Skill UI

This comprehensive guide diagnoses and fixes common Clari API errors, including 401 Unauthorized, empty exports, job timeouts, and data mismatches. It provides step-by-step solutions for debugging data extraction and forecasting issues using API calls.

This skill provides blueprints for deploying Clari data export pipelines into robust, production-grade cloud environments. It guides users on setting up reliable, scheduled, and serverless data syncs using major platforms like Airflow DAGs, AWS Lambda, and Google Cloud Functions. Ideal for automating revenue forecasting and business intelligence data extraction.

A comprehensive workflow for setting up local development environments for Clari API integrations. It allows users to mock forecast data, test complex export pipelines, and iterate on data transformation logic (such as forecasting and aggregation) without requiring live API calls. Ideal for building robust dashboards and validating data workflows.

This guide provides strategies to minimize API overhead when integrating with Clari. Users can optimize export frequency (e.g., daily vs. quarterly), implement data caching, and restrict data exports to only the necessary types, thereby reducing operational costs and improving system performance.

This checklist guides the secure and robust deployment of Clari API integrations into a production data pipeline. It covers crucial areas like secret management, rate limit handling, data deduplication, error resilience (circuit breakers, backoff), and comprehensive monitoring setup, ensuring reliable revenue forecasting and reporting.

This guide outlines best practices for securing your Clari integration. It covers secure API token management, emphasizing storage in secrets managers (like AWS Secrets Manager), and implementing robust PII redaction methods for exported forecast data to maintain data privacy and compliance.

This skill provides integration with Grammarly's Writing Score API, enabling applications to automatically score documents. It evaluates writing quality across four dimensions: engagement, correctness, clarity, and tone. Use this when building content quality assurance features, implementing quality gates, or providing detailed, multi-dimensional feedback on written content.

This skill provides a comprehensive set of APIs for advanced writing analysis using Grammarly. It allows users to score text based on engagement, correctness, clarity, and tone. Furthermore, it includes functionality for AI detection and sophisticated plagiarism checking. It is ideal for developers needing to build content verification, grammar-checking, or academic integrity tools.

This skill facilitates an interactive Quality Assurance (QA) session. Users can conversationally describe encountered bugs or issues. The agent clarifies the problem, explores the codebase for context and domain language, and then meticulously files durable GitHub issues. It supports both single-issue reports and breaking down complex problems into multiple, independently verifiable tickets, ensuring developers receive actionable, high-quality reports written from the user's perspective.

This expert simulates an experienced design system author for Ant Design, specializing in structured, enterprise-focused, data-dense web applications. It generates comprehensive, implementation-ready guidelines covering design tokens, component anatomy, interaction states, accessibility requirements (WCAG 2.2 AA), and content standards, ensuring maximal clarity and consistency for development and design teams.

Acts as an expert guide for generating comprehensive, implementation-ready design system documentation. It enforces strict best practices covering visual foundations, component anatomy, accessibility standards (WCAG 2.2 AA), and structured writing workflows, ensuring consistency and clarity for engineering and design teams.