Windsor Ai Business Data

cline/skills/skills/windsor-ai-business-data

作者 cline26378461e978无许可证34 个星标收录于 2026年10月8日更新于 2026年10月8日仓库2个月前更新

Query Windsor.ai business data across marketing, sales, CRM, ecommerce, finance, and analytics connectors. Use when users need dashboards, reports, data visualization, schema exploration, or connector-backed test data from Windsor.ai.

AI 生成的概览

通过 MCP 工具查询 Windsor.ai 的营销、销售、CRM、电商和财务等业务数据。

功能
该技能引导智能体使用 Windsor.ai 的四个 MCP 工具:get_connectors 列出已连接的平台和账户 ID,get_options 和 get_fields 探索可用字段与架构元数据,get_data 按日期范围、预设和筛选条件获取记录。它覆盖营销、销售、CRM、电商和财务连接器,并建议将结果写入本地 JSON 或 CSV 文件,用于仪表盘、报告或测试数据。
适用场景
当用户需要来自 Windsor.ai 连接器的业务数据(如广告支出、广告活动表现、CRM 或电商记录),或需要构建依赖真实连接器数据的仪表盘、报告、可视化或集成时使用。
运行要求
需要访问 Windsor.ai MCP 服务器及其四个工具(get_connectors、get_options、get_fields、get_data),以及已连接的平台账户和账户 ID。该技能不包含脚本,仅为说明文档。

Windsor.ai Business Data Skill

Use this skill whenever the user needs business data — marketing analytics, sales metrics, CRM data, ecommerce transactions, financial data, or any other data available through Windsor.ai's 325+ connectors.

When to Use

  • User is building a dashboard, report, or data visualization that needs business data from any source
  • User asks about ad spend, campaign performance, ROAS, CTR, CPC, or conversion metrics
  • User needs CRM, sales, ecommerce, or financial data in their codebase
  • User needs to explore what data sources or fields are available
  • User wants to seed a project with real data (e.g. for testing, prototyping, or generating fixtures)
  • User is building an integration with any platform supported by Windsor.ai

Available Tools

Windsor.ai provides 4 MCP tools:

get_connectors

Lists all connected platforms and their account IDs. Always call this first if you don't know what accounts are available.

get_options

Returns available fields, date filters, and options for a specific connector. Use this to discover what data can be queried before calling get_data.

Parameters:

  • connector (required): Platform ID like "google_ads", "facebook", "tiktok", "linkedin", "googleanalytics4", "hubspot", "salesforce", "searchconsole", "instagram", "youtube", "google_my_business", "shopify", "stripe", "quickbooks", and 300+ more
  • accounts (required): List of account IDs from get_connectors

get_fields

Returns detailed metadata about specific fields — data types, descriptions, available values. Use this when you need to understand the schema before writing code that processes the data.

Parameters:

  • connector (required): Platform ID
  • fields (required): List of field IDs like ["campaign", "spend", "clicks"]

get_data

Retrieves actual data. This is the main query tool.

Parameters:

  • connector (required): Platform ID
  • accounts (required): List of account IDs
  • fields (required): Fields to retrieve, e.g. ["campaign", "date", "spend", "clicks", "impressions"]
  • date_from / date_to: Date range as "YYYY-MM-DD"
  • date_preset: Shorthand like "last_7d", "last_30d", "this_month", "last_3m"
  • filters: Conditions like [["spend", "gt", 100], "and", ["campaign", "contains", "Sale"]]
  • options: Connector-specific options like {"attribution_window": "7d_view,1d_click"}

Workflow Pattern

  1. Discover → Call get_connectors to see what's connected
  2. Explore → Call get_options to see available fields for a connector
  3. Understand → Call get_fields for field metadata if building typed interfaces
  4. Query → Call get_data to pull the actual data

Common Field Patterns

Fields vary by connector type. Here are some common examples:

Marketing/Ads connectors: campaign, adgroup, ad, date, device, country, spend, clicks, impressions, conversions, revenue, ctr, cpc, cpm, roas

CRM connectors: deal, contact, company, stage, owner, amount, close_date

Ecommerce connectors: order_id, product, quantity, price, customer, status

Always check get_options first since available fields vary by connector.

Tips

  • When building dashboards or charts, pull data with get_data and write it to a local JSON/CSV file the app can read
  • For TypeScript projects, use get_fields to generate accurate type definitions
  • Use date_preset for quick queries: "last_7d", "last_30d", "this_month"
  • Combine filters for focused queries: [["spend", "gt", 0], "and", ["campaign", "ncontains", "test"]]
  • You can join data from different connectors (e.g. ad spend + CRM revenue) by pulling from each and merging in code

来源与署名

来源:cline/skills位于skills/windsor-ai-business-data提交2637846

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