The Claude 4.6 model family supports Parallel Tool Use, allowing the model to trigger multiple tools (e.g., searching 3 distinct databases) in a single turn. While powerful, this can be complex to handle. If your backend cannot handle concurrency, you should set disable_parallel_tool_use: true to force Claude to iterate through actions one-by-one.
When a tool call fails in your code (e.g., a database timeout), you must feed that error back to Claude using the is_error: true property in the tool_result object. This prevents Claude from hallucinating fake data and instead triggers a 'recovery' reasoning path where it might try a different tool or notify the user.
Claude now supports Programmatic Tool Calling, where the model orchestrates tools through Python code rather than individual API round-trips. This dramatically reduces latency by allowing multiple tool calls to be processed in a single inference pass. The model writes executable code that calls your tools, which the orchestrator runs and returns results from in batch.
For agents with large tool libraries (50+ tools), Anthropic introduced the Tool Search Tool. Instead of stuffing all tool schemas into the context window (which wastes tokens and confuses the model), Claude uses a search mechanism to dynamically discover and load only the relevant tools for the current task.