Model Rate Limit Recovery

Diagnose and recover from model rate limit errors (ChatGPT usage limits, 429 errors). Use when cron jobs or agent sessions fail with "Try again in ~9500 min"...

This skill appears to implement reasonable recovery steps for model rate limits, but it asks you (via the instructions) to read environment variables and logs and to create persistent scripts under /root. Before installing or running these instructions: 1) Confirm you trust the OpenClaw CLI and any third-party model providers referenced (DeepSeek, Anthropic). 2) Do not export high-privilege or production API keys; prefer limited-scope or test keys for rotation and recovery testing. 3) Inspect and, if needed, modify the recovery script paths so they don't assume /root or write to system-wide locations. 4) Be aware that running env | grep or log greps can reveal unrelated secrets; run such commands in a controlled/sandboxed environment first. 5) Ask the author to declare required env vars in metadata and to provide explicit least-privilege guidance — the mismatch between metadata (no env vars) and instructions (multiple secret env vars) is the primary red flag. If you want, test the procedures in a staging environment before applying to production.

Type: OpenClaw Skill Name: model-rate-limit-recovery Version: 1.0.0 The skill provides legitimate diagnostic and recovery procedures for handling LLM rate limit errors (429) in OpenClaw. It includes instructions for checking API keys in environment variables, configuring model fallbacks, and creating a shell script (`recover-failed-cron.sh`) to automate job recovery. While it interacts with sensitive environment variables and writes to the workspace, these actions are transparently documented and directly support the stated purpose of maintaining agent availability.