What this error means
API Error: 529 {"type":"overloaded_error"} is a Claude Code failure pattern reported for developers trying to fix claude code 529 overloaded error when anthropic api capacity is saturated during peak hours on opus or max plan. Based on the imported evidence, treat this as a tool-specific troubleshooting page rather than a generic API error.
Why this happens
Source: codersera.com detailed troubleshooting guide (May 2026). Covers root cause (Anthropic capacity saturation per-model), /doctor output (API connectivity green but overload inline), fixes (switch model via /model, check status.claude.com, let CLI retry with exponential backoff), and escalation path (documented 2026 regression for sustained per-account 529s). Category mapping: Claude Code → AI Coding Tools per SKILL.md exact mapping rules.
Common causes
- Source: codersera.com detailed troubleshooting guide (May 2026). Covers root cause (Anthropic capacity saturation per-model), /doctor output (API connectivity green but overload inline), fixes (switch model via /model, check status.claude.com, let CLI retry with exponential backoff), and escalation path (documented 2026 regression for sustained per-account 529s). Category mapping: Claude Code → AI Coding Tools per SKILL.md exact mapping rules.
Quick fixes
- Confirm the exact error signature matches
API Error: 529 {"type":"overloaded_error"}. - Check the Claude Code account, local tool state, and provider configuration involved in the failing workflow.
- 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
- Capture the exact error message and the command, editor action, or request that triggered it.
- Check whether the failure is account/auth, quota/rate, model/provider, local runtime, or deployment configuration.
- Review the source evidence below and compare it with your environment.
- Apply one change at a time and rerun the smallest failing action.
- 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.