Skill UI

Automate Fireflies workflows through Composio’s Fireflies toolkit by orchestrating Rube MCP calls; it guides you to search available tools, verify Fireflies connections, and execute schema-aware multi-tool operations reliably.

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 workflow connects to the Fireflies.ai API via GraphQL to fetch and process detailed meeting transcripts. It handles speaker-diarized data, extracting structured insights such as action items, key topics, sentiment analysis, and speaker breakdowns. It enables the creation of comprehensive meeting intelligence reports and robust downstream pipelines. Use this when you need to automate the retrieval, summarization, or deep analysis of recorded meeting content.

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.

A comprehensive guide to optimizing Fireflies.ai subscription costs. Learn how to reduce expenses by auditing user utilization, configuring selective recording policies, managing storage retention, and accurately right-sizing your plan (Pro, Business, Enterprise). Ideal for teams reviewing billing or implementing cost-saving measures.

This skill manages the complete lifecycle of Fireflies.ai meeting transcripts. It allows users to fetch raw data, export in various formats (JSON, CSV, SRT), sanitize sensitive personal information (PII Redaction), and enforce data retention policies to ensure compliance with regulations like GDPR and CCPA. Ideal for data governance and compliance workflows.

This utility collects comprehensive diagnostic evidence for Fireflies.ai integration issues. It captures environment details (Node/Python versions, OS), checks API connectivity, gathers account metadata, and pulls recent transcript metadata. The output is a safe, redacted bundle ideal for submitting support tickets or troubleshooting persistent platform problems.

A comprehensive guide for deploying Fireflies.ai integrations into production environments. This skill covers setting up the GraphQL client, implementing secure webhook receivers with signature verification, and managing multi-platform deployments across Vercel, Docker, and Google Cloud Run. Ideal for integrating AI-powered meetings data into production services.

A comprehensive guide to configuring Fireflies.ai's Enterprise Role-Based Access Control (RBAC). Learn how to manage workspace roles (Admin, Member, Guest), organize transcripts into specific channels, control granular privacy levels, and manage external sharing via detailed API instructions. Essential for large organizations managing sensitive meeting data.

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.