Skill UI

This guide provides production-ready patterns for integrating the Firecrawl SDK in TypeScript and Python. It covers essential architectural best practices, such as implementing singleton clients, typed service wrappers, automatic retries with exponential backoff, concurrency management, and robust response validation using Zod. Ideal for building scalable, reliable web scraping services.

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.

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.

This advanced workflow provides comprehensive meeting intelligence by allowing users to search across stored transcripts using keywords and date filters. It integrates the AskFred AI assistant for natural language Q&A over single or cross-meeting data. Furthermore, it aggregates detailed meeting analytics, providing key metrics such as total duration, action items, and top keywords for robust reporting and knowledge retrieval.

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.

A comprehensive runbook for rapidly responding to Fireflies.ai integration failures. Provides structured triage steps, P1-P4 severity assessment, and detailed remediation guides for common issues like API key expirations, rate limiting, and webhook discrepancies. Essential for on-call engineers during platform outages.

This guide provides a comprehensive, multi-step technical process for migrating historical meeting recordings and data into the Fireflies.ai ecosystem. It covers various scenarios, including batch uploads from public URLs, importing authenticated files (S3/GCS), direct file uploads, and tracking progress via webhooks, ensuring a robust and validated transition from competitor platforms.

Provides a robust, event-driven reference architecture for building meeting intelligence platforms using Fireflies.ai. This guide details the full production pipeline, covering multi-source meeting ingestion (Zoom, Teams), webhook processing, and subsequent data enrichment into structured action items, analytics reports, and database storage. Ideal for designing complex integrations or advanced meeting analytics systems.

This resource provides production-ready, type-safe GraphQL client patterns for integrating with the Fireflies.ai API in both TypeScript and Python. It addresses critical engineering concerns such as robust error handling, managing singletons, implementing multi-tenant support, and ensuring structured data validation using best practices.

This script provides a complete solution for setting up a webhook receiver for Fireflies.ai. It includes crucial HMAC-SHA256 signature verification to ensure data integrity, and then uses the Fireflies API to fetch the full transcript details, summary, and action items. Ideal for building real-time meeting intelligence pipelines, integrating meeting data into CRMs, or automating task creation.

Automate Firmao workflows through Composio’s Firmao toolkit via the Rube MCP bridge, always calling RUBE_SEARCH_TOOLS before executing connections and multi-tool commands so you know the current schemas, confirm ACTIVE connections, reuse sessions, and provide compliant arguments.

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.