Skill UI

This comprehensive guide serves as a quick reference for diagnosing and fixing common errors encountered when interacting with the Fireflies.ai GraphQL API. It covers specific error codes (e.g., authentication failure, rate limits, invalid parameters) and provides actionable fixes, diagnostic scripts, and schema introspection techniques, ensuring seamless API integration and rapid troubleshooting.

Provides minimal working examples and comprehensive instructions for querying the Fireflies.ai GraphQL API. Users can learn how to list workspace users, fetch recent meeting transcripts, and retrieve detailed summaries, including action items and keywords, using code examples in TypeScript, Python, and Bash. Ideal for initial API setup, integration testing, or learning GraphQL patterns for meeting data.

This guide details the comprehensive setup process for authenticating with the Fireflies.ai GraphQL API. It covers retrieving the API key, configuring environment variables, and verifying connectivity using code examples for Node.js, Python, and cURL. Essential for securely integrating Fireflies data into external applications and automating transcript access.

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.

This skill provides a structured methodology for reviewing code commits intended to fix security vulnerabilities or address audit findings. It ensures that the original root cause is properly resolved, verifies the fix hasn't introduced new bugs or vulnerabilities (regressions), and validates the overall completeness of the remediation effort. Ideal for security-critical code reviews.

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.

Automates Flask blueprint creation and related backend guidance, triggering whenever users request blueprint creator help or backend best practices; generates production-ready code, validations, and covers node.js/python/go microservices patterns.

Auto-activating skill that guides analysts through forensics data collector operations, aligning advanced security practices with compliance frameworks while generating validated code and configurations for enterprise deployments.

This guide teaches developers how to achieve type-safe and predictable error handling in TypeScript using functional programming concepts from fp-ts, specifically focusing on the Either and TaskEither patterns. Instead of relying on disruptive try/catch exceptions, this pattern treats errors as explicit data values, forcing the calling code to handle failure paths, which is crucial for building robust, maintainable, and functional APIs and services.

A practical, jargon-free guide to applying functional programming principles using the fp-ts library in TypeScript. It teaches essential patterns like `pipe`, `Option`, `Either`, and `flatMap` to handle null checks, errors, and complex data transformations in a clean, maintainable, and robustly functional way. Ideal for developers looking to refactor imperative code.

Learn practical, type-safe patterns for building complex React applications using fp-ts. This guide covers key functional programming concepts like handling optional values (Option), managing failure states (Either), and structuring data fetching and forms, ensuring your code is predictable and robust for React 18/19 and Next.js 14/15.