Integrations

Supercharge CodeScene with Relevance AI

CodeScene is a powerful platform for code analysis and project management that offers detailed analytics through a REST API. By integrating with Relevance AI, you can transform code insights into proactive actions, enabling smarter project management and enhanced team collaboration.

Give your AI Agents CodeScene Superpowers

CodeScene provides deep insights into code quality and project management. With Relevance AI, you can leverage these insights to create intelligent AI Agents that automate decision-making and optimize your development processes.

Predictive Code Intelligence

The AI Agent gains the ability to forecast potential code issues and technical debt before they manifest

Pattern Recognition Mastery

Enhanced capability to identify complex development patterns and team behaviors across multiple repositories

Technical Debt Navigation

Advanced understanding of code maintenance needs and strategic refactoring priorities

Tools

Equip AI Agents with the CodeScene Tools they need

Relevance AI seamlessly integrates with CodeScene to enhance your code analysis workflows.

CodeScene - Create a New Project
Creates a new CodeScene project by specifying project name, repository paths, and developer configuration settings for code analysis and collaboration
CodeScene - Get Project Analysis
Retrieves detailed analysis results for a specific project and analysis ID, providing insights into code quality and development patterns
CodeScene - Get Project Analysis
Retrieves detailed analysis results for a specific project and analysis ID, providing insights into code quality and development patterns
CodeScene - Get Projects
Fetches a list of all available CodeScene projects associated with the authenticated account, providing an overview of existing projects
Name
CodeScene API Call
Description
Make an authorized request to a CodeScene API
Parameters
["OAuth authentication", "Multiple HTTP methods (GET, POST, PUT, DELETE, PATCH)", "Custom headers support", "Request body configuration", "Response handling with status codes"]
Use Case
A development team uses the CodeScene API integration to automatically monitor code quality metrics across their repositories, triggering alerts when technical debt exceeds defined thresholds and enabling proactive maintenance of their codebase.

Security & Reliability

The CodeScene integration utilizes a robust REST API interface, enabling seamless automation of code quality analysis and project management. With secure OAuth authentication, only authorized workflows can access your CodeScene data, ensuring the integrity of your projects.

Relevance AI manages API operations (like GET, POST, PUT, DELETE) in the background, allowing you to focus on your development tasks without worrying about errors, formatting, or rate limits. Built-in validation and type conversion ensure that your workflows run smoothly, even when dealing with varying data formats.

This integration empowers you to automate project creation, gain deep insights into code analysis, and access real-time project analytics, all while integrating effortlessly into your existing development workflows.

No training on your data

Your data remains private and is never utilized for model training purposes.

Security first

We never store anything we don’t need to. The inputs or outputs of your tools are never stored.

Get Started

Best Practices for Non-Technical Users

To get the most out of the CodeScene + Relevance AI integration without writing code:
  • Start with a well-structured project: Ensure your codebase is organized and follows best practices for naming conventions and file structures.
  • Utilize automated workflows: Leverage CodeScene's capabilities to automate project creation and analysis for efficient management.
  • Connect securely: Verify that you are using the correct OAuth credentials and permissions during setup to ensure seamless integration.
  • Test API calls thoroughly: Validate your API requests with sample data before deploying to production to minimize errors.
  • Monitor performance: Keep an eye on API usage and implement caching strategies to optimize response times and reduce load.