Skill UI

Auto-activating skill provides guidance for HTTP method helper tasks, covering REST, GraphQL, OpenAPI, authentication, and API design patterns while producing production-ready code and validations.

This guide provides expert patterns and code templates for integrating with the HubSpot CRM API. It covers secure authentication methods, including OAuth 2.0 for public apps and Private App Tokens for single-account use. Topics include CRUD operations on CRM objects, handling associations, webhooks, and batch processing. Implementation examples are provided for both Node.js and Python SDKs.

The official Hugging Face Hub CLI (`hf`) is a comprehensive command-line tool for managing all types of resources on the Hugging Face Hub. Use it to download, upload, synchronize, and manage models, datasets, Spaces, and cloud buckets. It facilitates secure authentication, local cache management, and complex data operations, making it essential for ML workflows.

Automatically guides API developers through creating hypermedia link generators, covering REST, GraphQL, OpenAPI, authentication, and design patterns while producing validated code and configurations that follow best practices.

This comprehensive guide serves as a quick reference for diagnosing and resolving common Ideogram API errors and exceptions. It covers critical issues such as authentication failures (401), rate limiting (429), safety check failures (422), and incorrect parameter formats (400). Use this resource when debugging failed image generation requests or integrating Ideogram functionality into an application.

A comprehensive runbook for rapid incident response concerning Ideogram API outages, authentication failures, and performance degradation. It provides detailed triage scripts, decision flows based on HTTP status codes (401, 429, 5xx), immediate mitigation actions (e.g., enabling fallback mode), and structured templates for communication and postmortems.

A comprehensive guide to setting up and authenticating the Ideogram API for AI image generation. This skill covers obtaining the necessary API key, configuring environment variables, and providing verifiable code snippets (Python/TypeScript) to establish a successful connection. It is essential for integrating image generation, editing, and remixing capabilities into any development project.

Automates guidance and code for identifying insecure deserialization flaws, following Security Fundamentals best practices to help with authentication, input validation, and secure coding checks when that phrase is mentioned.

This guide provides step-by-step instructions for setting up and authenticating with the Instantly.ai API v2. It covers generating necessary API keys, setting up environment variables, and provides ready-to-use client wrappers in TypeScript and Python. Use this when building custom integrations or automating workflows with the Instantly outreach platform.

This guide provides comprehensive steps and code examples for migrating Instantly.ai integrations from the deprecated API v1 to the modern REST API v2. It details critical changes, including updating authentication from query-string API keys to Bearer token authorization, standardizing endpoints, and restructuring complex request bodies. Use this skill to ensure your applications remain functional after the v1 deprecation.

This comprehensive guide addresses common technical and business logic errors encountered when integrating with the Juicebox API. It covers HTTP status codes (e.g., 401, 403, 429), including authentication failures, quota exhaustion, rate limiting, data validation issues, and analysis timeouts. The resource provides detailed causes, specific fixes, and best practices for building reliable and robust integrations into recruiting and research workflows.

This bundle collects comprehensive diagnostic evidence from the Juicebox platform. It gathers API connectivity status, dataset health reports, analysis quota usage, and rate limit information into a single archive. Use it to systematically troubleshoot complex issues such as failed dataset uploads, stalled AI analysis runs, API authentication failures, or quota exhaustion.