Skill UI

This guide provides production-ready code patterns for integrating with the Cohere AI API v2 using TypeScript and Python. It covers essential best practices, including singleton client management, robust retry mechanisms, type-safe chat wrappers, streaming, embedding, reranking, and structured JSON output. Use this when establishing team coding standards or refactoring existing Cohere integrations.

A sophisticated tool for comparing two versions of a legal contract side-by-side. It detects all added, removed, and modified clauses, classifying changes by type and severity. Crucially, it performs favorability analysis, determining which party (Party A or Party B) each change strategically favors, and alerts the user to dangerous patterns like IP scope creep or indemnification drift, making it essential for high-stakes contract negotiations.

This guide details how to set up and execute large-scale, distributed GPU training jobs on the CoreWeave platform. It covers both single-node multi-GPU setups and multi-node training utilizing PyTorch DDP and Kubernetes resources (A100/H100). This workflow is ideal for fine-tuning large language models (LLMs) or running complex deep learning models that require high-performance, shared-storage compute clusters.

This comprehensive skill is designed to retrieve content from various Feishu cloud documents, returning the raw Markdown format. It provides advanced logic for handling Wiki URLs by first determining the actual document type (Docx, Sheet, Bitable) before calling the appropriate specialized tool. Furthermore, it guides the user on how to separately download and process embedded media like images, files, and whiteboards using dedicated media tools.

A comprehensive guide for accessing and managing Feishu IM messages. This skill allows users to retrieve historical chat records from both group and private conversations, read detailed thread replies, and conduct cross-conversation searches using keywords or time filters. It also supports downloading all types of embedded media, including images, files, audio, and videos, ensuring complete information recall.

This skill automatically converts structured data specifications (such as CSV, JSON schemas, SQL DDL, or Protobuf definitions) into functional, production-ready code. It generates complete models, validation logic, full CRUD API endpoints, and unit tests in multiple languages (Python, TypeScript, Go, etc.), significantly reducing boilerplate coding time and ensuring type safety.

A comprehensive guide to optimizing the Finta fundraise workflow. This document addresses critical performance bottlenecks, including pagination issues with large investor datasets, latency in multi-stage round data aggregation, and slow CRM synchronization. Optimization strategies cover cursor-based fetching, strategic caching (TTL management), connection pooling, and robust rate limit handling, aiming to reduce pipeline load times by 50-70% and maintain dashboard responsiveness.

This guide details how to implement robust Role-Based Access Control (RBAC) for Flexport API integrations. It addresses enterprise needs by allocating scoped API keys and managing permissions at an application layer. Users can define specific roles (Viewer, Operator, Finance, Admin) with granular permissions, ensuring that different user roles can only access necessary endpoints, thereby enhancing security and supporting multi-tenant architectures.

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.

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.

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 deep dive into migrating from the deprecated Grammarly Text Editor SDK to the current, server-side REST APIs. It details the architectural shift from client-side embedding to modern API calls, covering how to implement Writing Score (v2), AI Detection (v1), and Plagiarism Detection (v1) using secure token authentication.