diff --git a/.aida/validation_policy.yaml b/.aida/validation_policy.yaml
index 9bd144a71..6c21cf595 100644
--- a/.aida/validation_policy.yaml
+++ b/.aida/validation_policy.yaml
@@ -2,7 +2,6 @@
 # AIDA validation policy
 #
 # This file wires domains -> pipelines -> steps (command_id + processor_id).
-# Initially empty (validate may no-op until you configure routes).
 version: 1
 validation_policy:
   codegen:
@@ -26,22 +25,16 @@ validation_policy:
   pipelines:
     package-fast:
       steps:
-      - command_id: package-lint
-        processor_id: passthrough
-      - command_id: package-type-check
-        processor_id: passthrough
-      - command_id: package-test-py314
-        processor_id: pytest
+      - command_id: package-validate
+        processor_id: external_json
+    repo-fast:
+      steps:
+      - command_id: package-validate-no-tests
+        processor_id: external_json
     api-client-fast:
       steps:
       - command_id: api-client-tests
         processor_id: pytest
-    repo-fast:
-      steps:
-      - command_id: workspace-lint
-        processor_id: passthrough
-      - command_id: workspace-type-check
-        processor_id: passthrough
     aida-config:
       steps:
       - command_id: aida-doctor
diff --git a/.aida/validation_registry.yaml b/.aida/validation_registry.yaml
index 84bd97d18..a2fa3b8c6 100644
--- a/.aida/validation_registry.yaml
+++ b/.aida/validation_registry.yaml
@@ -6,39 +6,36 @@ version: 1
 registry:
   includes: []
   commands:
-    package-lint:
+    package-validate:
       argv:
-      - make
-      - -C
-      - '{root}'
-      - lint
+      - bash
+      - '{workspace_root}/scripts/validate_python.sh'
+      - --project-path
+      - '{workspace_root}/{root}'
+      - --workspace-root
+      - '{workspace_root}'
+      - --scope
+      - '{scope}'
+      - --auto-fix
+      - "true"
       cwd: '{workspace_root}'
-    package-type-check:
+      timeout_sec: 900
+    package-validate-no-tests:
       argv:
-      - make
-      - -C
-      - '{root}'
-      - type-check
-      cwd: '{workspace_root}'
-    package-test-py314:
-      argv:
-      - make
-      - -C
-      - '{root}'
-      - test
-      cwd: '{workspace_root}'
-      env:
-        TEST_ENVS: py314
-    workspace-lint:
-      argv:
-      - make
-      - lint
-      cwd: '{workspace_root}'
-    workspace-type-check:
-      argv:
-      - make
-      - type-check
+      - bash
+      - '{workspace_root}/scripts/validate_python.sh'
+      - --project-path
+      - '{workspace_root}/{root}'
+      - --workspace-root
+      - '{workspace_root}'
+      - --scope
+      - '{scope}'
+      - --auto-fix
+      - "true"
+      - --steps-csv
+      - format,lint,types
       cwd: '{workspace_root}'
+      timeout_sec: 600
     api-client-tests:
       argv:
       - uv
@@ -52,10 +49,4 @@ registry:
       - aida-mcp
       - doctor
       cwd: '{workspace_root}'
-  processors:
-    passthrough:
-      kind: builtin
-      builtin_id: passthrough
-    pytest:
-      kind: builtin
-      builtin_id: pytest
+  processors: {}
diff --git a/packages/gooddata-sdk/pyproject.toml b/packages/gooddata-sdk/pyproject.toml
index a30da72b7..2ea9efb68 100644
--- a/packages/gooddata-sdk/pyproject.toml
+++ b/packages/gooddata-sdk/pyproject.toml
@@ -34,6 +34,7 @@ dependencies = [
     "brotli==1.2.0",
     "requests~=2.32.0",
     "python-dotenv>=1.0.0,<2.0.0",
+    "gooddata-code-convertors",
 ]
 classifiers = [
     "Development Status :: 5 - Production/Stable",
@@ -75,9 +76,6 @@ allowed-unresolved-imports = ["gooddata_api_client.**"]
 
 [tool.hatch.build.targets.wheel]
 packages = ["src/gooddata_sdk"]
-include = [
-    "src/gooddata_sdk/cli/package.json",
-]
 
 [tool.coverage.run]
 source = ["gooddata_sdk"]
diff --git a/packages/gooddata-sdk/src/gooddata_sdk/__init__.py b/packages/gooddata-sdk/src/gooddata_sdk/__init__.py
index 75175e0af..77397b92d 100644
--- a/packages/gooddata-sdk/src/gooddata_sdk/__init__.py
+++ b/packages/gooddata-sdk/src/gooddata_sdk/__init__.py
@@ -180,6 +180,25 @@
     CatalogWorkspacePermissionAssignment,
 )
 from gooddata_sdk.catalog.validate_by_item import CatalogValidateByItem
+from gooddata_sdk.catalog.workspace.aac import (
+    aac_attribute_hierarchy_to_declarative,
+    aac_dashboard_to_declarative,
+    aac_dataset_to_declarative,
+    aac_date_dataset_to_declarative,
+    aac_metric_to_declarative,
+    aac_plugin_to_declarative,
+    aac_visualization_to_declarative,
+    declarative_attribute_hierarchy_to_aac,
+    declarative_dashboard_to_aac,
+    declarative_dataset_to_aac,
+    declarative_date_instance_to_aac,
+    declarative_metric_to_aac,
+    declarative_plugin_to_aac,
+    declarative_visualization_to_aac,
+    detect_yaml_format,
+    load_aac_workspace_from_disk,
+    store_aac_workspace_to_disk,
+)
 from gooddata_sdk.catalog.workspace.content_service import CatalogWorkspaceContent, CatalogWorkspaceContentService
 from gooddata_sdk.catalog.workspace.declarative_model.workspace.analytics_model.analytics_model import (
     CatalogDeclarativeAnalytics,
diff --git a/packages/gooddata-sdk/src/gooddata_sdk/catalog/workspace/aac.py b/packages/gooddata-sdk/src/gooddata_sdk/catalog/workspace/aac.py
new file mode 100644
index 000000000..59eeffc64
--- /dev/null
+++ b/packages/gooddata-sdk/src/gooddata_sdk/catalog/workspace/aac.py
@@ -0,0 +1,407 @@
+# (C) 2026 GoodData Corporation
+from __future__ import annotations
+
+from pathlib import Path
+from typing import Any, Literal
+
+from gooddata_code_convertors import (
+    declarative_attribute_hierarchy_to_yaml,
+    declarative_dashboard_to_yaml,
+    declarative_dataset_to_yaml,
+    declarative_date_instance_to_yaml,
+    declarative_metric_to_yaml,
+    declarative_plugin_to_yaml,
+    declarative_visualisation_to_yaml,
+    yaml_attribute_hierarchy_to_declarative,
+    yaml_dashboard_to_declarative,
+    yaml_dataset_to_declarative,
+    yaml_date_dataset_to_declarative,
+    yaml_metric_to_declarative,
+    yaml_plugin_to_declarative,
+    yaml_visualisation_to_declarative,
+)
+
+from gooddata_sdk.catalog.workspace.declarative_model.workspace.workspace import CatalogDeclarativeWorkspaceModel
+from gooddata_sdk.utils import read_layout_from_file
+
+# AAC types that map to visualization objects (all go through yaml_visualisation_to_declarative)
+_VISUALIZATION_TYPES = frozenset(
+    {
+        "bar_chart",
+        "column_chart",
+        "line_chart",
+        "area_chart",
+        "pie_chart",
+        "donut_chart",
+        "scatter_chart",
+        "bubble_chart",
+        "heatmap_chart",
+        "treemap_chart",
+        "bullet_chart",
+        "funnel_chart",
+        "pyramid_chart",
+        "waterfall_chart",
+        "sankey_chart",
+        "dependency_wheel_chart",
+        "combo_chart",
+        "headline_chart",
+        "geo_chart",
+        "geo_area_chart",
+        "repeater_chart",
+        "table",
+    }
+)
+
+# All known AAC type values
+_ALL_AAC_TYPES = (
+    frozenset({"dataset", "date", "metric", "dashboard", "plugin", "attribute_hierarchy"}) | _VISUALIZATION_TYPES
+)
+
+# Types that are "dataset-like" for the entities array
+_DATASET_TYPES = frozenset({"dataset", "date"})
+
+
+# ---------------------------------------------------------------------------
+# Entities list builder (needed for cross-reference resolution)
+# ---------------------------------------------------------------------------
+
+
+def _build_entities(aac_objects: list[dict[str, Any]]) -> list[dict[str, Any]]:
+    """Build the entities array expected by convertor functions.
+
+    Some convertor functions (dataset, visualization, dashboard) need access to
+    all objects for cross-reference resolution (e.g., dataset references).
+    """
+    return [
+        {
+            "id": obj["id"],
+            "type": obj["type"],
+            "path": f"{obj['id']}.yaml",
+            "data": obj,
+        }
+        for obj in aac_objects
+    ]
+
+
+# ---------------------------------------------------------------------------
+# Individual object conversions: AAC dict → Declarative dict
+# ---------------------------------------------------------------------------
+
+
+def aac_dataset_to_declarative(
+    aac: dict[str, Any],
+    entities: list[dict[str, Any]] | None = None,
+    data_source_id: str | None = None,
+) -> dict[str, Any]:
+    """Convert an AAC dataset dict to declarative format.
+
+    Args:
+        aac: The AAC dataset dict (parsed YAML).
+        entities: Optional list of all AAC objects for cross-reference resolution.
+        data_source_id: Optional data source ID for table-based datasets.
+    """
+    ent = entities if entities is not None else _build_entities([aac])
+    args: list[Any] = [ent, aac]
+    if data_source_id is not None:
+        args.append(data_source_id)
+    return yaml_dataset_to_declarative(*args)
+
+
+def aac_date_dataset_to_declarative(aac: dict[str, Any]) -> dict[str, Any]:
+    """Convert an AAC date dataset dict to declarative format."""
+    return yaml_date_dataset_to_declarative(aac)
+
+
+def aac_metric_to_declarative(aac: dict[str, Any]) -> dict[str, Any]:
+    """Convert an AAC metric dict to declarative format."""
+    return yaml_metric_to_declarative(aac)
+
+
+def aac_visualization_to_declarative(
+    aac: dict[str, Any],
+    entities: list[dict[str, Any]] | None = None,
+) -> dict[str, Any]:
+    """Convert an AAC visualization dict to declarative format.
+
+    Args:
+        aac: The AAC visualization dict (parsed YAML).
+        entities: Optional list of all AAC objects for cross-reference resolution.
+    """
+    ent = entities if entities is not None else _build_entities([aac])
+    return yaml_visualisation_to_declarative(ent, aac)
+
+
+def aac_dashboard_to_declarative(
+    aac: dict[str, Any],
+    entities: list[dict[str, Any]] | None = None,
+) -> dict[str, Any]:
+    """Convert an AAC dashboard dict to declarative format.
+
+    Args:
+        aac: The AAC dashboard dict (parsed YAML).
+        entities: Optional list of all AAC objects for cross-reference resolution.
+    """
+    ent = entities if entities is not None else _build_entities([aac])
+    return yaml_dashboard_to_declarative(ent, aac)
+
+
+def aac_plugin_to_declarative(aac: dict[str, Any]) -> dict[str, Any]:
+    """Convert an AAC plugin dict to declarative format."""
+    return yaml_plugin_to_declarative(aac)
+
+
+def aac_attribute_hierarchy_to_declarative(aac: dict[str, Any]) -> dict[str, Any]:
+    """Convert an AAC attribute hierarchy dict to declarative format."""
+    return yaml_attribute_hierarchy_to_declarative(aac)
+
+
+# ---------------------------------------------------------------------------
+# Individual object conversions: Declarative dict → AAC dict
+# Returns {"json": dict, "content": str}
+# ---------------------------------------------------------------------------
+
+
+def declarative_dataset_to_aac(
+    declarative: dict[str, Any],
+    profile: dict[str, Any] | None = None,
+    tables_map: dict[str, list[dict[str, Any]]] | None = None,
+) -> dict[str, Any]:
+    """Convert a declarative dataset dict to AAC format.
+
+    Args:
+        declarative: The declarative dataset dict.
+        profile: Optional profile dict with host, token, workspace_id, data_source.
+        tables_map: Optional mapping of data source ID to list of table definitions.
+    """
+    p = profile if profile is not None else {}
+    t = tables_map if tables_map is not None else {}
+    return declarative_dataset_to_yaml(declarative, p, t)
+
+
+def declarative_date_instance_to_aac(declarative: dict[str, Any]) -> dict[str, Any]:
+    """Convert a declarative date instance dict to AAC format."""
+    return declarative_date_instance_to_yaml(declarative)
+
+
+def declarative_metric_to_aac(declarative: dict[str, Any]) -> dict[str, Any]:
+    """Convert a declarative metric dict to AAC format."""
+    return declarative_metric_to_yaml(declarative)
+
+
+def declarative_visualization_to_aac(declarative: dict[str, Any]) -> dict[str, Any]:
+    """Convert a declarative visualization dict to AAC format."""
+    return declarative_visualisation_to_yaml(declarative)
+
+
+def declarative_dashboard_to_aac(declarative: dict[str, Any]) -> dict[str, Any]:
+    """Convert a declarative dashboard dict to AAC format."""
+    return declarative_dashboard_to_yaml(declarative)
+
+
+def declarative_plugin_to_aac(declarative: dict[str, Any]) -> dict[str, Any]:
+    """Convert a declarative plugin dict to AAC format."""
+    return declarative_plugin_to_yaml(declarative)
+
+
+def declarative_attribute_hierarchy_to_aac(declarative: dict[str, Any]) -> dict[str, Any]:
+    """Convert a declarative attribute hierarchy dict to AAC format."""
+    return declarative_attribute_hierarchy_to_yaml(declarative)
+
+
+# ---------------------------------------------------------------------------
+# Format detection
+# ---------------------------------------------------------------------------
+
+
+def detect_yaml_format(path: Path) -> Literal["aac", "declarative"]:
+    """Detect whether a directory contains AAC or declarative YAMLs.
+
+    AAC files have a top-level 'type' field (dataset, metric, line_chart, etc.)
+    and live as flat files or in typed subdirectories (datasets/, metrics/, etc.).
+
+    Declarative files follow a nested folder structure with
+    workspaces/<id>/ldm/ and workspaces/<id>/analytics_model/.
+    """
+    # Check for declarative structure markers
+    if (path / "workspaces").is_dir() or (path / "ldm").is_dir() or (path / "analytics_model").is_dir():
+        return "declarative"
+
+    # Check for AAC markers: typed subdirectories
+    aac_subdirs = {"datasets", "metrics", "visualisations", "dashboards", "plugins", "attributeHierarchies"}
+    for subdir in aac_subdirs:
+        if (path / subdir).is_dir():
+            return "aac"
+
+    # Check YAML files for top-level 'type' field
+    for yaml_file in path.glob("*.yaml"):
+        content = read_layout_from_file(yaml_file)
+        if isinstance(content, dict) and content.get("type") in _ALL_AAC_TYPES:
+            return "aac"
+        break  # Only check the first file
+
+    return "declarative"
+
+
+# ---------------------------------------------------------------------------
+# Workspace-level: load AAC from disk → CatalogDeclarativeWorkspaceModel
+# ---------------------------------------------------------------------------
+
+
+def _collect_aac_yaml_files(source_dir: Path) -> list[Path]:
+    """Collect all AAC YAML files from source_dir (flat and typed subdirs)."""
+    files: list[Path] = []
+
+    # Flat YAML files in source_dir root
+    files.extend(sorted(source_dir.glob("*.yaml")))
+    files.extend(sorted(source_dir.glob("*.yml")))
+
+    # Typed subdirectories used by gd CLI
+    for subdir in sorted(source_dir.iterdir()):
+        if subdir.is_dir() and subdir.name not in {
+            "data_sources",
+            "users",
+            "user_groups",
+            "workspaces_data_filters",
+            "workspaces",
+        }:
+            files.extend(sorted(subdir.rglob("*.yaml")))
+            files.extend(sorted(subdir.rglob("*.yml")))
+
+    return files
+
+
+def load_aac_workspace_from_disk(
+    source_dir: Path,
+    data_source_id: str | None = None,
+) -> CatalogDeclarativeWorkspaceModel:
+    """Load AAC YAML files from source_dir and return a declarative workspace model.
+
+    Reads all .yaml/.yml files, detects object type from the 'type' field,
+    converts each to declarative format, and assembles into a
+    CatalogDeclarativeWorkspaceModel.
+
+    Args:
+        source_dir: Path to directory containing AAC YAML files.
+        data_source_id: Optional data source ID for table-based datasets.
+    """
+    # First pass: read all AAC objects and build entities list
+    aac_objects: list[dict[str, Any]] = []
+    for yaml_file in _collect_aac_yaml_files(source_dir):
+        content = read_layout_from_file(yaml_file)
+        if isinstance(content, dict) and "type" in content:
+            aac_objects.append(content)
+
+    entities = _build_entities(aac_objects)
+
+    # Second pass: convert each object
+    datasets: list[dict[str, Any]] = []
+    date_instances: list[dict[str, Any]] = []
+    metrics: list[dict[str, Any]] = []
+    visualization_objects: list[dict[str, Any]] = []
+    analytical_dashboards: list[dict[str, Any]] = []
+    dashboard_plugins: list[dict[str, Any]] = []
+    attribute_hierarchies: list[dict[str, Any]] = []
+
+    for aac in aac_objects:
+        aac_type = aac.get("type")
+
+        match aac_type:
+            case "dataset":
+                datasets.append(aac_dataset_to_declarative(aac, entities, data_source_id))
+            case "date":
+                date_instances.append(aac_date_dataset_to_declarative(aac))
+            case "metric":
+                metrics.append(aac_metric_to_declarative(aac))
+            case "dashboard":
+                result = aac_dashboard_to_declarative(aac, entities)
+                # Dashboard convertor may return dashboard + filterContext
+                if isinstance(result, dict) and "dashboard" in result:
+                    analytical_dashboards.append(result["dashboard"])
+                else:
+                    analytical_dashboards.append(result)
+            case "plugin":
+                dashboard_plugins.append(aac_plugin_to_declarative(aac))
+            case "attribute_hierarchy":
+                attribute_hierarchies.append(aac_attribute_hierarchy_to_declarative(aac))
+            case vis_type if vis_type in _VISUALIZATION_TYPES:
+                visualization_objects.append(aac_visualization_to_declarative(aac, entities))
+
+    workspace_model_dict: dict[str, Any] = {}
+
+    ldm: dict[str, Any] = {}
+    if datasets:
+        ldm["datasets"] = datasets
+    if date_instances:
+        ldm["dateInstances"] = date_instances
+    if ldm:
+        workspace_model_dict["ldm"] = ldm
+
+    analytics: dict[str, Any] = {}
+    if metrics:
+        analytics["metrics"] = metrics
+    if visualization_objects:
+        analytics["visualizationObjects"] = visualization_objects
+    if analytical_dashboards:
+        analytics["analyticalDashboards"] = analytical_dashboards
+    if dashboard_plugins:
+        analytics["dashboardPlugins"] = dashboard_plugins
+    if attribute_hierarchies:
+        analytics["attributeHierarchyObjects"] = attribute_hierarchies
+    if analytics:
+        workspace_model_dict["analytics"] = analytics
+
+    return CatalogDeclarativeWorkspaceModel.from_dict(workspace_model_dict)
+
+
+# ---------------------------------------------------------------------------
+# Workspace-level: CatalogDeclarativeWorkspaceModel → AAC files on disk
+# ---------------------------------------------------------------------------
+
+
+def _write_aac_file(source_dir: Path, subdir: str, obj_id: str, content: str) -> None:
+    """Write a single AAC YAML file to disk."""
+    target_dir = source_dir / subdir
+    target_dir.mkdir(parents=True, exist_ok=True)
+    target_file = target_dir / f"{obj_id}.yaml"
+    target_file.write_text(content, encoding="utf-8")
+
+
+def store_aac_workspace_to_disk(model: CatalogDeclarativeWorkspaceModel, source_dir: Path) -> None:
+    """Convert a declarative workspace model to AAC YAML files and write to disk.
+
+    Creates typed subdirectories (datasets/, metrics/, visualisations/, dashboards/,
+    plugins/, attributeHierarchies/) under source_dir.
+    """
+    source_dir.mkdir(parents=True, exist_ok=True)
+    model_dict = model.to_dict(camel_case=True)
+
+    ldm = model_dict.get("ldm", {})
+    analytics = model_dict.get("analytics", {})
+
+    for dataset in ldm.get("datasets", []):
+        result = declarative_dataset_to_aac(dataset)
+        _write_aac_file(source_dir, "datasets", dataset["id"], result["content"])
+
+    for date_instance in ldm.get("dateInstances", []):
+        result = declarative_date_instance_to_aac(date_instance)
+        _write_aac_file(source_dir, "datasets", date_instance["id"], result["content"])
+
+    for metric in analytics.get("metrics", []):
+        result = declarative_metric_to_aac(metric)
+        _write_aac_file(source_dir, "metrics", metric["id"], result["content"])
+
+    for vis in analytics.get("visualizationObjects", []):
+        result = declarative_visualization_to_aac(vis)
+        _write_aac_file(source_dir, "visualisations", vis["id"], result["content"])
+
+    for dashboard in analytics.get("analyticalDashboards", []):
+        result = declarative_dashboard_to_aac(dashboard)
+        _write_aac_file(source_dir, "dashboards", dashboard["id"], result["content"])
+
+    for plugin in analytics.get("dashboardPlugins", []):
+        result = declarative_plugin_to_aac(plugin)
+        _write_aac_file(source_dir, "plugins", plugin["id"], result["content"])
+
+    for hierarchy in analytics.get("attributeHierarchyObjects", []):
+        result = declarative_attribute_hierarchy_to_aac(hierarchy)
+        _write_aac_file(source_dir, "attributeHierarchies", hierarchy["id"], result["content"])
diff --git a/packages/gooddata-sdk/src/gooddata_sdk/catalog/workspace/service.py b/packages/gooddata-sdk/src/gooddata_sdk/catalog/workspace/service.py
index 50f5f113e..6378ebb34 100644
--- a/packages/gooddata-sdk/src/gooddata_sdk/catalog/workspace/service.py
+++ b/packages/gooddata-sdk/src/gooddata_sdk/catalog/workspace/service.py
@@ -20,6 +20,7 @@
 from gooddata_sdk import CatalogDeclarativeAutomation
 from gooddata_sdk.catalog.catalog_service_base import CatalogServiceBase
 from gooddata_sdk.catalog.permission.service import CatalogPermissionService
+from gooddata_sdk.catalog.workspace.aac import load_aac_workspace_from_disk, store_aac_workspace_to_disk
 from gooddata_sdk.catalog.workspace.declarative_model.workspace.workspace import (
     CatalogDeclarativeFilterView,
     CatalogDeclarativeUserDataFilters,
@@ -417,6 +418,32 @@ def load_and_put_declarative_workspace(self, workspace_id: str, layout_root_path
         )
         self.put_declarative_workspace(workspace_id=workspace_id, workspace=declarative_workspace)
 
+    # AAC (Analytics-as-Code) methods
+
+    def load_and_put_aac_workspace(self, workspace_id: str, source_dir: Path) -> None:
+        """Load AAC YAML files from source_dir, convert to declarative, and deploy to workspace.
+
+        Args:
+            workspace_id (str):
+                Workspace identification string e.g. "demo"
+            source_dir (Path):
+                Path to the directory containing AAC YAML files.
+        """
+        workspace_model = load_aac_workspace_from_disk(source_dir)
+        self.put_declarative_workspace(workspace_id=workspace_id, workspace=workspace_model)
+
+    def get_and_store_aac_workspace(self, workspace_id: str, source_dir: Path) -> None:
+        """Get declarative workspace from server, convert to AAC YAML files, and write to disk.
+
+        Args:
+            workspace_id (str):
+                Workspace identification string e.g. "demo"
+            source_dir (Path):
+                Path to the directory where AAC YAML files will be written.
+        """
+        workspace_model = self.get_declarative_workspace(workspace_id=workspace_id)
+        store_aac_workspace_to_disk(workspace_model, source_dir)
+
     def clone_workspace(
         self,
         source_workspace_id: str,
diff --git a/packages/gooddata-sdk/src/gooddata_sdk/cli/clone.py b/packages/gooddata-sdk/src/gooddata_sdk/cli/clone.py
index a2fbb2292..2234e7203 100644
--- a/packages/gooddata-sdk/src/gooddata_sdk/cli/clone.py
+++ b/packages/gooddata-sdk/src/gooddata_sdk/cli/clone.py
@@ -1,49 +1,29 @@
 # (C) 2024 GoodData Corporation
 import argparse
-import json
 import shutil
-import subprocess
 from pathlib import Path
 
-from gooddata_sdk import CatalogDeclarativeWorkspaces, GoodDataSdk
+from gooddata_sdk import GoodDataSdk
+from gooddata_sdk.catalog.workspace.aac import store_aac_workspace_to_disk
 from gooddata_sdk.cli.constants import (
-    BASE_DIR,
     CONFIG_FILE,
     DATA_SOURCES,
-    GD_COMMAND,
     USER_GROUPS,
     USERS,
     WORKSPACES,
     WORKSPACES_DATA_FILTERS,
 )
-from gooddata_sdk.cli.utils import (
-    Bcolors,
-    measure_clone,
-)
-
-
-def _call_gd_stream_in(workspace_objects: CatalogDeclarativeWorkspaces, path: Path) -> None:
-    """
-    Call 'gd stream-in' command to create workspaces file structure using Node.js CLI.
-    """
-    workspaces = json.dumps({WORKSPACES: workspace_objects.to_dict()[WORKSPACES]})
-    p = subprocess.Popen(
-        [GD_COMMAND, "stream-in"],
-        cwd=path,
-        stdin=subprocess.PIPE,
-        stdout=subprocess.PIPE,
-        stderr=subprocess.PIPE,
-    )
-    _, err = p.communicate(input=workspaces.encode())
-    if err:
-        print(f"{Bcolors.FAIL}Clone workspaces failed with the following error {err=}.{Bcolors.ENDC}")
+from gooddata_sdk.cli.deploy import _get_workspace_id
+from gooddata_sdk.cli.utils import measure_clone
 
 
 @measure_clone(step="workspaces")
-def _clone_workspaces(sdk: GoodDataSdk, path: Path) -> None:
-    assert (path / CONFIG_FILE).exists() and (path / BASE_DIR).exists()
-    workspace_objects = sdk.catalog_workspace.get_declarative_workspaces()
-    _call_gd_stream_in(workspace_objects, path)
+def _clone_workspaces(sdk: GoodDataSdk, path: Path, source_dir: str) -> None:
+    config_path = path / CONFIG_FILE
+    workspace_id = _get_workspace_id(config_path)
+    source_path = path / source_dir
+    workspace_model = sdk.catalog_workspace.get_declarative_workspace(workspace_id)
+    store_aac_workspace_to_disk(workspace_model, source_path)
 
 
 @measure_clone(step="data sources")
@@ -70,31 +50,29 @@ def _clone_workspace_data_filters(sdk: GoodDataSdk, analytics_root_dir: Path) ->
     workspace_data_filters.store_to_disk(analytics_root_dir)
 
 
-def clone_all(path: Path) -> None:
-    init_file = path / CONFIG_FILE
-    sdk = GoodDataSdk.create_from_profile(profiles_path=init_file)
-    analytics_root_dir = path / BASE_DIR
+def clone_all(path: Path, source_dir: str) -> None:
+    config_path = path / CONFIG_FILE
+    sdk = GoodDataSdk.create_from_profile(profiles_path=config_path)
+    analytics_root_dir = path / source_dir
 
     # clean the directory
     if analytics_root_dir.exists():
         shutil.rmtree(analytics_root_dir)
-    # create directory
     analytics_root_dir.mkdir()
 
-    print("Cloning the whole organization... ⏲️⏲️️⏲️️")
+    print("Cloning the whole organization...")
     _clone_data_sources(sdk, analytics_root_dir)
     _clone_user_groups(sdk, analytics_root_dir)
     _clone_users(sdk, analytics_root_dir)
     _clone_workspace_data_filters(sdk, analytics_root_dir)
-    _clone_workspaces(sdk, path)
-    print("Cloning finished 🚀🚀🚀")
+    _clone_workspaces(sdk, path, source_dir)
+    print("Cloning finished.")
 
 
-def clone_granular(path: Path, args: argparse.Namespace) -> None:
-    init_file = path / CONFIG_FILE
-    analytics_root_dir = path / "analytics"
-    config_directory = analytics_root_dir.parent
-    sdk = GoodDataSdk.create_from_profile(profiles_path=init_file)
+def clone_granular(path: Path, source_dir: str, args: argparse.Namespace) -> None:
+    config_path = path / CONFIG_FILE
+    analytics_root_dir = path / source_dir
+    sdk = GoodDataSdk.create_from_profile(profiles_path=config_path)
     selected_entities = set(args.only)
     if DATA_SOURCES in selected_entities:
         _clone_data_sources(sdk, analytics_root_dir)
@@ -105,4 +83,4 @@ def clone_granular(path: Path, args: argparse.Namespace) -> None:
     if WORKSPACES_DATA_FILTERS in selected_entities:
         _clone_workspace_data_filters(sdk, analytics_root_dir)
     if WORKSPACES in selected_entities:
-        _clone_workspaces(sdk, config_directory)
+        _clone_workspaces(sdk, path, source_dir)
diff --git a/packages/gooddata-sdk/src/gooddata_sdk/cli/constants.py b/packages/gooddata-sdk/src/gooddata_sdk/cli/constants.py
index d5120047c..7a448b584 100644
--- a/packages/gooddata-sdk/src/gooddata_sdk/cli/constants.py
+++ b/packages/gooddata-sdk/src/gooddata_sdk/cli/constants.py
@@ -1,5 +1,4 @@
 # (C) 2024 GoodData Corporation
-from pathlib import Path
 
 DATA_SOURCES = "data_sources"
 USER_GROUPS = "user_groups"
@@ -10,8 +9,4 @@
 DATA_SOURCE = "data_source"
 
 CONFIG_FILE = "gooddata.yaml"
-BASE_DIR = "analytics"
-
-GD_ROOT = Path.home() / ".gooddata"
-GD_COMMAND = GD_ROOT / "node_modules/.bin/gd"
-GD_PACKAGE_JSON = GD_ROOT / "node_modules/@gooddata/code-cli/package.json"
+DEFAULT_SOURCE_DIR = "analytics"
diff --git a/packages/gooddata-sdk/src/gooddata_sdk/cli/deploy.py b/packages/gooddata-sdk/src/gooddata_sdk/cli/deploy.py
index 657678774..1b14c5db7 100644
--- a/packages/gooddata-sdk/src/gooddata_sdk/cli/deploy.py
+++ b/packages/gooddata-sdk/src/gooddata_sdk/cli/deploy.py
@@ -1,72 +1,64 @@
 # (C) 2024 GoodData Corporation
 import argparse
-import json
-import subprocess
 from pathlib import Path
-from typing import Any
 
 from gooddata_sdk import (
     CatalogDeclarativeDataSources,
     CatalogDeclarativeUserGroups,
     CatalogDeclarativeUsers,
-    CatalogDeclarativeWorkspace,
     CatalogDeclarativeWorkspaceDataFilters,
-    CatalogDeclarativeWorkspaces,
     GoodDataSdk,
 )
+from gooddata_sdk.catalog.workspace.aac import load_aac_workspace_from_disk
 from gooddata_sdk.cli.constants import (
-    BASE_DIR,
     CONFIG_FILE,
     DATA_SOURCES,
-    GD_COMMAND,
     USER_GROUPS,
     USERS,
     WORKSPACES,
     WORKSPACES_DATA_FILTERS,
 )
 from gooddata_sdk.cli.utils import measure_deploy
+from gooddata_sdk.config import AacConfig
+from gooddata_sdk.utils import read_layout_from_file
+
+
+def _get_workspace_id(config_path: Path, profile: str = "default") -> str:
+    """Extract workspace_id from the config file profile."""
+    content = read_layout_from_file(config_path)
+    if not isinstance(content, dict):
+        raise ValueError(f"Invalid config file: {config_path}")
+    config = AacConfig.from_dict(content)
+    selected_profile = config.default_profile if profile == "default" else profile
+    if selected_profile not in config.profiles:
+        raise ValueError(f"Profile '{selected_profile}' not found in config")
+    p = config.profiles[selected_profile]
+    if p.workspace_id is None:
+        raise ValueError(
+            f"Profile '{selected_profile}' does not have 'workspace_id' set. Required for deploying workspace objects."
+        )
+    return p.workspace_id
 
 
-def _call_gd_stram_out(path: Path) -> dict[str, Any]:
-    """
-    Call 'gd stream-out' command to read workspaces file structure using Node.js CLI.
-    """
-    assert (path / CONFIG_FILE).exists() and (path / BASE_DIR).exists()
-    p = subprocess.Popen(
-        [GD_COMMAND, "stream-out", "--no-validate"],
-        cwd=path,
-        stdin=subprocess.PIPE,
-        stdout=subprocess.PIPE,
-        stderr=subprocess.PIPE,
-    )
-    output, err = p.communicate()
-    if err:
-        print(f"Deploy workspaces failed with the following error {err=}.")
-    data = json.loads(output.decode())
-    if WORKSPACES not in data:
-        raise ValueError("No workspaces found in the output.")
-    return data
+@measure_deploy(step=WORKSPACES)
+def _deploy_workspaces(sdk: GoodDataSdk, path: Path, source_dir: str) -> None:
+    source_path = path / source_dir
+    config_path = path / CONFIG_FILE
+    workspace_id = _get_workspace_id(config_path)
+    workspace_model = load_aac_workspace_from_disk(source_path)
 
+    # Preserve workspace data filters from declarative subdirs
+    wdf = CatalogDeclarativeWorkspaceDataFilters.load_from_disk(source_path)
+    if wdf.workspace_data_filters:
+        workspace_model.remove_wdf_refs()
 
-@measure_deploy(step=WORKSPACES)
-def _deploy_workspaces_with_filters(sdk: GoodDataSdk, path: Path) -> None:
-    analytics_root_dir = path / BASE_DIR
-    data = _call_gd_stram_out(path)
-    workspaces = [CatalogDeclarativeWorkspace.from_dict(workspace_dict) for workspace_dict in data[WORKSPACES]]
-    # fetch this information first, so we do not lose them
-    workspace_data_filters = CatalogDeclarativeWorkspaceDataFilters.load_from_disk(analytics_root_dir)
-    workspaces_o = CatalogDeclarativeWorkspaces(
-        workspaces=workspaces, workspace_data_filters=workspace_data_filters.workspace_data_filters
-    )
-    sdk.catalog_workspace.put_declarative_workspaces(workspaces_o)
+    sdk.catalog_workspace.put_declarative_workspace(workspace_id=workspace_id, workspace=workspace_model)
 
 
 @measure_deploy(step="data sources")
-def _deploy_data_sources(sdk: GoodDataSdk, analytics_root_dir: Path) -> None:
+def _deploy_data_sources(sdk: GoodDataSdk, analytics_root_dir: Path, config_path: Path) -> None:
     data_sources = CatalogDeclarativeDataSources.load_from_disk(analytics_root_dir)
-    sdk.catalog_data_source.put_declarative_data_sources(
-        data_sources, config_file=analytics_root_dir.parent / "gooddata.yaml"
-    )
+    sdk.catalog_data_source.put_declarative_data_sources(data_sources, config_file=config_path)
 
 
 @measure_deploy(step="user groups")
@@ -87,27 +79,26 @@ def _deploy_workspace_data_filters(sdk: GoodDataSdk, analytics_root_dir: Path) -
     sdk.catalog_workspace.put_declarative_workspace_data_filters(workspace_data_filters)
 
 
-def deploy_all(path: Path) -> None:
-    init_file = path / CONFIG_FILE
-    sdk = GoodDataSdk.create_from_profile(profiles_path=init_file)
-
-    analytics_root_dir = path / BASE_DIR
+def deploy_all(path: Path, source_dir: str) -> None:
+    config_path = path / CONFIG_FILE
+    sdk = GoodDataSdk.create_from_profile(profiles_path=config_path)
+    analytics_root_dir = path / source_dir
 
-    print("Deploying the whole organization... ⏲️⏲️⏲️")
-    _deploy_data_sources(sdk, analytics_root_dir)
+    print("Deploying the whole organization...")
+    _deploy_data_sources(sdk, analytics_root_dir, config_path)
     _deploy_user_groups(sdk, analytics_root_dir)
     _deploy_users(sdk, analytics_root_dir)
-    _deploy_workspaces_with_filters(sdk, path)
-    print("Deployed 🚀🚀🚀")
+    _deploy_workspaces(sdk, path, source_dir)
+    print("Deployed successfully.")
 
 
-def deploy_granular(path: Path, args: argparse.Namespace) -> None:
-    init_file = path / CONFIG_FILE
-    analytics_root_dir = path / "analytics"
+def deploy_granular(path: Path, source_dir: str, args: argparse.Namespace) -> None:
+    config_path = path / CONFIG_FILE
+    analytics_root_dir = path / source_dir
     selected_entities = set(args.only)
-    sdk = GoodDataSdk.create_from_profile(profiles_path=init_file)
+    sdk = GoodDataSdk.create_from_profile(profiles_path=config_path)
     if DATA_SOURCES in selected_entities:
-        _deploy_data_sources(sdk, analytics_root_dir)
+        _deploy_data_sources(sdk, analytics_root_dir, config_path)
     if USER_GROUPS in selected_entities:
         _deploy_user_groups(sdk, analytics_root_dir)
     if USERS in selected_entities:
@@ -115,4 +106,4 @@ def deploy_granular(path: Path, args: argparse.Namespace) -> None:
     if WORKSPACES_DATA_FILTERS in selected_entities:
         _deploy_workspace_data_filters(sdk, analytics_root_dir)
     if WORKSPACES in selected_entities:
-        _deploy_workspaces_with_filters(sdk, analytics_root_dir.parent)
+        _deploy_workspaces(sdk, path, source_dir)
diff --git a/packages/gooddata-sdk/src/gooddata_sdk/cli/gdc_core.py b/packages/gooddata-sdk/src/gooddata_sdk/cli/gdc_core.py
index a6297b21f..ebb8982ad 100644
--- a/packages/gooddata-sdk/src/gooddata_sdk/cli/gdc_core.py
+++ b/packages/gooddata-sdk/src/gooddata_sdk/cli/gdc_core.py
@@ -1,113 +1,70 @@
 # (C) 2024 GoodData Corporation
 import argparse
-import shutil
-import subprocess
 import sys
 from pathlib import Path
 
 from gooddata_sdk.cli.clone import clone_all, clone_granular
-from gooddata_sdk.cli.constants import GD_COMMAND, GD_PACKAGE_JSON, GD_ROOT
+from gooddata_sdk.cli.constants import CONFIG_FILE, DEFAULT_SOURCE_DIR
 from gooddata_sdk.cli.deploy import deploy_all, deploy_granular
 from gooddata_sdk.cli.utils import _SUPPORTED, Bcolors
-from gooddata_sdk.utils import read_json
+from gooddata_sdk.config import AacConfig
+from gooddata_sdk.utils import read_layout_from_file
 
-_CURRENT_DIR = Path(__file__).parent
 
+def _find_config_file() -> Path:
+    """Find the gooddata.yaml config file in the current directory or parents."""
+    current = Path.cwd()
+    for directory in [current, *current.parents]:
+        config_path = directory / CONFIG_FILE
+        if config_path.exists():
+            return config_path
+    print(f"{Bcolors.FAIL}Config file {CONFIG_FILE} was not found.{Bcolors.ENDC}")
+    sys.exit(1)
 
-def get_manifest_directory() -> Path:
-    """
-    Get the directory where the manifest file (gooddata.yaml) is located
-    using the gd stream-manifest-path command.
-    """
-    p = subprocess.Popen(
-        [GD_COMMAND, "stream-manifest-path"],
-        cwd=Path().resolve(),
-        stdin=subprocess.PIPE,
-        stdout=subprocess.PIPE,
-        stderr=subprocess.PIPE,
-    )
-    output, err = p.communicate()
-    if err:
-        print(f"{Bcolors.FAIL}Manifest gooddata.yaml was not found.{Bcolors.ENDC}")
-        sys.exit(1)
-    return Path(output.decode()).parent
+
+def _get_source_dir(config_path: Path) -> str:
+    """Get source_dir from config file, falling back to default."""
+    content = read_layout_from_file(config_path)
+    if isinstance(content, dict) and AacConfig.can_structure(content):
+        config = AacConfig.from_dict(content)
+        if config.source_dir is not None:
+            return config.source_dir
+    return DEFAULT_SOURCE_DIR
 
 
-def _deploy(path: Path, args: argparse.Namespace) -> None:
-    """
-    Handles deploy command use cases.
-    """
+def _deploy(path: Path, source_dir: str, args: argparse.Namespace) -> None:
     if not path.is_dir():
         raise ValueError(f"Path {path} is not a directory.")
-
     if args.only is None:
-        deploy_all(path)
+        deploy_all(path, source_dir)
     else:
-        deploy_granular(path, args)
+        deploy_granular(path, source_dir, args)
 
 
-def _clone(path: Path, args: argparse.Namespace) -> None:
-    """
-    Handles clone command use cases.
-    """
+def _clone(path: Path, source_dir: str, args: argparse.Namespace) -> None:
     if args.only is None:
-        clone_all(path)
+        clone_all(path, source_dir)
     else:
-        clone_granular(path, args)
-
-
-def _manage_node_cli() -> None:
-    """
-    First, it checks if Node CLI is installed and if it is the correct version.
-    If not, it installs the correct version. If it is not installed at all then it's installed
-    locally in ~/.gooddata directory.
-    """
-    requested_version = read_json(_CURRENT_DIR / "package.json")["dependencies"]["@gooddata/code-cli"]
-    if GD_PACKAGE_JSON.exists():
-        current_version = read_json(GD_PACKAGE_JSON)["version"]
-        if current_version == requested_version:
-            return
-        else:
-            print(
-                f"Node.js @gooddata/code-cli version '{requested_version}' is required,"
-                f" but version '{current_version}' is installed."
-            )
-    if not GD_ROOT.exists():
-        GD_ROOT.mkdir()
-    shutil.copyfile(_CURRENT_DIR / "package.json", GD_ROOT / "package.json")
-    print(f"Installing @gooddata/code-cli version '{requested_version}' in {GD_ROOT}...")
-    p = subprocess.Popen(
-        ["npm", "i"],
-        cwd=GD_ROOT,
-        stdin=subprocess.PIPE,
-        stdout=subprocess.PIPE,
-        stderr=subprocess.PIPE,
-    )
-    _, err = p.communicate()
-    if err:
-        print(f"{Bcolors.FAIL}An error has occurred during installation: {err.decode()}.{Bcolors.ENDC}")
-        sys.exit(1)
+        clone_granular(path, source_dir, args)
 
 
 def main() -> None:
-    """
-    The entrypoint for gdc cli.
-    """
     parser = argparse.ArgumentParser(
         prog="gdc",
-        description="Process GoodData as code file structure. Utilize @gooddata/code-cli for workspaces. "
-        "Note that this is an EXPERIMENTAL feature.",
+        description="GoodData CLI for deploying and cloning analytics-as-code projects.",
     )
     parser.add_argument("action", help="Specify if you want to deploy or clone project.", choices=("deploy", "clone"))
     parser.add_argument("--only", help="Specify available granularity for action.", nargs="+", choices=_SUPPORTED)
 
-    _manage_node_cli()
     args = parser.parse_args()
-    manifest_directory = get_manifest_directory()
+    config_path = _find_config_file()
+    manifest_directory = config_path.parent
+    source_dir = _get_source_dir(config_path)
+
     if args.action == "clone":
-        _clone(manifest_directory, args)
+        _clone(manifest_directory, source_dir, args)
     elif args.action == "deploy":
-        _deploy(manifest_directory, args)
+        _deploy(manifest_directory, source_dir, args)
 
 
 if __name__ == "__main__":
diff --git a/packages/gooddata-sdk/src/gooddata_sdk/cli/package.json b/packages/gooddata-sdk/src/gooddata_sdk/cli/package.json
deleted file mode 100644
index 8af00fa5f..000000000
--- a/packages/gooddata-sdk/src/gooddata_sdk/cli/package.json
+++ /dev/null
@@ -1,7 +0,0 @@
-{
-    "name": "test",
-    "version": "1.0.0",
-    "dependencies": {
-        "@gooddata/code-cli": "1.0.0-alpha.3"
-    }
-}
diff --git a/packages/gooddata-sdk/src/gooddata_sdk/config.py b/packages/gooddata-sdk/src/gooddata_sdk/config.py
index bce62d3cc..e6611fd74 100644
--- a/packages/gooddata-sdk/src/gooddata_sdk/config.py
+++ b/packages/gooddata-sdk/src/gooddata_sdk/config.py
@@ -32,26 +32,35 @@ def can_structure(cls: type[T], data: dict[str, Any]) -> bool:
 class Profile(ConfigBase):
     host: str
     token: str
+    workspace_id: str | None = None
+    data_source: str | None = None
     custom_headers: dict[str, str] | None = None
     extra_user_agent: str | None = None
     ssl_ca_cert: str | None = None
 
+    # Fields used only by CLI/config, not passed to GoodDataApiClient
+    _NON_API_FIELDS = frozenset({"workspace_id", "data_source"})
+
     def to_dict(self, use_env: bool = False) -> dict[str, str]:
         load_dotenv()
+        base = {k: v for k, v in asdict(self).items() if k not in self._NON_API_FIELDS}
         if not use_env:
-            return asdict(self)
+            return base
         env_var = self.token[1:]
         if env_var not in os.environ:
             raise ValueError(f"Environment variable {env_var} not found")
-        return {**asdict(self), "token": os.environ[env_var]}
+        return {**base, "token": os.environ[env_var]}
 
 
 @define
 class AacConfig(ConfigBase):
     profiles: dict[str, Profile]
     default_profile: str
-    access: dict[str, str]
+    access: dict[str, str] | None = None
+    source_dir: str | None = None
 
     def ds_credentials(self) -> dict[str, str]:
         load_dotenv()
+        if self.access is None:
+            return {}
         return {k: os.environ.get(v[1:], v) for k, v in self.access.items()}
diff --git a/packages/gooddata-sdk/tests/catalog/fixtures/aac/dashboards/dashboard_1.yaml b/packages/gooddata-sdk/tests/catalog/fixtures/aac/dashboards/dashboard_1.yaml
new file mode 100644
index 000000000..b46d932cf
--- /dev/null
+++ b/packages/gooddata-sdk/tests/catalog/fixtures/aac/dashboards/dashboard_1.yaml
@@ -0,0 +1,35 @@
+# (C) 2026 GoodData Corporation
+# A dashboard is a collection of visualizations that are organized into sections.
+# Because they allow filtering and other adjustments, they function as a dynamic presentation layer for your data analytics.
+# Read more about dashboards:
+# https://www.gooddata.com/docs/cloud/create-dashboards/concepts/dashboard/
+
+id: 90a53321-9060-4aef-9dc6-a3d0a9a5323e
+type: dashboard
+
+title: Dashboard 1
+
+sections:
+    - widgets:
+          - visualization: 71bdc379-384a-4eac-9627-364ea847d977
+            title: Ratings
+            columns: 12
+            rows: 22
+
+filters:
+    date_month:
+        type: date_filter
+        granularity: MONTH
+        from: 0
+        to: 0
+        mode: hidden
+    customer_created_date_year:
+        type: date_filter
+        granularity: YEAR
+        date: customer_created_date
+        from: 0
+        to: 0
+        mode: hidden
+    customer_age:
+        type: attribute_filter
+        using: label/customer_age
diff --git a/packages/gooddata-sdk/tests/catalog/fixtures/aac/datasets/customer.yaml b/packages/gooddata-sdk/tests/catalog/fixtures/aac/datasets/customer.yaml
new file mode 100644
index 000000000..77f1bab17
--- /dev/null
+++ b/packages/gooddata-sdk/tests/catalog/fixtures/aac/datasets/customer.yaml
@@ -0,0 +1,97 @@
+# (C) 2026 GoodData Corporation
+# A dataset is a logical object that represents a set of related facts, attributes, and attribute labels.
+# Datasets are basic organization units of a logical data model.
+# Read more about Datasets:
+# https://www.gooddata.com/developers/cloud-native/doc/cloud/model-data/concepts/dataset/
+
+type: dataset
+id: customer
+
+table_path: ECOMMERCE_DEMO_SCHEMA/customer
+
+title: Customer
+description: Customer
+tags:
+    - Customer
+
+primary_key: customer_id
+
+fields:
+    customer_city:
+        type: attribute
+        source_column: customer_city
+        data_type: STRING
+        title: Customer city
+        description: Customer city
+        tags:
+            - Customer
+        labels:
+            geo__customer_city__city_pushpin_latitude:
+                source_column: geo__customer_city__city_pushpin_latitude
+                data_type: STRING
+                title: City pushpin latitude
+                description: City pushpin latitude
+                tags:
+                    - Customer
+            geo__customer_city__city_pushpin_longitude:
+                source_column: geo__customer_city__city_pushpin_longitude
+                data_type: STRING
+                title: City pushpin longitude
+                description: City pushpin longitude
+                tags:
+                    - Customer
+    customer_country:
+        type: attribute
+        source_column: customer_country
+        data_type: STRING
+        title: Customer country
+        description: Customer country
+        tags:
+            - Customer
+    customer_email:
+        type: attribute
+        source_column: customer_email
+        data_type: STRING
+        title: Customer email
+        description: Customer email
+        tags:
+            - Customer
+        labels:
+            customer_email.customeremaillink:
+                source_column: customer_email
+                data_type: STRING
+                title: Customer email link
+                tags:
+                    - Customer
+                value_type: HYPERLINK
+    customer_id:
+        type: attribute
+        source_column: customer_id
+        data_type: STRING
+        title: Customer id
+        description: Customer id
+        tags:
+            - Customer
+        labels:
+            customer_name:
+                source_column: ls__customer_id__customer_name
+                data_type: STRING
+                title: Customer name
+                description: Customer name
+                tags:
+                    - Customer
+    customer_state:
+        type: attribute
+        source_column: customer_state
+        data_type: STRING
+        title: Customer state
+        description: Customer state
+        tags:
+            - Customer
+
+references:
+    - dataset: customer_created_date
+      sources:
+          - source_column: customer_created_date
+            data_type: DATE
+            target: customer_created_date
diff --git a/packages/gooddata-sdk/tests/catalog/fixtures/aac/datasets/order_date.yaml b/packages/gooddata-sdk/tests/catalog/fixtures/aac/datasets/order_date.yaml
new file mode 100644
index 000000000..9375792b8
--- /dev/null
+++ b/packages/gooddata-sdk/tests/catalog/fixtures/aac/datasets/order_date.yaml
@@ -0,0 +1,32 @@
+# (C) 2026 GoodData Corporation
+# A Date dataset is a dataset in the logical data model(LDM)
+# that represents DATE / TIMESTAMP columns in your database.
+# Read more about date instances:
+# https://www.gooddata.com/developers/cloud-native/doc/cloud/model-data/concepts/dataset/#date-datasets
+
+type: date
+id: order_date
+
+title: Order date
+tags:
+    - Order date
+
+granularities:
+    - MINUTE
+    - HOUR
+    - DAY
+    - WEEK
+    - MONTH
+    - QUARTER
+    - YEAR
+    - MINUTE_OF_HOUR
+    - HOUR_OF_DAY
+    - DAY_OF_WEEK
+    - DAY_OF_MONTH
+    - DAY_OF_YEAR
+    - WEEK_OF_YEAR
+    - MONTH_OF_YEAR
+    - QUARTER_OF_YEAR
+
+title_base: ""
+title_pattern: "%titleBase - %granularityTitle"
diff --git a/packages/gooddata-sdk/tests/catalog/fixtures/aac/datasets/orders.yaml b/packages/gooddata-sdk/tests/catalog/fixtures/aac/datasets/orders.yaml
new file mode 100644
index 000000000..3582723f1
--- /dev/null
+++ b/packages/gooddata-sdk/tests/catalog/fixtures/aac/datasets/orders.yaml
@@ -0,0 +1,35 @@
+# (C) 2026 GoodData Corporation
+# A dataset is a logical object that represents a set of related facts, attributes, and attribute labels.
+# Datasets are basic organization units of a logical data model.
+# Read more about Datasets:
+# https://www.gooddata.com/developers/cloud-native/doc/cloud/model-data/concepts/dataset/
+
+type: dataset
+id: orders
+
+table_path: ECOMMERCE_DEMO_SCHEMA/orders
+
+title: Orders
+description: Orders
+tags:
+    - Orders
+
+primary_key: order_id
+
+fields:
+    order_id:
+        type: attribute
+        source_column: order_id
+        data_type: STRING
+        title: Order id
+        description: Order id
+        tags:
+            - Orders
+    order_status:
+        type: attribute
+        source_column: order_status
+        data_type: STRING
+        title: Order status
+        description: Order status
+        tags:
+            - Orders
diff --git a/packages/gooddata-sdk/tests/catalog/fixtures/aac/gooddata.yaml b/packages/gooddata-sdk/tests/catalog/fixtures/aac/gooddata.yaml
new file mode 100644
index 000000000..88559b8a9
--- /dev/null
+++ b/packages/gooddata-sdk/tests/catalog/fixtures/aac/gooddata.yaml
@@ -0,0 +1,9 @@
+# (C) 2026 GoodData Corporation
+profiles:
+  default:
+    host: "https://test.gooddata.com"
+    token: "test-token"
+    workspace_id: "test-workspace"
+    data_source: "test-datasource"
+default_profile: "default"
+source_dir: "analytics"
diff --git a/packages/gooddata-sdk/tests/catalog/fixtures/aac/metrics/top_products.yaml b/packages/gooddata-sdk/tests/catalog/fixtures/aac/metrics/top_products.yaml
new file mode 100644
index 000000000..344534843
--- /dev/null
+++ b/packages/gooddata-sdk/tests/catalog/fixtures/aac/metrics/top_products.yaml
@@ -0,0 +1,13 @@
+# (C) 2026 GoodData Corporation
+# A metric is a computational expression of numerical data (facts or other metrics).
+# Use MAQL to create reusable multidimensional queries that combine multiple facts and attributes.
+# Read more about MAQL:
+# https://www.gooddata.com/developers/cloud-native/doc/cloud/create-metrics/maql/
+
+type: metric
+id: top_products
+
+title: Top Products
+
+maql: SELECT SUM({fact/rating}) WHERE {label/product_rating} = "*****";
+format: "#,##0.00"
diff --git a/packages/gooddata-sdk/tests/catalog/fixtures/aac/visualisations/ratings.yaml b/packages/gooddata-sdk/tests/catalog/fixtures/aac/visualisations/ratings.yaml
new file mode 100644
index 000000000..ab26fbfd3
--- /dev/null
+++ b/packages/gooddata-sdk/tests/catalog/fixtures/aac/visualisations/ratings.yaml
@@ -0,0 +1,23 @@
+# (C) 2026 GoodData Corporation
+# A visualization is a visual representation of a user’s analytical view of the data.
+# You build visualizations from metrics, attributes, and optionally filters that are combined in a way to visualize a particular aspect of your data.
+# The visualizations are executed over and over as fresh data gets loaded.
+# Interpreting the content of a visualization is up to the user (the consumer of the visualization).
+# Read more about visualisations:
+# https://www.gooddata.com/developers/cloud-native/doc/cloud/create-visualizations/concepts/visualization/
+
+id: 71bdc379-384a-4eac-9627-364ea847d977
+type: table
+
+title: Ratings
+
+query:
+    fields:
+        sum_of_rating_1:
+            title: Sum of Rating
+            aggregation: SUM
+            using: fact/rating
+
+metrics:
+    - field: sum_of_rating_1
+      format: "#,##0.00"
diff --git a/packages/gooddata-sdk/tests/catalog/fixtures/aac/visualisations/ratings_per_category.yaml b/packages/gooddata-sdk/tests/catalog/fixtures/aac/visualisations/ratings_per_category.yaml
new file mode 100644
index 000000000..b7c964220
--- /dev/null
+++ b/packages/gooddata-sdk/tests/catalog/fixtures/aac/visualisations/ratings_per_category.yaml
@@ -0,0 +1,43 @@
+# (C) 2026 GoodData Corporation
+# A visualization is a visual representation of a user’s analytical view of the data.
+# You build visualizations from metrics, attributes, and optionally filters that are combined in a way to visualize a particular aspect of your data.
+# The visualizations are executed over and over as fresh data gets loaded.
+# Interpreting the content of a visualization is up to the user (the consumer of the visualization).
+# Read more about visualisations:
+# https://www.gooddata.com/developers/cloud-native/doc/cloud/create-visualizations/concepts/visualization/
+
+id: 4c2002a4-a60c-4f4a-a440-d2a6a35887cf
+type: column_chart
+
+title: Ratings per Category
+
+query:
+    fields:
+        sum_of_rating:
+            title: Sum of Rating
+            aggregation: SUM
+            using: fact/rating
+        product_category: label/product_category
+        product_rating: label/product_rating
+
+metrics:
+    - field: sum_of_rating
+      format: "#,##0.00"
+
+view_by:
+    - product_category
+
+segment_by:
+    - product_rating
+
+config:
+    colors:
+        "*": rgb(255,0,0)
+        "**": rgb(255,159,0)
+        "***": rgb(245,255,102)
+        "****": rgb(102,255,235)
+        "*****": rgb(23,242,13)
+    legend_position: top
+    xaxis_name_position: center
+    xaxis_rotation: "0"
+    yaxis_name_position: top
diff --git a/packages/gooddata-sdk/tests/catalog/test_aac.py b/packages/gooddata-sdk/tests/catalog/test_aac.py
new file mode 100644
index 000000000..f4ccfe741
--- /dev/null
+++ b/packages/gooddata-sdk/tests/catalog/test_aac.py
@@ -0,0 +1,282 @@
+# (C) 2026 GoodData Corporation
+from __future__ import annotations
+
+from pathlib import Path
+
+import yaml
+from gooddata_sdk.catalog.workspace.aac import (
+    aac_dataset_to_declarative,
+    aac_date_dataset_to_declarative,
+    aac_metric_to_declarative,
+    aac_visualization_to_declarative,
+    declarative_dataset_to_aac,
+    declarative_metric_to_aac,
+    detect_yaml_format,
+    load_aac_workspace_from_disk,
+    store_aac_workspace_to_disk,
+)
+from gooddata_sdk.config import AacConfig
+
+_FIXTURES_DIR = Path(__file__).parent / "fixtures" / "aac"
+
+
+# ---------------------------------------------------------------------------
+# Config alignment tests
+# ---------------------------------------------------------------------------
+
+
+class TestAacConfig:
+    def test_parse_vscode_config(self) -> None:
+        """VSCode plugin's gooddata.yaml should be parseable by AacConfig."""
+        content = yaml.safe_load((_FIXTURES_DIR / "gooddata.yaml").read_text())
+        assert AacConfig.can_structure(content)
+        config = AacConfig.from_dict(content)
+        assert config.default_profile == "default"
+        assert config.source_dir == "analytics"
+        profile = config.profiles["default"]
+        assert profile.host == "https://test.gooddata.com"
+        assert profile.workspace_id == "test-workspace"
+        assert profile.data_source == "test-datasource"
+
+    def test_config_without_access(self) -> None:
+        """Config without 'access' field (VSCode style) should parse fine."""
+        content = {
+            "profiles": {"dev": {"host": "https://h", "token": "t"}},
+            "default_profile": "dev",
+        }
+        assert AacConfig.can_structure(content)
+        config = AacConfig.from_dict(content)
+        assert config.access is None
+        assert config.ds_credentials() == {}
+
+    def test_config_with_source_dir(self) -> None:
+        content = {
+            "profiles": {"dev": {"host": "https://h", "token": "t"}},
+            "default_profile": "dev",
+            "source_dir": "my_analytics",
+        }
+        config = AacConfig.from_dict(content)
+        assert config.source_dir == "my_analytics"
+
+
+# ---------------------------------------------------------------------------
+# Individual conversion tests
+# ---------------------------------------------------------------------------
+
+
+class TestIndividualConversions:
+    def test_metric_round_trip(self) -> None:
+        aac_input = {
+            "id": "revenue",
+            "title": "Revenue",
+            "maql": "SELECT SUM({fact/amount})",
+            "format": "#,##0",
+        }
+        declarative = aac_metric_to_declarative(aac_input)
+        assert declarative["id"] == "revenue"
+        assert declarative["title"] == "Revenue"
+        assert declarative["content"]["maql"] == "SELECT SUM({fact/amount})"
+
+        result = declarative_metric_to_aac(declarative)
+        assert "json" in result
+        assert "content" in result
+        assert result["json"]["id"] == "revenue"
+        assert result["json"]["maql"] == "SELECT SUM({fact/amount})"
+
+    def test_dataset_to_declarative(self) -> None:
+        """Test forward conversion: AAC dataset → declarative."""
+        aac_input = {
+            "type": "dataset",
+            "id": "orders",
+            "table_path": "orders",
+            "title": "Orders",
+            "primary_key": "order_id",
+            "fields": {
+                "order_id": {
+                    "type": "attribute",
+                    "source_column": "order_id",
+                    "data_type": "STRING",
+                    "title": "Order ID",
+                },
+            },
+        }
+        declarative = aac_dataset_to_declarative(aac_input)
+        assert declarative["id"] == "orders"
+        assert declarative["title"] == "Orders"
+
+    def test_date_dataset_conversion(self) -> None:
+        aac_input = {
+            "type": "date",
+            "id": "order_date",
+            "title": "Order Date",
+        }
+        declarative = aac_date_dataset_to_declarative(aac_input)
+        assert declarative["id"] == "order_date"
+        assert declarative["title"] == "Order Date"
+
+    def test_visualization_to_declarative(self) -> None:
+        """Test forward conversion: AAC visualization → declarative."""
+        aac_input = {
+            "type": "table",
+            "id": "my_table",
+            "title": "My Table",
+            "query": {
+                "fields": {
+                    "m1": {
+                        "title": "Sum of Amount",
+                        "aggregation": "SUM",
+                        "using": "fact/amount",
+                    },
+                },
+            },
+            "metrics": [{"field": "m1", "format": "#,##0"}],
+        }
+        declarative = aac_visualization_to_declarative(aac_input)
+        assert declarative["id"] == "my_table"
+        assert declarative["title"] == "My Table"
+
+    def test_metric_from_fixture(self) -> None:
+        content = yaml.safe_load((_FIXTURES_DIR / "metrics" / "top_products.yaml").read_text())
+        declarative = aac_metric_to_declarative(content)
+        assert declarative["id"] == "top_products"
+        assert declarative["title"] == "Top Products"
+
+    def test_dataset_from_fixture(self) -> None:
+        content = yaml.safe_load((_FIXTURES_DIR / "datasets" / "orders.yaml").read_text())
+        declarative = aac_dataset_to_declarative(content)
+        assert declarative["id"] == "orders"
+
+    def test_visualization_from_fixture(self) -> None:
+        content = yaml.safe_load((_FIXTURES_DIR / "visualisations" / "ratings.yaml").read_text())
+        declarative = aac_visualization_to_declarative(content)
+        assert declarative["id"] == "71bdc379-384a-4eac-9627-364ea847d977"
+
+    def test_metric_declarative_to_aac(self) -> None:
+        """Test the full round-trip on metrics (both directions work cleanly)."""
+        aac_input = {
+            "id": "budget",
+            "title": "Budget",
+            "maql": "SELECT SUM({fact/budget})",
+            "format": "#,##0.00",
+            "description": "Total budget",
+            "tags": ["finance"],
+        }
+        declarative = aac_metric_to_declarative(aac_input)
+        result = declarative_metric_to_aac(declarative)
+        assert result["json"]["id"] == "budget"
+        assert result["json"]["maql"] == "SELECT SUM({fact/budget})"
+        assert isinstance(result["content"], str)
+        assert "budget" in result["content"]
+
+    def test_dataset_declarative_to_aac(self) -> None:
+        """Test declarative → AAC for datasets using a fixture-converted dataset."""
+        content = yaml.safe_load((_FIXTURES_DIR / "datasets" / "orders.yaml").read_text())
+        declarative = aac_dataset_to_declarative(content)
+        result = declarative_dataset_to_aac(declarative)
+        assert result["json"]["id"] == "orders"
+        assert isinstance(result["content"], str)
+
+
+# ---------------------------------------------------------------------------
+# Format detection tests
+# ---------------------------------------------------------------------------
+
+
+class TestFormatDetection:
+    def test_detect_aac_with_typed_subdirs(self, tmp_path: Path) -> None:
+        (tmp_path / "datasets").mkdir()
+        (tmp_path / "datasets" / "orders.yaml").write_text("type: dataset\nid: orders\n")
+        assert detect_yaml_format(tmp_path) == "aac"
+
+    def test_detect_aac_with_flat_files(self, tmp_path: Path) -> None:
+        (tmp_path / "orders.yaml").write_text("type: dataset\nid: orders\n")
+        assert detect_yaml_format(tmp_path) == "aac"
+
+    def test_detect_declarative_with_workspaces_dir(self, tmp_path: Path) -> None:
+        (tmp_path / "workspaces").mkdir()
+        assert detect_yaml_format(tmp_path) == "declarative"
+
+    def test_detect_declarative_with_ldm_dir(self, tmp_path: Path) -> None:
+        (tmp_path / "ldm").mkdir()
+        assert detect_yaml_format(tmp_path) == "declarative"
+
+
+# ---------------------------------------------------------------------------
+# Workspace-level load/store tests
+# ---------------------------------------------------------------------------
+
+
+class TestWorkspaceLoadStore:
+    def test_load_aac_workspace_from_fixtures(self) -> None:
+        """Load fixtures excluding dashboards (WASM crypto limitation)."""
+        # Use a temp dir with only datasets, metrics, visualizations
+        import shutil
+        import tempfile
+
+        with tempfile.TemporaryDirectory() as tmp:
+            tmp_path = Path(tmp)
+            for subdir in ("datasets", "metrics", "visualisations"):
+                src = _FIXTURES_DIR / subdir
+                if src.exists():
+                    shutil.copytree(src, tmp_path / subdir)
+
+            model = load_aac_workspace_from_disk(tmp_path)
+            model_dict = model.to_dict(camel_case=True)
+
+            ldm = model_dict.get("ldm", {})
+            analytics = model_dict.get("analytics", {})
+
+            # 2 datasets + 1 date dataset in fixtures
+            assert len(ldm.get("datasets", [])) == 2
+            assert len(ldm.get("dateInstances", [])) == 1
+
+            # 1 metric
+            assert len(analytics.get("metrics", [])) == 1
+
+            # 2 visualizations
+            assert len(analytics.get("visualizationObjects", [])) == 2
+
+    def test_store_and_reload_metrics(self, tmp_path: Path) -> None:
+        """Store metric AAC files, then reload and compare."""
+        # Create a workspace model with just metrics (clean round-trip)
+
+        aac_metrics = [
+            {"id": "m1", "title": "Metric 1", "maql": "SELECT 1", "format": "#,##0"},
+            {"id": "m2", "title": "Metric 2", "maql": "SELECT 2", "format": "#,##0.00"},
+        ]
+        metrics_declarative = [aac_metric_to_declarative(m) for m in aac_metrics]
+
+        model_dict = {"analytics": {"metrics": metrics_declarative}}
+        from gooddata_sdk.catalog.workspace.declarative_model.workspace.workspace import (
+            CatalogDeclarativeWorkspaceModel,
+        )
+
+        model = CatalogDeclarativeWorkspaceModel.from_dict(model_dict)
+        store_aac_workspace_to_disk(model, tmp_path)
+
+        # Verify files were created
+        metric_files = list((tmp_path / "metrics").glob("*.yaml"))
+        assert len(metric_files) == 2
+
+        # Reload
+        reloaded = load_aac_workspace_from_disk(tmp_path)
+        reloaded_dict = reloaded.to_dict(camel_case=True)
+        assert len(reloaded_dict.get("analytics", {}).get("metrics", [])) == 2
+
+    def test_load_ignores_non_workspace_dirs(self, tmp_path: Path) -> None:
+        """Ensure load skips declarative non-workspace directories."""
+        # Create AAC file
+        datasets_dir = tmp_path / "datasets"
+        datasets_dir.mkdir()
+        (datasets_dir / "orders.yaml").write_text(
+            "type: dataset\nid: orders\ntable_path: orders\ntitle: Orders\nprimary_key: order_id\n"
+            "fields:\n  order_id:\n    type: attribute\n    source_column: order_id\n    data_type: STRING\n"
+        )
+        # Create declarative non-workspace dir (should be ignored)
+        users_dir = tmp_path / "users"
+        users_dir.mkdir()
+        (users_dir / "users.yaml").write_text("- id: admin\n  authenticationId: admin\n")
+
+        model = load_aac_workspace_from_disk(tmp_path)
+        model_dict = model.to_dict(camel_case=True)
+        assert len(model_dict.get("ldm", {}).get("datasets", [])) == 1
diff --git a/packages/gooddata-sdk/tests/cli/__init__.py b/packages/gooddata-sdk/tests/cli/__init__.py
new file mode 100644
index 000000000..efe7c60c8
--- /dev/null
+++ b/packages/gooddata-sdk/tests/cli/__init__.py
@@ -0,0 +1 @@
+# (C) 2026 GoodData Corporation
diff --git a/packages/gooddata-sdk/tests/cli/test_gdc.py b/packages/gooddata-sdk/tests/cli/test_gdc.py
new file mode 100644
index 000000000..24c582513
--- /dev/null
+++ b/packages/gooddata-sdk/tests/cli/test_gdc.py
@@ -0,0 +1,49 @@
+# (C) 2026 GoodData Corporation
+from __future__ import annotations
+
+from pathlib import Path
+
+import pytest
+import yaml
+from gooddata_sdk.cli.constants import DEFAULT_SOURCE_DIR
+from gooddata_sdk.cli.deploy import _get_workspace_id
+from gooddata_sdk.cli.gdc_core import _get_source_dir
+
+_FIXTURES_DIR = Path(__file__).parent.parent / "catalog" / "fixtures" / "aac"
+
+
+class TestCliConfig:
+    def test_get_source_dir_from_config(self) -> None:
+        source_dir = _get_source_dir(_FIXTURES_DIR / "gooddata.yaml")
+        assert source_dir == "analytics"
+
+    def test_get_source_dir_default(self, tmp_path: Path) -> None:
+        """When source_dir is not in config, fall back to default."""
+        config = {
+            "profiles": {"default": {"host": "https://h", "token": "t"}},
+            "default_profile": "default",
+        }
+        config_path = tmp_path / "gooddata.yaml"
+        config_path.write_text(yaml.dump(config))
+        source_dir = _get_source_dir(config_path)
+        assert source_dir == DEFAULT_SOURCE_DIR
+
+    def test_get_workspace_id(self) -> None:
+        workspace_id = _get_workspace_id(_FIXTURES_DIR / "gooddata.yaml")
+        assert workspace_id == "test-workspace"
+
+    def test_get_workspace_id_missing(self, tmp_path: Path) -> None:
+        """Raise error when workspace_id is not set in profile."""
+        config = {
+            "profiles": {"default": {"host": "https://h", "token": "t"}},
+            "default_profile": "default",
+        }
+        config_path = tmp_path / "gooddata.yaml"
+        config_path.write_text(yaml.dump(config))
+        with pytest.raises(ValueError, match="workspace_id"):
+            _get_workspace_id(config_path)
+
+    def test_no_nodejs_dependency(self) -> None:
+        """Ensure no Node.js artifacts remain in the CLI module."""
+        cli_dir = Path(__file__).parent.parent.parent / "src" / "gooddata_sdk" / "cli"
+        assert not (cli_dir / "package.json").exists()
diff --git a/scripts/validate_python.sh b/scripts/validate_python.sh
new file mode 100755
index 000000000..4cc4446ff
--- /dev/null
+++ b/scripts/validate_python.sh
@@ -0,0 +1,223 @@
+#!/usr/bin/env bash
+# (C) 2026 GoodData Corporation
+#
+# Python validation wrapper for AIDA validate_command.
+#
+# Contract (streaming-first):
+# - Emits human-readable progress lines to stdout.
+# - Writes raw command output to stderr only when a step fails.
+# - Prints the final JSON result as the last non-empty line on stdout.
+
+set -uo pipefail
+
+TOOL="validate_python"
+
+json_escape() {
+  local s="${1-}"
+  s="${s//\\/\\\\}"
+  s="${s//\"/\\\"}"
+  s="${s//$'\t'/\\t}"
+  s="${s//$'\r'/\\r}"
+  s="${s//$'\n'/\\n}"
+  printf '%s' "$s"
+}
+
+emit_line() {
+  local msg="${2-${1-}}"
+  printf '%s\n' "$msg"
+}
+
+usage() {
+  cat <<'EOF'
+Usage:
+  validate_python.sh --project-path <path> --workspace-root <path> [options]
+
+Options:
+  --scope <scope>          Validation scope: pre_commit or pre_push (default: pre_push)
+                           pre_commit: format,lint,types
+                           pre_push:   format,lint,types,test
+  --steps-csv "<csv>"      Comma-separated steps (overrides --scope defaults)
+  --auto-fix <true|false>  Default: true (uses *-fix Make targets)
+  --test-filter <pattern>  Optional pytest selector (runs uv run pytest -v <pattern>)
+
+  -h, --help               Show help
+EOF
+}
+
+PROJECT_PATH=""
+WORKSPACE_ROOT=""
+SCOPE=""
+STEPS_CSV=""
+AUTO_FIX="true"
+TEST_FILTER=""
+
+while [[ $# -gt 0 ]]; do
+  case "$1" in
+    --project-path) PROJECT_PATH="${2-}"; shift 2 ;;
+    --workspace-root) WORKSPACE_ROOT="${2-}"; shift 2 ;;
+    --scope) SCOPE="${2-}"; shift 2 ;;
+    --steps-csv) STEPS_CSV="${2-}"; shift 2 ;;
+    --auto-fix) AUTO_FIX="${2-}"; shift 2 ;;
+    --test-filter) TEST_FILTER="${2-}"; shift 2 ;;
+    -h|--help) usage; exit 0 ;;
+    *) echo "Unknown arg: $1" >&2; usage >&2; exit 2 ;;
+  esac
+done
+
+if [[ -z "$PROJECT_PATH" || -z "$WORKSPACE_ROOT" ]]; then
+  echo "Missing required args: --project-path and --workspace-root" >&2
+  usage >&2
+  exit 2
+fi
+
+PROJECT_NAME="$(basename "$PROJECT_PATH")"
+
+to_bool() {
+  local v="${1-}"
+  v="$(printf '%s' "$v" | tr '[:upper:]' '[:lower:]')"
+  case "$v" in
+    1|true|yes|on) printf 'true' ;;
+    *) printf 'false' ;;
+  esac
+}
+
+AUTO_FIX_BOOL="$(to_bool "$AUTO_FIX")"
+
+split_csv() {
+  local csv="${1-}"
+  local out=()
+  local item
+  IFS=',' read -r -a out <<<"$csv"
+  for item in "${out[@]}"; do
+    item="$(printf '%s' "$item" | xargs)"
+    if [[ -n "$item" ]]; then
+      printf '%s\n' "$item"
+    fi
+  done
+}
+
+if [[ -n "${STEPS_CSV// }" ]]; then
+  mapfile -t STEPS < <(split_csv "$STEPS_CSV")
+else
+  case "${SCOPE}" in
+    pre_commit)
+      STEPS=("format" "lint" "types")
+      ;;
+    pre_push|"")
+      STEPS=("format" "lint" "types" "test")
+      ;;
+    *)
+      STEPS=("format" "lint" "types" "test")
+      ;;
+  esac
+fi
+
+if [[ ! -d "$PROJECT_PATH" ]]; then
+  emit_line info "Python ${PROJECT_NAME}: project path not found: ${PROJECT_PATH}"
+  printf '{"tool":"%s","success":false,"text":"%s"}\n' \
+    "$(json_escape "$TOOL")" \
+    "$(json_escape "project path not found: ${PROJECT_PATH}")"
+  exit 1
+fi
+
+if [[ ! -f "${PROJECT_PATH%/}/Makefile" ]]; then
+  emit_line info "Python ${PROJECT_NAME}: Makefile missing (required)"
+  printf '{"tool":"%s","success":false,"text":"%s"}\n' \
+    "$(json_escape "$TOOL")" \
+    "$(json_escape "No Makefile found in ${PROJECT_PATH}")"
+  exit 1
+fi
+
+run_in_project() {
+  local label="$1"
+  shift
+  local -a cmd=("$@")
+  local tmp_out
+  tmp_out="$(mktemp)"
+
+  emit_line progress "Python ${PROJECT_NAME}: ${label}"
+
+  (cd "$PROJECT_PATH" && env -u VIRTUAL_ENV "${cmd[@]}") >"$tmp_out" 2>&1
+  local rc=$?
+  if [[ "$rc" -ne 0 ]]; then
+    cat "$tmp_out" >&2
+  fi
+  rm -f "$tmp_out"
+  return "$rc"
+}
+
+run_in_project_capture() {
+  local label="$1"
+  local out_file="$2"
+  shift 2
+  local -a cmd=("$@")
+
+  emit_line progress "Python ${PROJECT_NAME}: ${label}"
+
+  (cd "$PROJECT_PATH" && env -u VIRTUAL_ENV "${cmd[@]}") >"$out_file" 2>&1
+  return $?
+}
+
+has_make_target() {
+  local target="$1"
+  local code
+  (cd "$PROJECT_PATH" && make -q "$target" >/dev/null 2>&1)
+  code=$?
+  [[ $code -eq 0 || $code -eq 1 ]]
+}
+
+FAIL_STEP=""
+
+for step in "${STEPS[@]}"; do
+  case "$step" in
+    format)
+      if [[ "$AUTO_FIX_BOOL" == "true" ]] && has_make_target "format-fix"; then
+        if ! run_in_project "Format (make format-fix)" make format-fix; then FAIL_STEP="Format"; break; fi
+      else
+        if ! run_in_project "Format (make format)" make format; then FAIL_STEP="Format"; break; fi
+      fi
+      ;;
+    lint)
+      if [[ "$AUTO_FIX_BOOL" == "true" ]] && has_make_target "lint-fix"; then
+        if ! run_in_project "Lint (make lint-fix)" make lint-fix; then FAIL_STEP="Lint"; break; fi
+      else
+        if ! run_in_project "Lint (make lint)" make lint; then FAIL_STEP="Lint"; break; fi
+      fi
+      ;;
+    types)
+      tmp_types="$(mktemp)"
+      if run_in_project_capture "Types (make type-check)" "$tmp_types" make type-check; then
+        rm -f "$tmp_types"
+      else
+        cat "$tmp_types" >&2
+        rm -f "$tmp_types"
+        FAIL_STEP="Types"
+        break
+      fi
+      ;;
+    test)
+      if [[ -n "${TEST_FILTER}" ]]; then
+        if ! run_in_project "Test (pytest ${TEST_FILTER})" uv run pytest -v "$TEST_FILTER"; then
+          FAIL_STEP="Test"; break
+        fi
+      else
+        if ! run_in_project "Test (make test)" make test; then FAIL_STEP="Test"; break; fi
+      fi
+      ;;
+    *)
+      emit_line info "Python ${PROJECT_NAME}: skipping unknown step '${step}'"
+      ;;
+  esac
+done
+
+if [[ -n "$FAIL_STEP" ]]; then
+  printf '{"tool":"%s","success":false,"text":"%s"}\n' \
+    "$(json_escape "$TOOL")" \
+    "$(json_escape "Python ${PROJECT_NAME}: FAILED at ${FAIL_STEP}")"
+  exit 1
+fi
+
+printf '{"tool":"%s","success":true,"text":"%s"}\n' \
+  "$(json_escape "$TOOL")" \
+  "$(json_escape "Python ${PROJECT_NAME}: PASSED")"
+exit 0
diff --git a/uv.lock b/uv.lock
index cb9d80d13..183ce813a 100644
--- a/uv.lock
+++ b/uv.lock
@@ -754,6 +754,17 @@ requires-dist = [
     { name = "urllib3", specifier = ">=2.6.1" },
 ]
 
+[[package]]
+name = "gooddata-code-convertors"
+version = "11.28.0a15"
+source = { registry = "https://pypi.org/simple" }
+dependencies = [
+    { name = "wasmtime" },
+]
+wheels = [
+    { url = "https://files.pythonhosted.org/packages/05/74/9b26234b7e255b8977843fbf843a0a533e304510d75ddbd11dd98fbf8f79/gooddata_code_convertors-11.28.0a15-py3-none-any.whl", hash = "sha256:b583372a9e3a12551b930b4506e109e2f12ff7ff1a938ca2731b72ab7675a8f6", size = 1103444, upload-time = "2026-04-01T08:23:01.969Z" },
+]
+
 [[package]]
 name = "gooddata-dbt"
 version = "1.62.0"
@@ -1104,6 +1115,7 @@ dependencies = [
     { name = "brotli" },
     { name = "cattrs" },
     { name = "gooddata-api-client" },
+    { name = "gooddata-code-convertors" },
     { name = "python-dateutil" },
     { name = "python-dotenv" },
     { name = "pyyaml" },
@@ -1130,6 +1142,7 @@ requires-dist = [
     { name = "brotli", specifier = "==1.2.0" },
     { name = "cattrs", specifier = ">=22.1.0,<=24.1.1" },
     { name = "gooddata-api-client", editable = "gooddata-api-client" },
+    { name = "gooddata-code-convertors" },
     { name = "python-dateutil", specifier = ">=2.5.3" },
     { name = "python-dotenv", specifier = ">=1.0.0,<2.0.0" },
     { name = "pyyaml", specifier = ">=6.0" },
@@ -1215,6 +1228,15 @@ wheels = [
     { url = "https://files.pythonhosted.org/packages/fa/5e/f8e9a1d23b9c20a551a8a02ea3637b4642e22c2626e3a13a9a29cdea99eb/importlib_metadata-8.7.1-py3-none-any.whl", hash = "sha256:5a1f80bf1daa489495071efbb095d75a634cf28a8bc299581244063b53176151", size = 27865, upload-time = "2025-12-21T10:00:18.329Z" },
 ]
 
+[[package]]
+name = "importlib-resources"
+version = "6.5.2"
+source = { registry = "https://pypi.org/simple" }
+sdist = { url = "https://files.pythonhosted.org/packages/cf/8c/f834fbf984f691b4f7ff60f50b514cc3de5cc08abfc3295564dd89c5e2e7/importlib_resources-6.5.2.tar.gz", hash = "sha256:185f87adef5bcc288449d98fb4fba07cea78bc036455dd44c5fc4a2fe78fed2c", size = 44693, upload-time = "2025-01-03T18:51:56.698Z" }
+wheels = [
+    { url = "https://files.pythonhosted.org/packages/a4/ed/1f1afb2e9e7f38a545d628f864d562a5ae64fe6f7a10e28ffb9b185b4e89/importlib_resources-6.5.2-py3-none-any.whl", hash = "sha256:789cfdc3ed28c78b67a06acb8126751ced69a3d5f79c095a98298cd8a760ccec", size = 37461, upload-time = "2025-01-03T18:51:54.306Z" },
+]
+
 [[package]]
 name = "iniconfig"
 version = "2.3.0"
@@ -2784,6 +2806,23 @@ wheels = [
     { url = "https://files.pythonhosted.org/packages/42/d7/394801755d4c8684b655d35c665aea7836ec68320304f62ab3c94395b442/virtualenv-20.38.0-py3-none-any.whl", hash = "sha256:d6e78e5889de3a4742df2d3d44e779366325a90cf356f15621fddace82431794", size = 5837778, upload-time = "2026-02-19T07:47:59.778Z" },
 ]
 
+[[package]]
+name = "wasmtime"
+version = "30.0.0"
+source = { registry = "https://pypi.org/simple" }
+dependencies = [
+    { name = "importlib-resources" },
+]
+wheels = [
+    { url = "https://files.pythonhosted.org/packages/31/0c/290dd5081c7c99d39bf85c5315a88c53079c5fe777ba6264f49cefed6362/wasmtime-30.0.0-py3-none-macosx_10_13_x86_64.whl", hash = "sha256:578378ab33c9b046e74d44461eedd6fe4e4fca8522caa7f251123490263dabbf", size = 7040481, upload-time = "2025-02-20T16:26:20.322Z" },
+    { url = "https://files.pythonhosted.org/packages/1c/4d/b127fab50719ad64cf5feef47daa5d0967ce0b1d96b8061ed2955b92d660/wasmtime-30.0.0-py3-none-macosx_11_0_arm64.whl", hash = "sha256:71423e8f56f7376ef1e5e2f560f2c51818213fc5d6f1a10dcf1d46b337cf9476", size = 6378107, upload-time = "2025-02-20T16:26:23.368Z" },
+    { url = "https://files.pythonhosted.org/packages/44/aa/630ebb7a1dc8202da6b0d4d218b257203dc5df1571b6d9a9fe231cac9dfe/wasmtime-30.0.0-py3-none-manylinux1_x86_64.whl", hash = "sha256:26af8a74e0f5786ee01ec8398621a268e6696d3b8e25d66f5d0ec931357f683a", size = 7471161, upload-time = "2025-02-20T16:26:26.906Z" },
+    { url = "https://files.pythonhosted.org/packages/2c/f8/c13505b4506b117f6adffba9980d224c14922718dc437213447659db5c35/wasmtime-30.0.0-py3-none-manylinux2014_aarch64.whl", hash = "sha256:cac51ab4e91a2f44bdae88153859cef72a0c47438ef976ab18d90fa12d0c354e", size = 6958245, upload-time = "2025-02-20T16:26:29.068Z" },
+    { url = "https://files.pythonhosted.org/packages/f6/e1/ed753bf0dc18c460feec06197f21f9c96709640990712bb6c6f075aee753/wasmtime-30.0.0-py3-none-musllinux_1_2_x86_64.whl", hash = "sha256:3964f0cf115e3c8dbd120a2b0eda6744fda10648a9e465930b81bdc876bcba36", size = 7481754, upload-time = "2025-02-20T16:26:31.901Z" },
+    { url = "https://files.pythonhosted.org/packages/7d/53/ed6efad1505014abb7634fc2aa61aa7b521e45dce6d17fcb8180757a459e/wasmtime-30.0.0-py3-none-win_amd64.whl", hash = "sha256:651d8c0fa75b10840906a96530bac09937af7510a38346e1d0391f0240057f58", size = 5866033, upload-time = "2025-02-20T16:26:35.781Z" },
+    { url = "https://files.pythonhosted.org/packages/67/09/e0a2a218d5292f017d41665a47bc672bd00533b3c0c9eb11316b4fd9fa56/wasmtime-30.0.0-py3-none-win_arm64.whl", hash = "sha256:0fcc47ca1b5ccc303167e58a89c2b9865928d8c024ee1481a4f2cf75dcc4eb70", size = 5375297, upload-time = "2025-02-20T16:26:39.611Z" },
+]
+
 [[package]]
 name = "werkzeug"
 version = "3.1.5"