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Windsor AI Business Data

ClineOfficialPublished by Cline

  • Skill
  • Tool integration
  • Automation and integrations
  • Apache-2.0
  • No issues found

From the author

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.
— the description by Cline

AutoGineer summary

Written by AutoGineer from the skill’s own files, not by the author

The Windsor.ai Business Data skill provides a structured interface to interact with a vast ecosystem of business data connectors. It enables users to discover available data sources, explore schema metadata, and perform targeted queries across marketing, sales, CRM, ecommerce, and financial platforms. By following a standard discovery-to-query workflow, the skill allows for the seamless integration of real-world business metrics into dashboards, reports, and development projects.

What it does

  • Lists connected platforms and account identifiers.
  • Explores available fields and filtering options for specific connectors.
  • Retrieves detailed metadata and data types for specific fields.
  • Executes data queries with support for date ranges, presets, and complex filtering.
  • Facilitates the generation of test data and schema-based type definitions.

When to use it

  • When building dashboards or data visualizations requiring external business metrics.
  • When you need to integrate CRM, ecommerce, or financial data into an application.
  • When prototyping or seeding a project with real-world data fixtures.
  • When you need to analyze ad spend, campaign performance, or conversion metrics.
  • When you need to understand the available data schema for a specific platform integration.

Advantages

  • Unified access to over 325 different business and marketing data sources.
  • Standardized workflow for discovering and querying diverse data types.
  • Supports complex filtering and date-based presets for precise data retrieval.
  • Provides metadata access for generating accurate type definitions in code.
  • Enables cross-platform data merging by providing a consistent query interface.

Usage examples

“What data sources do I have connected to Windsor.ai?”
The agent calls get_connectors to return a list of all active platforms and their associated account IDs.
“Show me the available fields for my Google Ads account.”
The agent calls get_options for the google_ads connector to display all queryable fields and filter options.
“Get me the spend and clicks for my Facebook campaigns from the last 30 days.”
The agent calls get_data with the facebook connector, the specified fields, and the last_30d date preset.
“I need to know the data type for the revenue field in Shopify.”
The agent calls get_fields for the shopify connector to retrieve metadata and data type information for the revenue field.

Install

  1. Download the skill as a ZIP:

    https://autogineer.com/agent-skills/cline/windsor-ai-business-data/download
  2. Unzip it into the cross-client skills folder of your project:

    mkdir -p .agents/skills && unzip windsor-ai-business-data.zip -d .agents/skills

Documentation by Cline

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

Files

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 "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

Requirements and compatibility

Written for: Claude Code

Works with: Claude Code, Claude apps, OpenAI Codex, GitHub Copilot, Cursor, Gemini CLI, Kiro, OpenCode, Goose, Amp, Roo Code, JetBrains Junie, Factory Droid, Devin (ex-Windsurf), Mistral Vibe, OpenHands, Letta

“Works with” means the tool reads the open Agent Skills format; a skill written for one tool may use features others lack.

Needs: Claude Code frontmatter

Security

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Attribution and licence

Published by
Cline
Publisher
Cline (Official)
Source
cline/skills · skills/windsor-ai-business-data · commit 2637846
Licence
Apache License 2.0 (redistribution allowed)
  • LICENSE (added by AutoGineer from LICENSE)
  • ATTRIBUTION.md (written by AutoGineer)
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Download ZIP

The ZIP holds the skill’s files, its licence files and an ATTRIBUTION.md. Download windsor-ai-business-data.zip