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Messages/Tools

Tool Runner (SDK)

Use the SDK's Tool Runner abstraction to handle the agentic loop, error wrapping, and type safety automatically.

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  • Basic usage
  • Iterating over the tool runner
  • Advanced usage
  • Debugging tool execution
  • Intercepting tool errors
  • Modifying tool results
  • Streaming
  • Next steps

Tool Runner handles the agentic loop, error wrapping, and type safety so you don't have to. Use the manual loop only when you need human-in-the-loop approval, custom logging, or conditional execution. Available in Python, TypeScript, and Ruby SDKs.

The tool runner provides an out-of-the-box solution for executing tools with Claude. Instead of manually handling tool calls, tool results, and conversation management, the tool runner automatically:

  • Executes tools when Claude calls them
  • Handles the request/response cycle
  • Manages conversation state
  • Provides type safety and validation

Use the tool runner for most tool use implementations.

The tool runner is currently in beta and available in the Python, TypeScript, and Ruby SDKs.

Automatic context management with compaction

The tool runner supports automatic compaction, which generates summaries when token usage exceeds a threshold. This allows long-running agentic tasks to continue beyond context window limits.

Basic usage

Define tools using the SDK helpers, then use the tool runner to execute them.

The tool function must return a content block or content block array, including text, images, or document blocks. This allows tools to return rich, multimodal responses. Returned strings are converted to a text content block. If you want to return a structured JSON object to Claude, encode it to a JSON string before returning it. Numbers, booleans, or other non-string primitives must also be converted to strings.

Iterating over the tool runner

The tool runner is an iterable that yields messages from Claude. This is often referred to as a "tool call loop". Each iteration, the runner checks if Claude requested a tool use. If so, it calls the tool and sends the result back to Claude automatically, then yields the next message from Claude to continue your loop.

You can end the loop at any iteration with a break statement. The runner loops until Claude returns a message without a tool use.

If you don't need intermediate messages, you can get the final message directly:

Advanced usage

Within the loop, you can fully customize the tool runner's next request to the Messages API. The runner automatically appends tool results to the message history, so you don't need to manually manage them. You can optionally inspect the tool result for logging or debugging, and modify the request parameters before the next API call.

Debugging tool execution

When a tool throws an exception, the tool runner catches it and returns the error to Claude as a tool result with is_error: true. By default, only the exception message is included, not the full stack trace.

To view full stack traces and debug information, set the ANTHROPIC_LOG environment variable:

# View info-level logs including tool errors
export ANTHROPIC_LOG=info

# View debug-level logs for more verbose output
export ANTHROPIC_LOG=debug

When enabled, the SDK logs full exception details (using Python's logging module, the console in TypeScript, or Ruby's logger), including the complete stack trace when a tool fails.

Intercepting tool errors

By default, tool errors are passed back to Claude, which can then respond appropriately. However, you may want to detect errors and handle them differently, for example, to stop execution early or implement custom error handling.

Use the tool response method to intercept tool results and check for errors before they're sent to Claude:

Modifying tool results

You can modify tool results before they're sent back to Claude. This is useful for adding metadata such as cache_control to enable prompt caching on tool results, or for transforming the tool output.

Use the tool response method to get the tool result, then modify it before the runner proceeds. Whether you explicitly append the modified result or mutate it in place depends on the SDK; see the code comments in each tab.

Adding cache_control to tool results is particularly useful when tools return large amounts of data (such as document search results) that you want to cache for subsequent API calls. See Prompt caching for more details on caching strategies.

Streaming

Enable streaming to receive events as they arrive. Each iteration yields a stream object that you can iterate for events.

Next steps

  • For manual control over the tool-call loop, see Handle tool calls.
  • For running multiple tools concurrently, see Parallel tool use.
  • For the full tool-use workflow, see Define tools.