cline/skills

windsor-ai-business-data

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.

Trending #7268 First seen Jun 19, 2026

Installation

$ npx skills add cline/skills --skill windsor-ai-business-data

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More details

Agent compatibility

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Repository health

Stars 23
License LICENSE
Default branch main
Open issues 0
Status Active

Package contents

Files included with this skill beyond the listing page.

  • skill md SKILL.md 4,109 B
  • docs SUMMARY.md 263 B

History

  1. First seen on skills.sh
  2. First recorded snapshot · 292 installs

SKILL.md

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 "googleads", "facebook", "tiktok", "linkedin", "googleanalytics4", "hubspot", "salesforce", "searchconsole", "instagram", "youtube", "googlemy_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"]
  • datefrom / dateto: Date range as "YYYY-MM-DD"
  • datepreset: Shorthand like "last7d", "last30d", "thismonth", "last_3m"
  • filters: Conditions like [["spend", "gt", 100], "and", ["campaign", "contains", "Sale"]]
  • options: Connector-specific options like {"attributionwindow": "7dview,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 datepreset for quick queries: "last7d", "last30d", "thismonth"
  • 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