Skill UI

Automates Excel macro creation and configuration by guiding workflows, ensuring best practices, generating production-ready code, and validating outputs to accelerate business automation tasks like workflow orchestration, email handling, and spreadsheet operations.

Automates guidance for implementing factory patterns within test automation, offering best-practice code generation, validation, and setup assistance for unit, integration, and mocking scenarios.

Automates FastAPI ML endpoint deployments by guiding architecture, producing production-ready code, and validating serving configs when you invoke the ML deployment skill.

Automates FastAPI router creation by guiding backend developers through best practices, code generation, and validation for services spanning Python, Node.js, Go, and microservice architectures.

Automates fastify plugin creation within backend development workflows by guiding through best practices, generating production-ready code, and validating configurations for microservices, caching, and database integrations.

Automates guidance on assessing feature importance for machine learning training, covering data prep, model training, tuning, and experiment tracking while generating production-ready code, configurations, and validation instructions for best-practice compliance.

Automates guidance for setting up and validating feature store connectors within ML deployment pipelines, covering best practices, code generation, and production monitoring for inference.

Automates guidance for API filtering query builder tasks, offering industry best practices, production-ready code, and validation across REST, GraphQL, OpenAPI, and authentication design patterns.

This guide provides comprehensive setup for implementing CI/CD pipelines for Fireflies.ai integrations. It covers best practices for validating GraphQL queries, running mock-based unit tests (using Vitest), and executing live integration tests against the actual API. It integrates seamlessly with GitHub Actions, ensuring that code changes are automatically validated in a stable, automated testing environment before deployment. Essential for maintaining API stability and robustness.

Automated Firestore index guidance for GCP Skills, triggering on index creator requests to deliver best-practice configs, validation, and production-ready code for Firebase/BigQuery/Vertex AI workloads.

Automates fixture generator tasks for test automation, offering best-practice guidance, ready-to-use code/configuration, and validation for unit, integration, and mocking scenarios.

Automates flame graph generation during performance testing, guiding users through best practices, sample code, and validation for load, stress, and benchmarking workflows.