What this error means

append_messages() inside tool runner loop causes infinite loop (plain context message) or dropped assistant turn (assistant message replacement) — two failure modes is a Anthropic API failure pattern reported for developers trying to fix anthropic sdk tool_runner loop hanging infinitely or dropping responses when append_messages() is called during tool execution. Based on the imported evidence, treat this as a tool-specific troubleshooting page rather than a generic API error.

Why this happens

Reported on anthropics/anthropic-sdk-python#1536, fixed in PR#1538 (2026-05-13). Calling append_messages() inside a tool runner loop had two failure modes: plain context messages caused infinite loop, assistant message replacements caused dropped turns. Critical for agentic workflows using tool_runner. Category: Anthropic API (SDK runtime bug).

Common causes

  • Reported on anthropics/anthropic-sdk-python#1536, fixed in PR#1538 (2026-05-13). Calling append_messages() inside a tool runner loop had two failure modes: plain context messages caused infinite loop, assistant message replacements caused dropped turns. Critical for agentic workflows using tool_runner. Category: Anthropic API (SDK runtime bug).

Quick fixes

  1. Confirm the exact error signature matches append_messages() inside tool runner loop causes infinite loop (plain context message) or dropped assistant turn (assistant message replacement) — two failure modes.
  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.