docs: update comments to use "Meta Search Tools" terminology

Updated all references from "meta tools" to "meta search tools" in:

- README.md section headers and descriptions

- stackone_ai/meta_search_tools.py docstrings and comments

- stackone_ai/models.py method documentation

- tests/test_meta_search_tools.py test descriptions

- examples/meta_search_tools_example.py comments and output

Author: ryoppippi

README.md

@@ -30,12 +30,12 @@ employee = employee_tool.call(id="employee-id")
 employee = employee_tool.execute({"id": "employee-id"})
 ```
 
-## Meta Tools (Beta)
+## Meta Search Tools (Beta)
 
-Meta tools enable dynamic tool discovery and execution without hardcoding tool names:
+Meta search tools enable dynamic tool discovery and execution without hardcoding tool names:
 
 ```python
-# Get meta tools for dynamic discovery
+# Get meta search tools for dynamic discovery
 tools = toolset.get_tools("hris_*")
 meta_tools = tools.meta_search_tools()
 
@@ -54,7 +54,7 @@ result = execute_tool.call(toolName="hris_list_employees", params={"limit": 10})
 - AI-friendly tool descriptions and parameters
 - **Tool Calling**: Direct method calling with `tool.call()` for intuitive usage
 - **Glob Pattern Filtering**: Advanced tool filtering with patterns like `"hris_*"` and exclusions `"!hris_delete_*"`
-- **Meta Tools** (Beta): Dynamic tool discovery and execution based on natural language queries
+- **Meta Search Tools** (Beta): Dynamic tool discovery and execution based on natural language queries
 - Integration with popular AI frameworks:
   - OpenAI Functions
   - LangChain Tools

examples/meta_search_tools_example.py

@@ -1,8 +1,8 @@
 #!/usr/bin/env python
 """
-Example demonstrating meta tools for dynamic tool discovery and execution.
+Example demonstrating meta search tools for dynamic tool discovery and execution.
 
-Meta tools allow AI agents to search for relevant tools based on natural language queries
+Meta search tools allow AI agents to search for relevant tools based on natural language queries
 and execute them dynamically without hardcoding tool names.
 """
 
@@ -17,7 +17,7 @@
 
 
 def example_meta_tools_basic():
-    """Basic example of using meta tools for tool discovery"""
+    """Basic example of using meta search tools for tool discovery"""
     print("🔍 Example 1: Dynamic tool discovery\n")
 
     # Initialize StackOne toolset
@@ -27,7 +27,7 @@ def example_meta_tools_basic():
     all_tools = toolset.get_tools("hris_*")
     print(f"Total HRIS tools available: {len(all_tools)}")
 
-    # Get meta tools for dynamic discovery
+    # Get meta search tools for dynamic discovery
     meta_tools = all_tools.meta_search_tools()
 
     # Get the filter tool to search for relevant tools
@@ -113,8 +113,8 @@ def example_tool_calling():
 
 
 def example_with_openai():
-    """Example of using meta tools with OpenAI"""
-    print("🤖 Example 4: Using meta tools with OpenAI\n")
+    """Example of using meta search tools with OpenAI"""
+    print("🤖 Example 4: Using meta search tools with OpenAI\n")
 
     try:
         from openai import OpenAI
@@ -125,14 +125,14 @@ def example_with_openai():
         # Initialize StackOne toolset
         toolset = StackOneToolSet()
 
-        # Get HRIS tools and their meta tools
+        # Get HRIS tools and their meta search tools
         hris_tools = toolset.get_tools("hris_*")
         meta_tools = hris_tools.meta_search_tools()
 
         # Convert to OpenAI format
         openai_tools = meta_tools.to_openai()
 
-        # Create a chat completion with meta tools
+        # Create a chat completion with meta search tools
         response = client.chat.completions.create(
             model="gpt-4",
             messages=[
@@ -177,7 +177,7 @@ def example_with_langchain():
         tools = toolset.get_tools("hris_list_*")
         langchain_tools = tools.to_langchain()
 
-        # Get meta tools as well
+        # Get meta search tools as well
         meta_tools = tools.meta_search_tools()
         langchain_meta_tools = meta_tools.to_langchain()
 
@@ -195,7 +195,7 @@ def example_with_langchain():
             [
                 (
                     "system",
-                    "You are an HR assistant. Use the meta tools to discover and execute relevant tools.",
+                    "You are an HR assistant. Use the meta search tools to discover and execute relevant tools.",
                 ),
                 ("human", "{input}"),
                 ("placeholder", "{agent_scratchpad}"),
@@ -222,7 +222,7 @@ def example_with_langchain():
 def main():
     """Run all examples"""
     print("=" * 60)
-    print("StackOne AI SDK - Meta Tools & Tool Calling Examples")
+    print("StackOne AI SDK - Meta Search Tools & Tool Calling Examples")
     print("=" * 60)
     print()
 

stackone_ai/meta_search_tools.py

@@ -1,4 +1,4 @@
-"""Meta tools for dynamic tool discovery and execution"""
+"""Meta search tools for dynamic tool discovery and execution"""
 
 from __future__ import annotations
 
@@ -175,7 +175,7 @@ def execute_filter(arguments: str | JsonDict | None = None) -> JsonDict:
     execute_config = ExecuteConfig(
         name=name,
         method="POST",
-        url="",  # Meta tools don't make HTTP requests
+        url="",  # Meta search tools don't make HTTP requests
         headers={},
     )
 
@@ -188,7 +188,7 @@ def __init__(self) -> None:
                 description=description,
                 parameters=parameters,
                 _execute_config=execute_config,
-                _api_key="",  # Meta tools don't need API key
+                _api_key="",  # Meta search tools don't need API key
                 _account_id=None,
             )
 
@@ -254,7 +254,7 @@ def execute_tool(arguments: str | JsonDict | None = None) -> JsonDict:
     execute_config = ExecuteConfig(
         name=name,
         method="POST",
-        url="",  # Meta tools don't make HTTP requests
+        url="",  # Meta search tools don't make HTTP requests
         headers={},
     )
 
@@ -267,7 +267,7 @@ def __init__(self) -> None:
                 description=description,
                 parameters=parameters,
                 _execute_config=execute_config,
-                _api_key="",  # Meta tools don't need API key
+                _api_key="",  # Meta search tools don't need API key
                 _account_id=None,
             )
 

stackone_ai/models.py

@@ -481,9 +481,9 @@ def to_langchain(self) -> Sequence[BaseTool]:
         return [tool.to_langchain() for tool in self.tools]
 
     def meta_search_tools(self) -> "Tools":
-        """Return meta tools for tool discovery and execution
+        """Return meta search tools for tool discovery and execution
 
-        Meta tools enable dynamic tool discovery and execution based on natural language queries.
+        Meta search tools enable dynamic tool discovery and execution based on natural language queries.
 
         Returns:
             Tools collection containing meta_filter_relevant_tools and meta_execute_tool
@@ -500,7 +500,7 @@ def meta_search_tools(self) -> "Tools":
         # Create search index
         index = ToolIndex(self.tools)
 
-        # Create meta tools
+        # Create meta search tools
         filter_tool = create_meta_search_tools_filter_tool(index)
         execute_tool = create_meta_search_tools_execute_tool(self)
 

tests/test_meta_search_tools.py

@@ -1,4 +1,4 @@
-"""Tests for meta tools functionality"""
+"""Tests for meta search tools functionality"""
 
 import pytest
 import responses