reqon

Define and execute declarative data synchronization pipelines using the Reqon DSL.

1|Updated Dec 20, 2025

Search Tags:#data pipeline #api integration #etl #data synchronization #dsl #reqon

Ready to run

npx skills add https://github.com/mcclowes/reqon --skill reqon

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: reqon
Source: https://github.com/mcclowes/reqon/tree/main/.claude/skills/reqon
Command: npx skills add https://github.com/mcclowes/reqon --skill reqon

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes references (resource) components.

What problem does it solve?

This Skill simplifies the process of defining and executing complex data synchronization pipelines, especially for API integrations, by providing a declarative language.

Core Features & Use Cases

Declarative DSL: Define data fetching, mapping, and validation logic in a readable .vague file.
API Integration: Connect to various APIs with different authentication methods and handle pagination.
Data Transformation: Map and validate data structures between sources and stores.
Use Case: Automate the synchronization of data from a third-party API into your internal database, handling authentication, data transformation, and error management.

Quick Start

Use the reqon skill to parse and execute the provided '.vague' file.

Frequently Asked Questions about reqon

High-intent search queries and answers about installing and using this skill.

FAQPage Schema

What is a declarative data pipeline and how does it work for API integration?▼

A declarative data pipeline defines API fetching, mapping, and validation logic in a readable file rather than imperative code. It works by parsing a structured mission file to automatically execute data synchronization and integration flows.

How do I automate ETL and data synchronization from a third-party API to my database?▼

You can automate ETL and data synchronization by defining a declarative mission file that specifies the API source, authentication, data transformation rules, and target store. The pipeline executes these instructions to fetch, validate, and load data automatically.

Can I handle complex API authentication and pagination for data fetching?▼

Yes, declarative data pipelines support connecting to various APIs with different authentication methods and handling pagination. This allows automated fetching of large datasets across multiple pages without manual intervention.

What is the best way to validate and transform data structures between API sources and stores?▼

The best way to validate and transform data structures is by defining mapping rules in a declarative DSL file. This structured approach ensures data from external APIs conforms to your internal database schema before loading.

Do I need to write custom scripts for complex flow control in data integration pipelines?▼

No, you do not need custom scripts for complex flow control in data integration. The declarative DSL supports complex flow control mechanisms natively within the mission file, automating the integration process.

Are there limitations to using declarative DSL for data synchronization pipelines?▼

Using a declarative DSL for data synchronization pipelines requires defining logic within the specific file format's constraints. Highly customized or non-standard API behaviors might require careful configuration within the structured mission-based approach.