Skill UI

This skill provides comprehensive methods for accessing, exporting, and transforming data from Apple Notes. It addresses the specific HTML structure of note bodies, handling rich content like checklists, tables, and attachments. Users can export notes to structured formats like JSON (for backups/migration) or convert the HTML content to Markdown format, ensuring data integrity across different platforms and automating migration pipelines.

This skill provides comprehensive access to Bright Data's SERP API and Web Scraper API. It allows users to collect structured search engine results (Google, Bing, Yahoo) synchronously, or trigger large-scale, asynchronous data collections with webhooks. Ideal for market research, SEO analysis, and large-scale data scraping projects.

This comprehensive guide details how to implement robust webhook endpoints to receive, validate, and process data deliveries from Bright Data's Web Scraper and Datasets APIs. Learn best practices for handling large JSON/NDJSON payloads, verifying authorization headers, processing status notifications, and ensuring data deduplication in automated scraping pipelines.

Transforms raw calendar data (ICS/JSON) into actionable development workflows. This skill automatically generates detailed meeting briefings, summarizes standup notes using Git commits and CI status, and creates repeatable Bash scripts. It bridges time management and development tasks, ensuring users are always prepared for their next meeting or sprint.

This advanced guide covers core Anthropic workflow patterns, specifically focusing on tool use (function calling) and building complex, agentic loops. It provides detailed instructions on defining tools using JSON Schema, executing tool calls, and managing the iterative process required for building sophisticated, AI-powered agents using the Anthropic API.

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.

This guide provides a comprehensive framework for investigating production issues on the Nexu platform using the Datadog Logs API. It details how to query crash events, analyze OpenClaw stderr output, check gateway startup status, and review API request logs (including 5xx errors). It includes best practices for authentication, filtering by pod/time, and parsing raw JSON logs using Python for actionable insights.

This workflow is designed for developers building design-to-code pipelines. It connects to Figma via API to extract core design tokens, including colors, typography styles, and spacing values. It converts these raw design assets into structured code formats, such as CSS custom properties, JSON tokens, and Tailwind configurations, ensuring design consistency across development environments.

Automate the complex process of migrating design systems, design tokens, and styles between multiple Figma files, or from external sources into Figma. This tool covers the full pipeline: inventorying assets, extracting raw style data (colors, typography, effects), transforming them into structured design tokens (e.g., JSON format), and finally writing them back into Figma variables using the Variables API. Ideal for maintaining consistency across large design libraries.

Generate publication-quality architecture, workflow, pipeline, and system topology diagrams from structured JSON (FigureSpec) into deterministic, editable SVG vector graphics. Ideal for formal figures needing precise, repeatable, hand-editable output.

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.

This comprehensive tool analyzes a detailed specification by synthesizing data from multiple source files (JSON, Markdown, etc.). It tracks phase completion, identifies task progress, maps boundary contexts (upstream/downstream dependencies), and proactively highlights necessary revalidation points or blockers, providing a single, unified report of the spec's completeness and current development state.