What this error means

429 {"type":"error","error":{"type":"rate_limit_error","message":"Rate limited"}} is a Anthropic API failure pattern reported for developers trying to fix anthropic api 429 rate limit error where billing counter is decremented even when the request fails. Based on the imported evidence, treat this as a tool-specific troubleshooting page rather than a generic API error.

Why this happens

GitHub issue reports Anthropic API returning 429 rate_limit_error during Claude Code ultrareview session. Counter decremented from 3 to 2 and user charged despite failed request. Error occurs at generate() in cli.js. Affects paid Anthropic API users.

Common causes

  • Developers using Claude Code hit rate limits and get charged for failed requests, causing unexpected billing and workflow interruption. The error message is generic and hard to debug.
  • GitHub issue reports Anthropic API returning 429 rate_limit_error during Claude Code ultrareview session. Counter decremented from 3 to 2 and user charged despite failed request. Error occurs at generate() in cli.js. Affects paid Anthropic API users.

Quick fixes

  1. Confirm the exact error signature matches 429 {"type":"error","error":{"type":"rate_limit_error","message":"Rate limited"}}.
  2. Check the Anthropic API account, local tool state, and provider configuration involved in the failing workflow.
  3. Reduce request pressure, check quota or plan limits, and retry with backoff instead of immediate repeated requests.

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.