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Agent Skill · 研究检索

toolweb-ai-agent-stack-builder(toolweb ai Agent 堆栈构建器)

toolweb-ai-agent-stack-builder 用于查找、检索和筛选相关信息,适合在 OpenClaw 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。

toolweb-ai-agent-stack-builder 是研究检索类 Agent Skill,可用宿主为 OpenClaw,通过ClawHub获取,权限为调用外部服务;许可证为 MIT-0,第三方扫描已通过,按安装量在研究检索类的 73,675 个 Skill 里排第 27,492。

总安装 3,378周安装 138GitHub Stars 公开资料未说明下载 1,082核验 2026-05-01

安装说明

本站只整理中文说明,不托管安装包,也不代用户安装。
GitHub
许可证
MIT-0
版本
1.0.0

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-agent-stack-builder(toolweb ai Agent 堆栈构建器)
来源仓库:https://github.com/krishnakumarmahadevan-cmd/toolweb-ai-agent-stack-builder
安装命令:
openclaw skills install toolweb-ai-agent-stack-builder
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-agent-stack-builder

这个 Skill 是做什么的

研究检索类 Skill 主要解决「找资料、核对事实、把来源整理清楚」的问题,通常会让助手先检索再总结。

toolweb-ai-agent-stack-builder 智能推荐 AI 代理技术堆栈,适配项目需求和团队能力。适合在 OpenClaw 中辅助架构选型,平衡性能、成本与开发效率。通过 clawhub 安装后,Agent 可综合约束条件输出候选技术组合及理由说明。

推荐结果应作为参考,最终决策需结合具体业务验证和技术债评估。适用宿主包括 OpenClaw,接入前应确认版本、权限和运行环境要求。

上手步骤

4 步
  1. 1

    确认自己的宿主工具

    公开资料标注支持 OpenClaw;先确认自己用的是其中之一,再按对应工具的 Skills 目录放置。

  2. 2

    拿到安装命令

    可以直接复制的命令是 openclaw skills install toolweb-ai-agent-stack-builder;命令里的占位符换成自己的路径或密钥再执行。

  3. 3

    安装后重启宿主

    命令执行完要完全退出宿主工具再打开,让新装的 Skill 被重新扫描到,否则列表里可能看不到。

  4. 4

    按最小权限试用

    它需要调用外部服务,先在测试目录或测试账号里跑,确认没问题再放到正式项目。

常见问题

6 条

toolweb-ai-agent-stack-builder 怎么安装?

在终端执行 openclaw skills install toolweb-ai-agent-stack-builder。装完完全退出宿主工具再打开,让它重新扫描本地 Skill。

toolweb-ai-agent-stack-builder 支持哪些 AI 工具?

公开资料标注支持 OpenClaw。其他工具只要能读取本地 Skill 目录,一般也能手动放进去,但要自己确认触发方式是否一致。

toolweb-ai-agent-stack-builder 需要什么权限?

权限级别是调用外部服务。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。

toolweb-ai-agent-stack-builder 是免费的吗?

来源标注的许可证是 MIT-0。本站不代收任何费用,也不托管安装包;能否商用、要不要署名,以许可证原文为准。

toolweb-ai-agent-stack-builder 用的人多吗?

公开数据是累计安装 3,378 次,近一周安装 138 次,下载 1,082 次。这些数字来自第三方目录统计,只能当作热度参考,不代表质量或安全性。

toolweb-ai-agent-stack-builder 安全吗?

第三方扫描结果为通过,但这只覆盖已知的静态检查项,不能替代自己读一遍源码和安装命令。

值得选的地方和要先想清楚的地方

值得选的地方

  • 专注 OpenClaw 一种宿主,触发方式和使用习惯不用来回切换。
  • 许可证明确为 MIT-0,商用和分发边界好判断。
  • 第三方扫描已通过,常见的高风险行为没有命中。

先想清楚的地方

  • 第三方目录整理,版本更新和行为细节以来源仓库为准。

适不适合你

更适合

  • 已经在用 OpenClaw,想直接扩展它能力的人。
  • 需要处理研究检索类任务、又不想每次都手写提示词的人。
  • 需要许可证清楚、并且有第三方扫描结果的团队项目。

不太适合

  • 需要厂商级技术支持和 SLA 的生产系统。

研究检索类 Skill 对比

6 个同类
Skill总安装GitHub 星权限许可证扫描
find-skills

寻找技能 · Codex、Claude

31,199,81316,486操作浏览器MIT有提醒
self-improving-agent

自我改进 Agent · OpenClaw

16,464,0023,396接触敏感数据MIT-0通过
soultrace

灵魂追踪 · Codex、Claude

7,588,94412需要联网未明确有提醒
self-improving

自我完善 · OpenClaw

6,829,2841,046需要联网MIT-0通过
microsoft-foundry

微软代工厂 · Codex、Claude

6,614,144764调用外部服务未明确有提醒
toolweb-ai-agent-stack-builder

toolweb ai Agent 堆栈构建器 · 本页

3,378—调用外部服务MIT-0通过

按安装量取同分类前几名;数字来自第三方目录统计,只作热度参考,不代表质量结论。

SKILL.md 原文

name
AI Agent Stack Builder
description
Intelligent recommendation system that generates optimal AI agent technology stacks based on project requirements, constraints, and team expertise.

Overview

The AI Agent Stack Builder is an intelligent recommendation engine designed to help development teams select the optimal technology stack for building AI agents. By analyzing project requirements—including type, expected user load, budget constraints, latency requirements, deployment preferences, and team expertise—the system provides curated recommendations for frameworks, large language models (LLMs), and supporting technologies.

This tool addresses a critical pain point in modern AI development: the overwhelming number of choices when building agent-based systems. Whether you're developing a customer service chatbot, autonomous research agent, or data analysis tool, the Stack Builder evaluates your unique constraints and generates a prioritized set of recommendations tailored to your situation.

The API is ideal for development teams, AI architects, technical leads, and organizations evaluating AI agent solutions who need objective, data-driven guidance on technology selection aligned with their specific operational and business constraints.

Usage

Sample Request:

{
  "formData": {
    "projectType": "customer_service_chatbot",
    "userLoad": "high",
    "budget": "medium",
    "latency": "low",
    "deployment": "cloud",
    "expertise": "intermediate",
    "capabilities": ["natural_language_understanding", "context_retention", "multi_turn_conversation"],
    "security": ["data_encryption", "role_based_access_control"],
    "additionalNotes": "Need HIPAA compliance for healthcare customer service"
  },
  "sessionId": "sess_abc123def456",
  "userId": 12345,
  "timestamp": "2024-01-15T14:30:00Z"
}

Sample Response:

{
  "recommendation": {
    "frameworks": [
      {
        "name": "LangChain",
        "priority": 1,
        "reasoning": "Excellent for multi-turn conversations with memory management and integrations",
        "suitability_score": 0.95
      },
      {
        "name": "LlamaIndex",
        "priority": 2,
        "reasoning": "Strong context retention and retrieval capabilities",
        "suitability_score": 0.88
      }
    ],
    "llms": [
      {
        "name": "GPT-4",
        "provider": "OpenAI",
        "priority": 1,
        "reasoning": "Superior NLU and context understanding for customer interactions",
        "cost_per_1m_tokens": 0.03,
        "latency_ms": 200
      },
      {
        "name": "Claude 3 Sonnet",
        "provider": "Anthropic",
        "priority": 2,
        "reasoning": "Strong privacy stance and cost-effective alternative",
        "cost_per_1m_tokens": 0.003,
        "latency_ms": 250
      }
    ],
    "supporting_technologies": [
      {
        "category": "vector_database",
        "recommendation": "Pinecone",
        "reasoning": "Managed solution suitable for cloud deployment with high availability"
      },
      {
        "category": "monitoring",
        "recommendation": "Datadog",
        "reasoning": "Comprehensive monitoring for latency-sensitive applications"
      }
    ],
    "compliance_notes": "Verify LLM provider's HIPAA BAA requirements; consider on-premise deployment for sensitive data handling",
    "estimated_monthly_cost": 1500,
    "implementation_timeline_weeks": 4
  }
}

Endpoints

GET /

Root / Health Check

Returns a health status of the API service.

ParameterTypeRequiredDescription
None——No parameters required

Response: 200 OK

{
  "status": "healthy",
  "version": "1.0.0"
}

POST /api/agent/stack

Generate Stack Recommendation

Generates an AI agent technology stack recommendation based on project requirements and constraints.

ParameterTypeRequiredDescription
formDataObject✓Project requirements and constraints
formData.projectTypestring✓Type of AI agent project (e.g., "customer_service_chatbot", "research_agent", "data_analysis_agent")
formData.userLoadstring✓Expected user load level ("low", "medium", "high")
formData.budgetstring✓Budget constraint ("low", "medium", "high")
formData.latencystring✓Latency requirement ("low", "medium", "high")
formData.deploymentstring✓Deployment environment ("cloud", "on_premise", "hybrid", "edge")
formData.expertisestring✓Team's technical expertise level ("beginner", "intermediate", "advanced")
formData.capabilitiesarray[string]OptionalRequired AI capabilities (e.g., "natural_language_understanding", "context_retention", "function_calling")
formData.securityarray[string]OptionalSecurity and compliance requirements (e.g., "data_encryption", "role_based_access_control", "audit_logging")
formData.additionalNotesstringOptionalAdditional context or special requirements
sessionIdstring✓Unique session identifier for tracking
userIdintegerOptionalUser identifier for personalization
timestampstring✓Request timestamp in ISO 8601 format

Response: 200 OK

{
  "recommendation": {
    "frameworks": [...],
    "llms": [...],
    "supporting_technologies": [...],
    "compliance_notes": "string",
    "estimated_monthly_cost": 0,
    "implementation_timeline_weeks": 0
  }
}

Error Response: 422 Unprocessable Entity

{
  "detail": [
    {
      "loc": ["body", "formData", "projectType"],
      "msg": "field required",
      "type": "value_error.missing"
    }
  ]
}

GET /api/frameworks

Get Available Frameworks

Retrieves the list of available AI agent frameworks that the system can recommend.

ParameterTypeRequiredDescription
None——No parameters required

Response: 200 OK

{
  "frameworks": [
    {
      "name": "LangChain",
      "version": "0.1.0",
      "category": "orchestration",
      "description": "Framework for building applications with LLMs",
      "maturity": "production"
    },
    {
      "name": "LlamaIndex",
      "version": "0.10.0",
      "category": "retrieval",
      "description": "Data framework for LLM applications",
      "maturity": "production"
    }
  ]
}

GET /api/llms

Get Available LLMs

Retrieves the list of available large language models that the system can recommend.

ParameterTypeRequiredDescription
None——No parameters required

Response: 200 OK

{
  "llms": [
    {
      "name": "GPT-4",
      "provider": "OpenAI",
      "type": "closed_source",
      "context_window": 128000,
      "cost_per_1m_tokens": 0.03,
      "latency_ms": 200
    },
    {
      "name": "Claude 3 Opus",
      "provider": "Anthropic",
      "type": "closed_source",
      "context_window": 200000,
      "cost_per_1m_tokens": 0.015,
      "latency_ms": 300
    }
  ]
}

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/creative/ai-agent-stack-builder
  • API Docs: https://api.mkkpro.com:8162/docs

平台分布

OpenClaw

80.42%
按下载量换算870

安全审计

VirusTotal

通过

ClawScan

通过

Static analysis

通过

权限和风险

调用外部服务

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。目前只有一个公开来源,建议同时核对源仓库。

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