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Remove unified categoried from the README and docs
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CLAUDE.md

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@@ -68,7 +68,7 @@ All tool definitions are generated from OpenAPI specs in `stackone_ai/oas/`:
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```python
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# Use glob patterns for tool selection
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tools = StackOneToolSet(include_tools=["hris_*", "!hris_create_*"])
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tools = StackOneToolSet(include_tools=["bamboohr_*", "!bamboohr_create_*"])
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```
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### Authentication

README.md

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@@ -59,10 +59,10 @@ toolset = StackOneToolSet() # Uses STACKONE_API_KEY env var
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# Or explicitly: toolset = StackOneToolSet(api_key="your-api-key")
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# Get HRIS-related tools with glob patterns
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tools = toolset.fetch_tools(actions=["hris_*"], account_ids=["your-account-id"])
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tools = toolset.fetch_tools(actions=["bamboohr_*"], account_ids=["your-account-id"])
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# Use a specific tool with the call method
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employee_tool = tools.get_tool("hris_get_employee")
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employee_tool = tools.get_tool("bamboohr_get_employee")
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# Call with keyword arguments
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employee = employee_tool.call(id="employee-id")
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# Or with traditional execute method
@@ -108,9 +108,9 @@ tools = toolset.fetch_tools(providers=["hibob"])
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- **`account_ids`**: Filter tools by account IDs. Tools will be loaded for each specified account.
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- **`providers`**: Filter by provider names (e.g., `["hibob", "bamboohr"]`). Case-insensitive matching.
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- **`actions`**: Filter by action patterns with glob support:
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- Exact match: `["hris_list_employees"]`
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- Exact match: `["bamboohr_list_employees"]`
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- Glob pattern: `["*_list_employees"]` matches all tools ending with `_list_employees`
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- Provider prefix: `["hris_*"]` matches all HRIS tools
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- Provider prefix: `["bamboohr_*"]` matches all BambooHR tools
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## Implicit Feedback (Beta)
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@@ -170,7 +170,7 @@ from stackone_ai import StackOneToolSet
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# Initialize StackOne tools
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toolset = StackOneToolSet()
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tools = toolset.fetch_tools(actions=["hris_*"], account_ids=["your-account-id"])
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tools = toolset.fetch_tools(actions=["bamboohr_*"], account_ids=["your-account-id"])
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# Convert to LangChain format
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langchain_tools = tools.to_langchain()
@@ -217,7 +217,7 @@ from stackone_ai.integrations.langgraph import to_tool_node, bind_model_with_too
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# Prepare tools
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toolset = StackOneToolSet()
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tools = toolset.fetch_tools(actions=["hris_*"], account_ids=["your-account-id"])
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tools = toolset.fetch_tools(actions=["bamboohr_*"], account_ids=["your-account-id"])
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langchain_tools = tools.to_langchain()
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class State(TypedDict):
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# Get tools and convert to LangChain format
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toolset = StackOneToolSet()
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tools = toolset.fetch_tools(actions=["hris_*"], account_ids=["your-account-id"])
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tools = toolset.fetch_tools(actions=["bamboohr_*"], account_ids=["your-account-id"])
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langchain_tools = tools.to_langchain()
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# Create CrewAI agent with StackOne tools
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result = feedback_tool.call(
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feedback="The HRIS tools are working great! Very fast response times.",
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account_id="acc_123456",
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tool_names=["hris_list_employees", "hris_get_employee"]
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tool_names=["bamboohr_list_employees", "bamboohr_get_employee"]
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)
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```
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@@ -327,7 +327,7 @@ tools[0](limit=10)
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## Semantic Search
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Discover tools using natural language instead of exact names. Queries like "onboard new hire" resolve to the right actions even when the tool is called `hris_create_employee`.
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Discover tools using natural language instead of exact names. Queries like "onboard new hire" resolve to the right actions even when the tool is called `bamboohr_create_employee`.
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```python
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from stackone_ai import StackOneToolSet

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