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toolweb-aiot-engineer工具网 AIoT 工程师

Agent Skill

toolweb-aiot-engineer 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

3,340

周安装

142

GitHub Stars

公开资料未说明

下载量

1,170
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-aiot-engineer(工具网 AIoT 工程师)
来源仓库:https://github.com/krishnakumarmahadevan-cmd/toolweb-aiot-engineer
安装命令:
openclaw skills install toolweb-aiot-engineer
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-aiot-engineer

简介

ToolWeb-AIoT-Engineer 为人工智能与物联网工程师生成个性化职业发展路线图。

  • 适用于 OpenClaw 中需要规划学习路径或技能提升的专业人士。
  • 根据个人背景与目标定制技术栈与实践项目建议。
  • 通过 clawhub 安装后输入基本信息即可获得定制化方案。
  • 建议结合行业趋势定期更新路线,保持竞争力。

SKILL.md

name
AIoT Engineer Roadmap
description
Professional AI + IoT Engineering Career Roadmap Platform that generates personalized learning paths and specialization guidance for aspiring and current engineers.

Overview

The AIoT Engineer Roadmap is a professional career development platform designed to guide engineers through the intersection of Artificial Intelligence and Internet of Things technologies. It provides personalized roadmaps, specialization paths, and structured learning curricula tailored to individual experience levels, existing skills, and career goals.

This platform serves as a comprehensive resource for engineers looking to master AIoT technologies, from foundational concepts through advanced specializations. Whether you're transitioning into AIoT from another discipline or deepening expertise in a specific domain, the platform adapts recommendations based on your assessment profile.

The roadmap generator leverages assessment data including your current experience, technical competencies, and career objectives to produce a targeted, sequential learning path. The platform maintains extensive curated specialization tracks and learning resources, making it an ideal resource for career planners, technical managers evaluating team development, and individual contributors charting their professional growth.

Usage

Generate a Personalized Roadmap

Example Request:

{
  "assessmentData": {
    "experience": {
      "yearsInTech": 3,
      "backgroundAreas": ["embedded_systems", "python"]
    },
    "skills": {
      "technicalSkills": ["Python", "Linux", "Basic ML"],
      "softSkills": ["Communication", "Problem-solving"]
    },
    "goals": {
      "targetRole": "AIoT Solutions Architect",
      "timeframe": "18 months",
      "focusAreas": ["edge_computing", "machine_learning"]
    },
    "sessionId": "sess_abc123xyz",
    "timestamp": "2024-01-15T10:30:00Z"
  },
  "sessionId": "sess_abc123xyz",
  "userId": 12547,
  "timestamp": "2024-01-15T10:30:00Z"
}

Example Response:

{
  "roadmapId": "roadmap_xyz789",
  "userId": 12547,
  "generatedAt": "2024-01-15T10:30:15Z",
  "phases": [
    {
      "phase": 1,
      "title": "AIoT Foundations",
      "duration": "3 months",
      "topics": [
        "AI/ML fundamentals",
        "IoT architecture basics",
        "Data processing pipelines",
        "Cloud platform essentials"
      ],
      "resources": [
        {
          "title": "Introduction to ML for IoT",
          "type": "course",
          "duration": "40 hours",
          "provider": "industry-standard"
        }
      ]
    },
    {
      "phase": 2,
      "title": "Edge Computing & Embedded AI",
      "duration": "4 months",
      "topics": [
        "Edge deployment strategies",
        "Model optimization",
        "Real-time inference",
        "Resource-constrained environments"
      ]
    },
    {
      "phase": 3,
      "title": "Advanced Specialization",
      "duration": "6 months",
      "specialization": "AIoT Solutions Architecture",
      "topics": [
        "System design patterns",
        "Enterprise integration",
        "Security & compliance",
        "Scalability optimization"
      ]
    }
  ],
  "recommendedSpecializations": [
    "Edge AI Engineer",
    "AIoT Solutions Architect",
    "ML Operations (MLOps) Specialist"
  ],
  "estimatedCompletionTime": "13-18 months",
  "nextSteps": [
    "Enroll in recommended Phase 1 courses",
    "Set up local development environment",
    "Join community learning group"
  ]
}

Endpoints

GET /

Health Check Endpoint

Verifies that the API service is operational and responsive.

Parameters: None

Response: Returns a 200 status with JSON object confirming service health.


POST /api/aiot/roadmap

Generate Personalized Roadmap

Generates a customized AIoT engineering career roadmap based on the provided assessment data, current skills, experience level, and professional goals.

Parameters:

NameTypeRequiredDescription
assessmentDataobjectYesAssessment profile containing experience, skills, and goals
assessmentData.experienceobjectYesProfessional background and years of experience
assessmentData.skillsobjectYesCurrent technical and soft skills inventory
assessmentData.goalsobjectYesCareer objectives and target roles
assessmentData.sessionIdstringYesUnique session identifier for this assessment
assessmentData.timestampstringYesISO 8601 timestamp of assessment
sessionIdstringYesSession identifier matching assessmentData.sessionId
userIdinteger or nullNoOptional user ID for authenticated requests
timestampstringYesISO 8601 timestamp of the request

Response Shape:

Returns a JSON object containing:

  • roadmapId: Unique identifier for the generated roadmap
  • userId: Associated user ID (if provided)
  • generatedAt: Timestamp when roadmap was created
  • phases: Array of learning phases, each with title, duration, topics, and resources
  • recommendedSpecializations: List of suggested specialization paths
  • estimatedCompletionTime: Projected timeline for roadmap completion
  • nextSteps: Immediate action items to begin the roadmap

Validation Errors (422): Returns validation error details if required fields are missing or malformed.


GET /api/aiot/specializations

Get Available Specializations

Retrieves the complete list of available specialization paths within the AIoT engineering discipline.

Parameters: None

Response Shape:

Returns a JSON array of specialization objects, each containing:

  • Specialization name and identifier
  • Description and scope
  • Required prerequisite skills
  • Typical career outcomes
  • Industry demand metrics
  • Associated learning modules

GET /api/aiot/learning-paths

Get All Learning Paths

Retrieves all structured learning paths available in the platform, organized by skill level and domain.

Parameters: None

Response Shape:

Returns a JSON array of learning path objects, each containing:

  • Path identifier and title
  • Target skill level (beginner, intermediate, advanced)
  • Domain focus area (edge computing, machine learning, IoT architecture, etc.)
  • List of courses and modules
  • Estimated duration
  • Recommended prerequisites
  • Completion certifications

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/aiot-engineer
  • API Docs: https://api.mkkpro.com:8097/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

72.21%
按下载量换算845

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

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