705ecc52f43f89a231de0d1b7064997&reaction=like'>👍</a>
 | <a 
href='https://app.codeant.ai/feedback?pr_url=https%3A%2F%2Fgithub.com%2Fapache%2Fsuperset%2Fpull%2F39922&comment_hash=c3bced350dd7cdaba73005078ef89ab36705ecc52f43f89a231de0d1b7064997&reaction=dislike'>👎</a>



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