Skill UI

This guide details how to set up a robust, local development loop for Framer plugins and components. It covers hot-reloading using Vite, writing unit tests with Vitest, and integrating with the Framer Server API. This workflow enables developers to achieve fast iteration cycles, ensuring seamless development from concept to production-ready prototype within the Framer environment.

A comprehensive skill that brings the entire GitHub pull request workflow directly into your terminal. It allows users to view PR status, monitor real-time CI/CD progress, summarize bot comments, and execute merge operations (squash, merge, rebase) without switching to a browser. It consolidates all critical PR information—including file changes and review blockers—into one cohesive view, streamlining the developer workflow and DevOps process.

This powerful orchestrator automates the entire GitHub issue lifecycle. It fetches issues based on criteria (labels, milestones, assignees), spawns specialized sub-agents to implement necessary code fixes, and automatically opens Pull Requests (PRs). Furthermore, it monitors open PRs, addresses review comments, and manages the remediation process, streamlining the development workflow from issue tracking to merge.

Manages the complete lifecycle of GitHub issues using a structured, label-based state machine. This skill assists maintainers in triaging incoming reports, determining if an issue is a bug or enhancement, and moving it through defined states (e.g., needs info, ready for agent, wontfix). It ensures systematic workflow management for development projects.

This skill demonstrates the complete workflow for integrating with the Glean platform. It guides users through three core steps: setting up a custom data source using the Indexing API, programmatically indexing documents, and executing advanced search queries using the Client API. This is essential for developers starting new Glean connectors or needing to test their search pipelines.

A comprehensive development workflow solution for integrating with the Glean enterprise search API. It enables developers to simulate local search responses, mock data sources, and test custom connectors and UIs without needing a live Glean deployment. Users can toggle between mock mode for rapid iteration and sandbox mode for validation against a real Glean instance, ensuring a fast feedback loop for building robust enterprise search applications.

This comprehensive guide details the setup and deployment workflow for Glean enterprise search across development, staging, and production environments. It emphasizes strict environment isolation by managing separate datasources, API tokens, and configurations for each stage. The skill covers best practices for promotion workflows, validation steps, and error handling, ensuring search relevance and data integrity during scaling and updates.

This skill provides comprehensive guidance and solutions for diagnosing and fixing common technical errors and exceptions encountered when integrating with the Grammarly API. It covers specific HTTP error codes (400, 401, 413, 429), addressing issues such as invalid tokens, payload size limits, rate limit exhaustion, and text formatting requirements. Use it when debugging failed API requests or troubleshooting complex integration workflows.

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.

A guide and toolkit for optimizing Grammarly API costs in large-scale applications. It addresses common cost overruns associated with high text volume by implementing strategies such as result caching, chunking long documents, sample-based scoring, and setting usage budget alerts. Use this when integrating Grammarly into enterprise workflows or managing billing for high-volume content analysis.

This guide provides a comprehensive walkthrough for integrating with the Hex API. It demonstrates the core workflow: list available Hex projects, trigger a project run with custom input parameters, and poll the status until the job is successfully completed. Ideal for setting up automated data pipelines, building robust backend services, or deeply integrating Hex functionality into external applications.

This guide details the recommended reference architecture and project structure for integrating with the Hex platform. It covers best practices for designing robust data pipelines, including components like orchestration layers (Airflow, Dagster), API clients, and standardized project layouts. Use this when starting new Hex integrations or reviewing complex data workflows.