Self-reflection + Self-criticism + Self-learning + Self-organizing memory. Agent evaluates its own work, catches mistakes, and improves permanently. Use when (1) a command, tool, API, or operation fails; (2) the user corrects you or rejects your work; (3) you realize your knowledge is outdated or incorrect; (4) you discover a better approach; (5) the user explicitly installs or references the skill for the current task.
Debug DNS resolution and network connectivity. Use when troubleshooting DNS failures, testing port connectivity, diagnosing firewall rules, inspecting HTTP requests with curl verbose mode, configuring /etc/hosts, or debugging proxy and certificate issues.
Understand and troubleshoot computer networks with TCP/IP, DNS, routing, and diagnostic tools.
AI-powered auto-repair system for OpenClaw with iflow integration. Automatically diagnose and fix crashes, config errors, model issues. Falls back to iflow-helper when needed.
Production-grade autonomous self-improvement system with research-backed meta-learning, safe self-modification, and continuous optimization. Based on AI safety research (MIRI, DeepMind, OpenAI) and meta-learning principles. Enables endless evolution cycles with safety constraints.
General AI agent introspection debugging framework: auto capture errors, root cause analysis, automatic repair, fix verification, no manual intervention required
Self-reflection + Self-criticism + Self-learning + Self-organizing memory. Agent evaluates its own work, catches mistakes, and improves permanently. Use before starting work and after responding to the user.