fix: component tool schema description

haystack/tools/component_tool.py

@@ -337,7 +337,7 @@ def _create_tool_parameters_schema(self, component: Component, inputs_from_state
         :raises SchemaGenerationError: If schema generation fails
         :returns: OpenAI tools schema for the component's run method parameters.
         """
-        component_run_description, param_descriptions = _get_component_param_descriptions(component)
+        param_descriptions = _get_component_param_descriptions(component)
 
         # collect fields (types and defaults) and descriptions from function parameters
         fields: dict[str, Any] = {}
@@ -365,7 +365,9 @@ def _create_tool_parameters_schema(self, component: Component, inputs_from_state
 
         parameters_schema: dict[str, Any] = {}
         try:
-            model = create_model(component.run.__name__, __doc__=component_run_description, **fields)
+            # No `__doc__`: it would surface as a top-level `description` on the parameters schema,
+            # which LLM providers ignore. The component description feeds the tool-level description.
+            model = create_model(component.run.__name__, **fields)
             parameters_schema = model.model_json_schema()
         except Exception as e:
             raise SchemaGenerationError(

haystack/tools/parameters_schema_utils.py

@@ -102,47 +102,34 @@ def _get_param_descriptions(method: Callable) -> tuple[str, dict[str, str]]:
     return parsed_doc.short_description or "", param_descriptions
 
 
-def _get_component_param_descriptions(component: Any) -> tuple[str, dict[str, str]]:
+def _get_component_param_descriptions(component: Any) -> dict[str, str]:
     """
     Get parameter descriptions from a component, handling both regular Components and SuperComponents.
 
     For regular components, this extracts descriptions from the run method's docstring.
     For SuperComponents, this extracts descriptions from the underlying pipeline components.
 
     :param component: The component to extract parameter descriptions from
-    :returns: A tuple of (short_description, param_descriptions)
+    :returns: A dictionary mapping parameter names to their descriptions
     """
     from haystack.core.super_component.super_component import _SuperComponent
 
     # Get descriptions from the component's run method
-    short_desc, param_descriptions = _get_param_descriptions(component.run)
+    _, param_descriptions = _get_param_descriptions(component.run)
 
-    # If it's a SuperComponent, enhance the descriptions from the original components
+    # If it's a SuperComponent, enhance the parameter descriptions from the original components
     if isinstance(component, _SuperComponent):
-        # Collect descriptions from components in the pipeline
-        component_descriptions = []
-        processed_components = set()
-
-        # First gather descriptions from all components that have inputs mapped
         for super_param_name, pipeline_paths in component.input_mapping.items():
             # Collect descriptions from all mapped components
             descriptions = []
             for path in pipeline_paths:
                 try:
-                    # Get the component and socket this input is mapped fromq
+                    # Get the component and socket this input is mapped from
                     comp_name, socket_name = component._split_component_path(path)
                     pipeline_component = component.pipeline.get_component(comp_name)
 
-                    # Get run method descriptions for this component
-                    run_desc, run_param_descriptions = _get_param_descriptions(pipeline_component.run)
-
-                    # Don't add the same component description multiple times
-                    if comp_name not in processed_components:
-                        processed_components.add(comp_name)
-                        if run_desc:
-                            component_descriptions.append(f"'{comp_name}': {run_desc}")
-
                     # Add parameter description if available
+                    _, run_param_descriptions = _get_param_descriptions(pipeline_component.run)
                     if input_param_mapping := run_param_descriptions.get(socket_name):
                         descriptions.append(f"Provided to the '{comp_name}' component as: '{input_param_mapping}'")
                 except Exception as e:
@@ -153,20 +140,12 @@ def _get_component_param_descriptions(component: Any) -> tuple[str, dict[str, st
                         e=str(e),
                     )
 
-            # We don't only handle a one to one description mapping of input parameters, but a one to many mapping.
-            # i.e. for a combined_input parameter description:
-            # super_comp = SuperComponent(
-            #   pipeline=pipeline,
-            #   input_mapping={"combined_input": ["comp_a.query", "comp_b.text"]},
-            # )
+            # A single SuperComponent input can map to multiple pipeline components, e.g.
+            # input_mapping={"combined_input": ["comp_a.query", "comp_b.text"]}
             if descriptions:
                 param_descriptions[super_param_name] = ", and ".join(descriptions) + "."
 
-        # We also create a combined description for the SuperComponent based on its components
-        if component_descriptions:
-            short_desc = f"A component that combines: {', '.join(component_descriptions)}"
-
-    return short_desc, param_descriptions
+    return param_descriptions
 
 
 def _dataclass_to_pydantic_model(dc_type: Any) -> type[BaseModel]:

releasenotes/notes/component-tool-schema-description-b3e47b8bc4742f9c.yaml

@@ -0,0 +1,9 @@
+---
+fixes:
+  - |
+    ``ComponentTool`` no longer adds a top-level ``description`` key to the generated ``parameters``
+    JSON schema. The wrapped component's docstring was emitted inside the parameters schema, where
+    LLM providers (OpenAI, Anthropic, Google) do not use it, and for tools wrapping a
+    ``SuperComponent`` it produced a confusing auto-generated summary. The parameters schema now only
+    carries per-parameter descriptions, matching plain ``Tool`` and function-based tools. The
+    tool-level ``description`` is unchanged.

test/tools/test_component_tool.py

@@ -179,7 +179,6 @@ def test_from_component_basic(self):
         assert tool.description == "A simple component that generates text."
         assert tool.parameters == {
             "type": "object",
-            "description": "A simple component that generates text.",
             "properties": {"text": {"type": "string", "description": "user's name"}},
             "required": ["text"],
         }
@@ -198,21 +197,13 @@ def test_from_component_with_inputs_from_state(self):
         tool = ComponentTool(component=SimpleComponent(), inputs_from_state={"text": "text"})
         assert tool.inputs_from_state == {"text": "text"}
         # Inputs should be excluded from schema generation
-        assert tool.parameters == {
-            "type": "object",
-            "properties": {},
-            "description": "A simple component that generates text.",
-        }
+        assert tool.parameters == {"type": "object", "properties": {}}
 
     def test_from_component_with_inputs_from_state_different_names(self):
         tool = ComponentTool(component=SimpleComponent(), inputs_from_state={"state_text": "text"})
         assert tool.inputs_from_state == {"state_text": "text"}
         # Inputs should be excluded from schema generation
-        assert tool.parameters == {
-            "type": "object",
-            "properties": {},
-            "description": "A simple component that generates text.",
-        }
+        assert tool.parameters == {"type": "object", "properties": {}}
 
     def test_from_component_with_invalid_inputs_from_state_nested_dict(self):
         """Test that ComponentTool rejects nested dict format for inputs_from_state"""
@@ -240,7 +231,6 @@ def test_from_component_with_dataclass(self):
                     "type": "object",
                 }
             },
-            "description": "A simple component that processes a User.",
             "properties": {"user": {"$ref": "#/$defs/User", "description": "The User object to process."}},
             "required": ["user"],
             "type": "object",
@@ -262,7 +252,6 @@ def test_from_component_with_list_input(self):
 
         assert tool.parameters == {
             "type": "object",
-            "description": "Concatenates a list of strings into a single string.",
             "properties": {
                 "texts": {
                     "type": "array",
@@ -303,7 +292,6 @@ def test_from_component_with_nested_dataclass(self):
                     "type": "object",
                 },
             },
-            "description": "Creates information about the person.",
             "properties": {"person": {"$ref": "#/$defs/Person", "description": "The Person to process."}},
             "required": ["person"],
             "type": "object",
@@ -328,7 +316,6 @@ def test_from_component_with_list_of_documents(self):
                 "Document": DOCUMENT_SCHEMA,
                 "SparseEmbedding": SPARSE_EMBEDDING_SCHEMA,
             },
-            "description": "Concatenates the content of multiple documents with newlines.",
             "properties": {
                 "documents": {
                     "description": "List of Documents whose content will be concatenated",
@@ -351,7 +338,6 @@ def test_from_component_with_dynamic_input_types(self):
         builder = PromptBuilder(template="Hello, {{name}}!")
         tool = ComponentTool(component=builder, name="prompt_builder_tool")
         assert tool.parameters == {
-            "description": "Renders the prompt template with the provided variables.",
             "properties": {
                 "name": {"description": "Input 'name' for the component."},
                 "template": {
@@ -417,10 +403,9 @@ def run(self, text: str, number: int = 42) -> dict[str, str]:
         # Create ComponentTool from SuperComponent
         tool = ComponentTool(component=super_comp, name="text_processor")
 
-        # Verify that schema includes the docstrings from the original component
+        # Verify that schema includes the per-parameter docstrings from the original component
         assert tool.parameters == {
             "type": "object",
-            "description": "A component that combines: 'processor': Process inputs and return result.",
             "properties": {
                 "input_text": {
                     "type": "string",
@@ -484,11 +469,9 @@ def run(self, text: str) -> dict[str, str]:
         # Create ComponentTool from SuperComponent
         tool = ComponentTool(component=super_comp, name="combined_processor")
 
-        # Verify that schema includes combined docstrings from both components
+        # Verify that schema includes combined per-parameter docstrings from both components
         assert tool.parameters == {
             "type": "object",
-            "description": "A component that combines: 'comp_a': Process query in component A., 'comp_b': Process "
-            "text in component B.",
             "properties": {
                 "combined_input": {
                     "type": "string",

test/tools/test_pipeline_tool.py

@@ -164,9 +164,6 @@ def test_auto_generated_tool_params(self, sample_pipeline):
         )
 
         assert tool.parameters == {
-            "description": "A component that combines: 'bm25_retriever': Run the InMemoryBM25Retriever on the "
-            "given input data., 'ranker': Returns a list of documents ranked by their similarity "
-            "to the given query.",
             "properties": {
                 "query": {
                     "description": "Provided to the 'bm25_retriever' component as: 'The query string for the Retriever."
@@ -182,9 +179,6 @@ def test_auto_generated_tool_params(self, sample_pipeline):
     def test_auto_generated_tool_params_no_mappings(self, sample_pipeline):
         tool = PipelineTool(pipeline=sample_pipeline, name="test_tool", description="A test tool")
         assert tool.parameters == {
-            "description": "A component that combines: 'bm25_retriever': Run the InMemoryBM25Retriever on the given "
-            "input data., 'ranker': Returns a list of documents ranked by their similarity to the "
-            "given query.",
             "properties": {
                 "query": {
                     "description": "Provided to the 'bm25_retriever' component as: 'The query string for the "