What this error means

[Bug] append_messages() inside tool runner loop causes infinite loop (advanced usage docs example) is a Anthropic API failure pattern reported for developers trying to fix infinite loop in anthropic sdk tool runner when calling append_messages() inside the loop iteration — tool results never reach history causing model to re-call same tool. Based on the imported evidence, treat this as a tool-specific troubleshooting page rather than a generic API error.

Why this happens

GitHub Issue #1536 in anthropics/anthropic-sdk-python, fixed by PR #1594 (opened May 23, 2026). Root cause: _messages_modified flag set by append_messages bypasses auto-append of assistant message + tool result. This matches the official documentation example. Not in covered-errors.md.

Common causes

  • GitHub Issue #1536 in anthropics/anthropic-sdk-python, fixed by PR #1594 (opened May 23, 2026). Root cause: _messages_modified flag set by append_messages bypasses auto-append of assistant message + tool result. This matches the official documentation example. Not in covered-errors.md.

Quick fixes

  1. Confirm the exact error signature matches [Bug] append_messages() inside tool runner loop causes infinite loop (advanced usage docs example).
  2. Check the Anthropic API account, local tool state, and provider configuration involved in the failing workflow.
  3. Compare the failing environment with a known working setup, then change one configuration value at a time.

Platform/tool-specific checks

  • Verify the command, editor, extension, or API client that produced the error.
  • Compare local settings with CI, deployment, or editor-level settings when the error appears in only one environment.
  • Avoid deleting credentials, local model data, or project settings until the failing scope is clear.

Step-by-step troubleshooting

  1. Capture the exact error message and the command, editor action, or request that triggered it.
  2. Check whether the failure is account/auth, quota/rate, model/provider, local runtime, or deployment configuration.
  3. Review the source evidence below and compare it with your environment.
  4. Apply one change at a time and rerun the smallest failing action.
  5. Keep the working fix documented for the team or deployment environment.

How to prevent it

  • Keep provider/tool configuration documented.
  • Record non-secret diagnostics such as tool version, provider name, model name, and command path.
  • Add a lightweight check before CI or production workflows depend on the tool.