claude-monitor
Monitor de performance do Claude Code e sistema local. Diagnostica lentidao, mede CPU/RAM/disco, verifica API latency e gera relatorios de saude do sistema.
What this skill does
# Claude Monitor — Diagnóstico de Performance ## Overview Monitor de performance do Claude Code e sistema local. Diagnostica lentidao, mede CPU/RAM/disco, verifica API latency e gera relatorios de saude do sistema. ## When to Use This Skill - When the user mentions "lento" or related topics - When the user mentions "lentidao" or related topics - When the user mentions "lag" or related topics - When the user mentions "lagado" or related topics - When the user mentions "travando" or related topics - When the user mentions "claude lento" or related topics ## Do Not Use This Skill When - The task is unrelated to claude monitor - A simpler, more specific tool can handle the request - The user needs general-purpose assistance without domain expertise ## How It Works Skill para diagnosticar e resolver problemas de lentidão no Claude Code e no sistema. Determina se o gargalo é local (PC) ou remoto (API Claude) e sugere ações corretivas. ## Quando Usar - Usuário reclama que o Claude Code está lento ou travando - Troca de sessões de conversa demora para carregar - Respostas do Claude demoram muito - PC parece lento enquanto usa o Claude Code - Qualquer menção a performance, lag, lentidão ## 1. Diagnóstico Rápido (Health_Check.Py) Rode SEMPRE como primeiro passo: ```bash python C:\Users\renat\skills\claude-monitor\scripts\health_check.py ``` O script analisa em ~3 segundos: - **CPU**: Uso atual e por core. >80% = gargalo provável - **RAM**: Total, usada, disponível. >85% = pressão de memória - **Browsers**: Processos e RAM por browser. >5GB total = excesso de abas - **Claude Code**: Processos e RAM consumida - **Disco**: Espaço livre. <10% = impacto em swap/performance - **Rede**: Latência ao endpoint da API Claude - **Diagnóstico**: Classificação automática do problema com sugestões ## 2. Interpretar O Resultado O script retorna um JSON com `diagnosis` contendo: - `bottleneck`: "cpu" | "ram" | "browsers" | "disk" | "network" | "claude_api" | "ok" - `severity`: "critical" | "warning" | "ok" - `suggestions`: Lista de ações recomendadas - `summary`: Resumo em português para mostrar ao usuário **Mostre o `summary` ao usuário** e ofereça executar as sugestões. ## 3. Ações Corretivas Automáticas Baseado no diagnóstico, ofereça ao usuário: #### Se CPU alta (>80%): - Listar processos consumindo mais CPU - Sugerir fechar processos pesados desnecessários - Verificar se Windows Update está rodando em background #### Se browsers pesados (>5GB RAM ou >40 processos): ```bash python C:\Users\renat\skills\claude-monitor\scripts\health_check.py --browsers-detail ``` Mostra RAM por browser e sugere quais fechar. **Nunca fechar processos sem permissão explícita do usuário.** #### Se disco cheio (>85%): - Mostrar pastas maiores - Sugerir limpeza de Temp, cache de browsers, lixeira #### Se rede lenta (latência >500ms): - Testar conexão com api.anthropic.com - Sugerir verificar VPN, proxy, ou conexão WiFi ## 4. Monitor Contínuo (Opcional) Se o usuário quiser monitoramento em background: ```bash python C:\Users\renat\skills\claude-monitor\scripts\monitor.py --interval 30 --duration 300 ``` Parâmetros: - `--interval`: Segundos entre cada amostra (default: 30) - `--duration`: Duração total em segundos (default: 300 = 5 min) - `--output`: Caminho do arquivo de log (default: monitor_log.json) - `--alert-cpu`: Threshold de CPU para alerta (default: 80) - `--alert-ram`: Threshold de RAM % para alerta (default: 85) O monitor salva snapshots periódicos e gera um relatório ao final com: - Picos de CPU e RAM - Tendência (melhorando/piorando/estável) - Eventos de alerta detectados - Recomendação final ## 5. Benchmark Da Api Claude (Opcional) Para testar se a lentidão é da API: ```bash python C:\Users\renat\skills\claude-monitor\scripts\api_bench.py ``` Mede o tempo de resposta do processo Claude Code local (não faz chamadas à API). Compara com tempos típicos e indica se está dentro do esperado. ## Thresholds De Referência | Métrica | OK | Warning | Critical | |---------|-----|---------|----------| | CPU % | <60% | 60-85% | >85% | | RAM usada % | <70% | 70-85% | >85% | | RAM browsers | <3 GB | 3-6 GB | >6 GB | | Processos browser | <30 | 30-60 | >60 | | Disco livre | >15% | 10-15% | <10% | | Latência rede | <200ms | 200-500ms | >500ms | ## Dicas Para O Usuário Quando apresentar o diagnóstico, inclua estas dicas contextuais: - **Muitas abas = muito CPU/RAM**: Cada aba de browser é um processo separado. 50 abas = 50 processos competindo por recursos. - **Claude Code é pesado**: Ele roda vários processos Electron. É normal consumir 3-5 GB. Mas se estiver usando >6 GB com várias sessões, considere fechar sessões antigas. - **Troca de sessão lenta**: Geralmente causada por CPU alta ou muitos processos competindo. A sessão precisa carregar o histórico da conversa, e se o CPU está ocupado, demora. - **Disco quase cheio**: Afeta a velocidade do swap (memória virtual) e pode causar lentidão generalizada. ## Dependências - Python 3.10+ - psutil (instalado automaticamente pelo script se não disponível) - Nenhuma API key necessária ## Best Practices - Provide clear, specific context about your project and requirements - Review all suggestions before applying them to production code - Combine with other complementary skills for comprehensive analysis ## Common Pitfalls - Using this skill for tasks outside its domain expertise - Applying recommendations without understanding your specific context - Not providing enough project context for accurate analysis ## Limitations - Use this skill only when the task clearly matches the scope described above. - Do not treat the output as a substitute for environment-specific validation, testing, or expert review. - Stop and ask for clarification if required inputs, permissions, safety boundaries, or success criteria are missing.
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