Skill UI

This skill acts as a rigorous, Socratic interviewer designed to stress-test a proposed plan against an established domain model and existing project documentation. It forces the user to sharpen terminology, resolve cross-cutting dependencies, and identify inconsistencies between stated requirements, code implementations, and documented decisions. It ensures the resulting architecture is precise, consistent, and well-documented by automatically updating the context and generating Architecture Decision Records (ADRs).

This skill provides a comprehensive, multi-phase guide for authors to draft a Specification Enhancement Proposal (SEP) adhering to rigorous governance standards. It walks users through prerequisites, initial vetting (Gate), detailed interviews (e.g., breaking changes, security), and technical research, ensuring the proposed change is viable and community-vetted before formal submission.

A comprehensive guide to setting up CI/CD pipelines for ElevenLabs integrations. It implements a robust two-tier testing strategy: running mocked unit tests on every push to save API quota, and executing gated, real integration tests only on main branches or manually. Essential for automated validation of TTS projects using GitHub Actions.

A comprehensive checklist guiding the safe and robust deployment of Text-to-Speech (TTS) integrations powered by ElevenLabs into a live production environment. It covers critical steps including API configuration, implementing health checks, setting up circuit breakers for resilience, and establishing thorough monitoring and rollback procedures, ensuring reliable voice feature go-live.

This comprehensive guide provides a production-grade reference architecture for building robust Text-to-Speech (TTS) and voice applications using the ElevenLabs API. It covers detailed project structure, service layer design (including TTS orchestration, voice management, and caching), configuration handling, and best practices for streaming and multi-model orchestration, ensuring scalability and reliability in a commercial SaaS environment.

Establishes comprehensive Continuous Integration and Continuous Deployment (CI/CD) workflows for Fathom meeting intelligence. This setup includes unit tests using mocked transcripts to validate data parsing logic and robust integration tests that connect to the live Fathom API. It ensures the reliability of webhooks and data processing for real-time meeting summaries and action items upon every pull request or merge.

A comprehensive guide to diagnose and resolve common technical errors encountered when integrating with or using the Fathom API. It covers specific issues such as 401 Unauthorized, 429 Rate Limiting, empty transcripts, and webhook failures, providing actionable fixes for developers and power users.

This guide provides best practices for optimizing Fathom API usage and managing associated cloud costs. It covers strategies like implementing caching for transcripts, switching from API polling to webhooks, batching CRM writes, and establishing data retention policies (e.g., archiving after 90 days) to minimize unnecessary spending on storage and API calls.

This guide provides advanced strategies for optimizing bulk data synchronization and reducing latency when interacting with the Fathom meeting intelligence API. Techniques covered include implementing granular caching strategies (different TTLs for transcripts vs. action items), efficient batch processing with rate limit management, connection pooling, and robust error handling for reliable, high-throughput data operations.

This guide provides advanced, deep debugging techniques for complex Figma REST API issues that resist standard error handling. It covers full network tracing (cURL), validating unexpected response shapes (TypeScript), measuring rate limits, and safely chunking large files. Use this when standard troubleshooting fails, or detailed evidence is required for support escalation.

This workflow is designed for developers building design-to-code pipelines. It connects to Figma via API to extract core design tokens, including colors, typography styles, and spacing values. It converts these raw design assets into structured code formats, such as CSS custom properties, JSON tokens, and Tailwind configurations, ensuring design consistency across development environments.

This skill provides comprehensive guidance on optimizing complex integrations with the Figma API to minimize operational costs and prevent hitting rate limits. It covers architectural best practices, such as transitioning from inefficient polling to webhook-driven systems, batching multiple requests, and using parameters like `depth=1`. Essential for building scalable, cost-effective SaaS solutions.