Skill UI

This skill provides comprehensive management for the entire track lifecycle within a Conductor system. It allows users to perform critical operations such as archiving, restoring, deleting, renaming tracks, and cleaning up orphaned artifacts. Use it when managing track status across active, completed, or archived states to ensure data integrity and system organization.

This skill provides a comprehensive, actionable overview of the Conductor project's status. It aggregates information from project plans, active tracks, and detailed specifications to display overall progress, identify next critical tasks, and flag potential blockers. Use it when you need a high-level dashboard view of project health and required actions.

This skill validates the completeness, consistency, and correctness of Conductor project artifacts. It checks for the existence of required directories, verifies essential project documentation (like index.md, product.md, etc.), and confirms adherence to established naming and status patterns. Use this tool after setup, when diagnosing issues, or before implementation to ensure the project context is sound.

A comprehensive guide for diagnosing and fixing common integration errors with Customer.io. It covers critical topics such as API status codes (400, 401, 429), authentication failures, incorrect timestamp formatting, and best practices for event tracking and transactional message delivery. Use this resource when troubleshooting campaign failures or API calls failing.

This guide implements Deepgram's callback and webhook mechanism for handling asynchronous audio transcription. It provides a complete workflow, including submitting audio for background processing, setting up a secure webhook endpoint (with HMAC signature verification), and managing job status using Redis. Essential for integrating robust, delayed voice processing results into a production backend system.

A comprehensive quick-reference guide to diagnosing and resolving common Documenso API errors. Covers status codes (400, 401, 413, etc.), authentication issues, payload validation, rate limits, and best practices for successful document lifecycle management and API integration.

A comprehensive set of production-ready design patterns for integrating with the Documenso SDK. It covers best practices for managing singleton clients, building typed service wrappers, robust API error handling (including status code analysis), and automatically implementing retry logic with exponential backoff. Ideal for establishing stable, scalable, and maintainable coding standards in TypeScript and Python.

This guide details how to implement and handle Documenso webhooks for real-time document lifecycle notifications. Learn to set up secure webhook endpoints to receive critical events—such as document creation, signing completion, rejection, or opening. Use this when you need to trigger automated downstream workflows (e.g., updating CRMs, sending alerts, or logging audit trails) based on any status change in a document signing process.

A comprehensive workflow for implementing advanced search and retrieval features within Evernote. It allows users to build complex queries using search grammar, filter notes by tags, notebooks, dates, and completion status, and paginates through large result sets. The service also enriches results by mapping GUIDs to human-readable names for notebooks and tags.

A comprehensive guide to diagnosing and resolving common errors and status codes (400, 401, 429, etc.) encountered when integrating with the Exa API. Provides specific solutions for malformed requests, authentication failures, rate limit issues, and content fetching errors, ensuring smooth API debugging and integration.

This guide provides a comprehensive pattern for creating robust and scalable FastAPI routers. It covers essential best practices, including implementing proper authentication logic (required/optional dependencies), defining structured response models using Pydantic, and correctly assigning HTTP status codes. Use this skill when building structured and secure Python backend APIs.

A comprehensive toolkit for monitoring the health and performance of Fireflies.ai integration. It tracks crucial metrics such as API connectivity, webhook delivery status, transcript processing latency, and seat utilization. Built using Prometheus metrics and suitable for Grafana dashboards, ensuring reliable data pipeline monitoring for engineering teams.