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holmesgpt-skill霍姆斯 GPT 技能

Agent Skill

holmesgpt-skill 用于查找、检索和筛选相关信息,适合在 Codex、Claude、Cursor、Gemini CLI 中需要根据关键词、任务场景或来源线索快速定位候选结果时使用。可结合来源仓库、安装命令和原始 README 继续核验具体用法。安装前建议确认权限范围、维护状态,以及是否会触发联网、命令执行或文件读写。

总安装

945

周安装

39

GitHub Stars

61

下载量

309
CodexClaudeCursorGemini CLI

安装说明

本站只整理中文说明和来源信息,不托管安装包,也不代用户安装。

GitHub

来源数

3

许可证

MIT

最后核验

2026-05-01

来源状态

来源可访问

安装方式

通过对话安装

复制提示词发给支持本地命令或 Skills 的 AI 助手,先确认命令和权限,再让它执行。

请帮我安装这个 Agent Skill:holmesgpt-skill(霍姆斯 GPT 技能)
来源仓库:https://github.com/julianobarbosa/claude-code-skills
仓库路径:skills/holmesgpt-skill
安装命令:
npx skills add https://github.com/julianobarbosa/claude-code-skills --skill holmesgpt-skill
安装前请先检查当前环境是否支持对应 CLI,并向我确认将要执行的命令、安装目录、联网范围和文件读写权限;确认后再执行。

命令行安装

复制命令到本机终端执行。不同来源提供的安装方式可能略有差异;本站展示可直接复制的安装命令,安装前请核对来源页面。

skills.shnpx skills
npx skills add https://github.com/julianobarbosa/claude-code-skills --skill holmesgpt-skill

简介

holmesgpt-skill 用于查找、检索和筛选相关信息。

  • 适合在 Codex、Claude、Cursor、Gemini CLI 中根据关键词、任务场景或来源线索快速定位候选结果。
  • 通过 npx skills add 命令从指定仓库安装,需确认权限范围和维护状态。
  • 使用前应核实是否会触发联网、命令执行或文件读写等操作。
  • 适用宿主包括 Codex、Claude、Cursor、Gemini CLI,接入前应确认版本、权限和运行环境要求。

SKILL.md

HolmesGPT Skill

AI-powered troubleshooting for Kubernetes and cloud-native environments.

Overview

HolmesGPT is a CNCF Sandbox project that connects AI models with live observability data to investigate infrastructure problems, find root causes, and suggest remediations. It operates with read-only access and respects RBAC permissions, making it safe for production environments.

Quick Reference

TopicReference
Installationreferences/installation.md
Configurationreferences/configuration.md
Data Sourcesreferences/data-sources.md
Commandsreferences/commands.md
Troubleshootingreferences/troubleshooting.md
HTTP APIreferences/http-api.md
Integrationsreferences/integrations.md

Key Features

  • Root Cause Analysis: Investigates alerts and cluster issues
  • Multi-Source Integration: 30+ toolsets (K8s, Prometheus, Grafana)
  • Alert Integration: AlertManager, PagerDuty, OpsGenie, Jira, Slack
  • Interactive Mode: Troubleshooting with /run, /show, /clear
  • Custom Toolsets: Extend with proprietary tools via YAML configuration
  • CI/CD Integration: Automated deployment failure investigation

Installation Quick Start

CLI (Homebrew)

brew tap robusta-dev/homebrew-holmesgpt
brew install holmesgpt
export ANTHROPIC_API_KEY="your-key"  # or OPENAI_API_KEY
holmes ask "what pods are unhealthy?"

Kubernetes (Helm)

helm repo add robusta https://robusta-charts.storage.googleapis.com
helm repo update
helm install holmesgpt robusta/holmes -f values.yaml

Docker

docker run -it --net=host \
  -e OPENAI_API_KEY="your-key" \
  -v ~/.kube/config:/root/.kube/config \
  us-central1-docker.pkg.dev/genuine-flight-317411/devel/holmes \
  ask "what pods are crashing?"

Essential Commands

# Basic investigation
holmes ask "what pods are unhealthy and why?"
holmes ask "why is my deployment failing?"

# Interactive mode
holmes ask "investigate issue" --interactive

# Alert investigation
holmes investigate alertmanager --alertmanager-url http://localhost:9093
holmes investigate pagerduty --pagerduty-api-key <KEY> --update

# With file context
holmes ask "summarize the key points" -f ./logs.txt

# CI/CD integration
holmes ask "why did deployment fail?" --destination slack --slack-token <TOKEN>

Supported AI Providers

ProviderEnvironment VariableModels
AnthropicANTHROPIC_API_KEYSonnet 4, Opus 4.5
OpenAIOPENAI_API_KEYGPT-4.1, GPT-4o
Azure OpenAIAZURE_API_KEYGPT-4.1
AWS BedrockAWS credentialsClaude 3.5 Sonnet
Google GeminiGEMINI_API_KEYGemini 1.5 Pro
Vertex AIVERTEXAI_PROJECTGemini 1.5 Pro
OllamaLocal installLlama 3.1, Mistral

Basic Helm Values Structure

# values.yaml for Kubernetes deployment
image:
  repository: robustadev/holmes
  tag: latest

env:
  - name: ANTHROPIC_API_KEY
    valueFrom:
      secretKeyRef:
        name: holmesgpt-secrets
        key: anthropic-api-key

# Model configuration
modelList:
  sonnet:
    api_key: "{{ env.ANTHROPIC_API_KEY }}"
    model: anthropic/claude-sonnet-4-20250514
    temperature: 0

# Toolsets to enable
toolsets:
  kubernetes/core:
    enabled: true
  kubernetes/logs:
    enabled: true
  prometheus/metrics:
    enabled: true

# Resources
resources:
  requests:
    memory: "1024Mi"
    cpu: "100m"
  limits:
    memory: "1024Mi"

# RBAC (read-only by default)
createServiceAccount: true

Interactive Mode Commands

CommandDescription
/clearReset context when changing topics
/runExecute custom commands and share output with AI
/showDisplay complete tool outputs
/contextReview accumulated investigation information

Custom Toolset Example

# custom-toolset.yaml
toolsets:
  my-custom-tool:
    description: "Custom diagnostic tool"
    tools:
      - name: check_service_health
        description: "Check health of a specific service"
        command: |
          curl -s http://{{ service_name }}.{{ namespace }}.svc.cluster.local/health
        parameters:
          - name: service_name
            description: "Name of the service"
          - name: namespace
            description: "Kubernetes namespace"

Use with: holmes ask "check health" -t custom-toolset.yaml

Kubernetes Annotations for Integration

# Add to Services/Deployments for HolmesGPT context
metadata:
  annotations:
    holmesgpt.dev/runbook: |
      This service handles payment processing.
      Common issues: database connectivity, API rate limits.
      Check: kubectl logs -l app=payment-service

Environment Variables Reference

VariableDescriptionDefault
HOLMES_CONFIG_PATHConfig file path~/.holmes/config.yaml
HOLMES_LOG_LEVELLog verbosityINFO
PROMETHEUS_URLPrometheus server URL-
GITHUB_TOKENGitHub API token-
DATADOG_API_KEYDataDog API key-
CONFLUENCE_BASE_URLConfluence URL-

Best Practices

  1. Use Specific Queries: Include namespace, deployment name, symptoms
  2. Start with Claude Sonnet 4.0/4.5: Best accuracy for complex investigations
  3. Enable Relevant Toolsets: Only enable what you need to reduce noise
  4. Use Interactive Mode: For complex multi-step investigations
  5. Set Up Runbooks: Provide context for known alert types
  6. CI/CD Integration: Automate deployment failure analysis

Security Considerations

  • HolmesGPT uses read-only access (get, list, watch only)
  • Respects existing RBAC permissions
  • Never modifies, creates, or deletes resources
  • API keys stored in Kubernetes Secrets
  • Data not used for model training

Official Resources

适合场景

01

用户想查找某类 Agent Skill 时

02

需要根据任务场景推荐可安装能力包时

03

需要对比不同来源的安装命令和来源信息时

04

需要参考平台分布和安装热度时

能力概览

能力 1

按任务关键词查找相关 Skills

能力 2

展示可复制的安装命令

能力 3

保留来源站点、仓库和原始说明,方便继续核验

能力 4

补充不同宿主或平台的使用分布数据

能力 5

展示第三方安全扫描或审计结果

安装后应在对应宿主中按原始 README 的触发条件使用;具体调用方式请以来源页面和 README 为准。

平台分布

Claude Code

28.53%
按下载量换算88

OpenCode

24.65%
按下载量换算76

Gemini CLI

19.69%
按下载量换算61

Antigravity

12.18%
按下载量换算38

Codex

7.99%
按下载量换算25

Cursor

3.66%
按下载量换算11

安全审计

Gen Agent Trust Hub

未通过

Socket

通过

Snyk

可疑

权限和风险

敏感数据

该 Skill 可能接触密钥、Token、环境变量或敏感配置,应进入高风险复核队列,默认不自动发布。

安装前确认

本站仅展示第三方公开信息,不托管安装包,不提供自动安装或运行环境。安装前应自行审查源码、依赖和命令行为。来源安全扫描存在 warning/failed 结果,不能写成本站确认安全。

来源信息

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