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network
Understand and troubleshoot computer networks with TCP/IP, DNS, routing, and diagnostic tools.
Codex 또는 Claude로 설치 이 Prompt를 복사해 Codex, Claude 또는 다른 어시스턴트에 붙여 넣으면 Skill 페이지를 검토하고 설치를 진행할 수 있습니다.
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Understand and troubleshoot computer networks with TCP/IP, DNS, routing, and diagnostic tools.
Codex 또는 Claude로 설치 이 Prompt를 복사해 Codex, Claude 또는 다른 어시스턴트에 붙여 넣으면 Skill 페이지를 검토하고 설치를 진행할 수 있습니다.
SOC 직업 분류 기준
| name | Network |
| description | Understand and troubleshoot computer networks with TCP/IP, DNS, routing, and diagnostic tools. |
| metadata | {"clawdbot":{"emoji":"🌐","os":["linux","darwin","win32"]}} |
dig and nslookup query DNS directly — bypass local cache for accurate resultsping tests reachability — but ICMP may be blocked, no response doesn't mean downtraceroute/tracert shows path — identifies where packets stop or slow downnetstat -tulpn or ss -tulpn shows listening ports — find what's using a portcurl -v shows full HTTP transaction — headers, timing, TLS negotiationtcpdump and Wireshark capture packets — last resort for deep debuggingssh -L local:remote:port creates secure tunnelSelf-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tool, API, or operation fails; (2) the user corrects you or rejects your work; (3) you realize your knowledge is outdated or incorrect; (4) you discover a better approach; (5) the user explicitly installs or references the skill for the current task.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.
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.