Token导航 LogoToken导航TokenDH.com
研究检索external-serviceclawhub未标认证来源可访问clear审计通过

toolweb-ai-incident-responsetoolweb ai 事件响应

Agent Skill

toolweb-ai-incident-response 用于记录任务执行中的错误、用户纠正、经验和能力缺口,适合在 OpenClaw 中希望让 Agent 持续沉淀问题、修正和最佳实践时使用。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

4,079

周安装

165

GitHub Stars

公开资料未说明

下载量

1,280
OpenClaw

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

2

许可证

MIT-0

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:toolweb-ai-incident-response(toolweb ai 事件响应)
来源仓库:https://github.com/krishnakumarmahadevan-cmd/toolweb-ai-incident-response
安装命令:
openclaw skills install toolweb-ai-incident-response
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。该命令会通过 OpenClaw 从第三方来源获取 Skill;本站只展示命令,不托管安装包,也不自动执行。

ClawHubOpenClaw
openclaw skills install toolweb-ai-incident-response

简介

通过专门的学习路径和技能评估,为人工智能事件响应专业人员生成个性化的职业路线图。

SKILL.md

name
AI Incident Response Roadmap
description
Generate personalized career roadmaps for AI incident response professionals with specialized learning paths and skill assessments.

Overview

The AI Incident Response Roadmap platform is a professional career development tool designed to help security professionals build expertise in AI-driven incident response. This platform assesses your current background, technical skills, and career goals to generate a personalized roadmap tailored to your experience level and objectives.

The tool provides structured learning paths, identifies specialization opportunities in emerging AI security domains, and tracks your progression through validated skill assessments. Whether you're transitioning from general cybersecurity into AI incident response or deepening expertise in specific specialization areas, this platform delivers actionable guidance aligned with industry standards.

Ideal users include security engineers, incident responders, SOC analysts, threat hunters, and CISSP/CISM professionals seeking to advance their capabilities in AI security and incident response automation.

Usage

Example Request

{
  "assessmentData": {
    "background": {
      "yearsExperience": 5,
      "currentRole": "Security Engineer",
      "certifications": ["Security+", "CEH"]
    },
    "skills": {
      "threatAnalysis": "intermediate",
      "incidentResponse": "intermediate",
      "pythonProgramming": "beginner",
      "cloudSecurity": "intermediate"
    },
    "goals": {
      "targetRole": "AI Incident Response Specialist",
      "timeline": "12 months",
      "focusAreas": ["automation", "ml-detection", "forensics"]
    },
    "sessionId": "sess_abc123def456",
    "timestamp": "2024-01-15T10:30:00Z"
  },
  "sessionId": "sess_abc123def456",
  "userId": 12345,
  "timestamp": "2024-01-15T10:30:00Z"
}

Example Response

{
  "roadmapId": "roadmap_xyz789",
  "userId": 12345,
  "status": "success",
  "personalized_roadmap": {
    "phases": [
      {
        "phase": 1,
        "title": "Foundation Building",
        "duration": "3 months",
        "skills": [
          "Python for Security Automation",
          "AI/ML Fundamentals",
          "Incident Response Frameworks"
        ],
        "resources": [
          "SANS Cyber Aces Python Course",
          "Google Machine Learning Crash Course",
          "NIST IR Guidelines"
        ],
        "milestones": [
          "Complete Python automation project",
          "Understand ML model basics",
          "Review NIST IR processes"
        ]
      },
      {
        "phase": 2,
        "title": "Specialization",
        "duration": "6 months",
        "skills": [
          "ML-Based Threat Detection",
          "Automated Forensics",
          "AI Model Interpretability"
        ],
        "resources": [
          "Advanced threat detection labs",
          "Forensics case studies",
          "MLOps for Security"
        ],
        "milestones": [
          "Build custom detection model",
          "Complete forensics case study",
          "Implement detection automation"
        ]
      },
      {
        "phase": 3,
        "title": "Expert Mastery",
        "duration": "3 months",
        "skills": [
          "AI Incident Response Leadership",
          "Advanced Automation Orchestration",
          "Emerging Threats Research"
        ]
      }
    ],
    "specialization": "ML-Driven Detection & Response",
    "estimatedCompletion": "2024-12-15",
    "nextSteps": [
      "Enroll in Python automation course",
      "Set up ML lab environment",
      "Join AI security community"
    ]
  },
  "timestamp": "2024-01-15T10:35:22Z"
}

Endpoints

GET /

Health Check Endpoint

Verifies API availability and service status.

Parameters: None

Response:

  • Status: 200 OK
  • Content-Type: application/json
  • Body: Empty object or service status object

POST /api/ai-ir/roadmap

Generate Roadmap

Generates a personalized AI incident response career roadmap based on user assessment data.

Parameters:

NameTypeRequiredDescription
assessmentDataAssessmentData objectYesUser assessment containing background, skills, and goals
assessmentData.backgroundObjectNoProfessional background details (years of experience, current role, etc.)
assessmentData.skillsObjectNoCurrent technical skills and proficiency levels
assessmentData.goalsObjectNoCareer goals and target specializations
assessmentData.sessionIdStringYesUnique session identifier
assessmentData.timestampStringYesISO 8601 timestamp of assessment
sessionIdStringYesRequest session identifier
userIdInteger/NullNoUnique user identifier
timestampStringYesISO 8601 timestamp of request

Response:

  • Status: 200 OK
  • Content-Type: application/json
  • Body: Personalized roadmap with phases, specialization path, learning resources, and milestones

Error Responses:

  • 422 Unprocessable Entity: Validation error in request body. Returns HTTPValidationError with field-specific error details.

GET /api/ai-ir/specializations

Get Specializations

Retrieves all available specialization paths in AI incident response.

Parameters: None

Response:

  • Status: 200 OK
  • Content-Type: application/json
  • Body: Array of specialization objects containing specialization name, description, required skills, and prerequisites

GET /api/ai-ir/learning-paths

Get Learning Paths

Retrieves all available learning paths and modules for AI incident response training.

Parameters: None

Response:

  • Status: 200 OK
  • Content-Type: application/json
  • Body: Array of learning path objects containing path title, modules, estimated duration, skill prerequisites, and resources

Pricing

PlanCalls/DayCalls/MonthPrice
Free550Free
Developer20500$39/mo
Professional2005,000$99/mo
Enterprise100,0001,000,000$299/mo

About

ToolWeb.in - 200+ security APIs, CISSP & CISM, platforms: Pay-per-run, API Gateway, MCP Server, OpenClaw, RapidAPI, YouTube.

References

  • Kong Route: https://api.mkkpro.com/career/ai-incident-response
  • API Docs: https://api.mkkpro.com:8110/docs

适合场景

01

OpenClaw 用户查找和安装 Skill 时

02

用户想查找某类 Agent Skill 时

03

需要根据任务场景推荐可安装能力包时

04

需要对比不同来源的安装命令和来源信息时

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

OpenClaw

96.83%
按下载量换算1,239

安全审计

VirusTotal

通过

ClawScan

通过

Static analysis

通过

权限和风险

external-service

该 Skill 可能调用第三方服务、云服务或外部模型 API,使用前需要确认账号、额度、数据发送范围和服务条款。

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。当前只有一个来源,正式发布前建议补源仓库或其他目录站核验。

来源信息

继续浏览同类 Skills