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docs: improve formatting consistency in tools documentation
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docs/tools.md

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@@ -288,9 +288,9 @@ async def run_my_agent() -> str:
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In certain cases, you might want to modify the output of the tool-agents before returning it to the central agent. This may be useful if you want to:
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- Extract a specific piece of information (e.g., a JSON payload) from the sub-agent's chat history.
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- Convert or reformat the agent’s final answer (e.g., transform Markdown into plain text or CSV).
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- Validate the output or provide a fallback value when the agent’s response is missing or malformed.
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- Extract a specific piece of information (e.g., a JSON payload) from the sub-agent's chat history.
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- Convert or reformat the agent’s final answer (e.g., transform Markdown into plain text or CSV).
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- Validate the output or provide a fallback value when the agent’s response is missing or malformed.
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You can do this by supplying the `custom_output_extractor` argument to the `as_tool` method:
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@@ -369,15 +369,17 @@ asyncio.run(main())
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```
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The `is_enabled` parameter accepts:
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- **Boolean values**: `True` (always enabled) or `False` (always disabled)
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- **Callable functions**: Functions that take `(context, agent)` and return a boolean
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- **Async functions**: Async functions for complex conditional logic
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- **Boolean values**: `True` (always enabled) or `False` (always disabled)
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- **Callable functions**: Functions that take `(context, agent)` and return a boolean
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- **Async functions**: Async functions for complex conditional logic
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Disabled tools are completely hidden from the LLM at runtime, making this useful for:
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- Feature gating based on user permissions
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- Environment-specific tool availability (dev vs prod)
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- A/B testing different tool configurations
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- Dynamic tool filtering based on runtime state
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- Feature gating based on user permissions
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- Environment-specific tool availability (dev vs prod)
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- A/B testing different tool configurations
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- Dynamic tool filtering based on runtime state
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## Handling errors in function tools
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