Skill UI

This skill systematically analyzes an existing codebase to generate seven comprehensive technical documents. It covers the technology stack, architectural patterns, directory structure, coding conventions, external integrations, testing strategies, and technical concerns. It is invaluable for new team members onboarding, conducting project audits, or creating a complete, verifiable system knowledge base.

This skill guides AI agents to handle complex technical tasks with maximum precision and minimal computational overhead. It implements adaptive verbosity rules, sophisticated input filtering (for logs, source files, VCS, and payloads), and surgical output generation. It ensures context-window awareness, structured reasoning, and adherence to best practices for coding, debugging, and architecture analysis.

A powerful pre-tool-use hook designed to significantly improve AI-generated code quality and reliability. GateGuard forces the LLM to conduct concrete investigations—such as listing imports, checking data schemas, and identifying affected modules—before committing any edits, writing new files, or executing destructive commands. It moves beyond simple self-evaluation by demanding verifiable facts, dramatically reducing bugs and increasing design depth in complex coding workflows.

This guide provides production-ready patterns for integrating with the Hex platform API using TypeScript and Python. It covers essential best practices like robust retry logic, typed client usage, pipeline orchestration, and Airflow integration, helping developers establish standardized, reliable coding standards for complex Hex workflows.

This guide provides production-ready, high-quality patterns for integrating with Algolia Search v5. It covers critical architectural aspects such as implementing singleton client management, performing strongly typed searches, robust error handling (including specific API error codes), efficient batch indexing, and handling multi-tenant environments. Use these patterns to refactor existing code and establish reliable coding standards.

This guide details how to use sophisticated coding agents (such as Codex, Claude Code, or Pi) through a structured bash workflow. It provides methods for complex development tasks, including building new features, refactoring large codebases, and reviewing pull requests (PRs). Key best practices covered include managing pseudo-terminals (PTY), defining focused working directories (`workdir`), and executing tasks in the background for robust, multi-step automation.

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.

Automated guardrails for enforcing security policies and coding standards across all Figma API integrations. This tool is essential for CI/CD pipelines, helping to prevent credential leaks (PATs), validate API scopes, enforce request best practices, and ensure stable, secure connectivity with Figma.

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 production-ready, robust coding patterns for Framer development. This resource covers key areas including type-safe CMS interactions, plugin state management hooks, reusable component architectures, and server API wrappers. Use this when refactoring existing SDK usage or establishing scalable coding standards for complex Framer integrations.

A rigorous coding discipline tool derived from Andrej Karpathy’s principles. It helps developers, especially when working with LLMs, enforce four critical rules: surfacing assumptions, prioritizing simplicity, making surgical changes, and defining verifiable goals. It acts as a comprehensive pre-commit hook and review agent to prevent over-engineering, hidden assumptions, and unnecessary code bloat.

This comprehensive guide serves as a quick reference for diagnosing and fixing common Klaviyo API errors and SDK exceptions. It provides detailed root causes and solutions for standard HTTP status codes (400, 401, 403, 429, etc.) and common coding pitfalls. Ideal for developers integrating Klaviyo into their applications.