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.

Assists with security fundamentals by auto-activating when asked about https certificate checker tasks, guiding through detection patterns, secure coding, and validation workflows for reliable certificate handling.

This skill outlines step-by-step methods for discovering, confirming, and exploiting Insecure Direct Object Reference flaws via parameter manipulation, HTTP method switching, enumeration, and Burp Suite workflows, enabling authorized testers to document findings and suggest fixes.

This skill provides a comprehensive diagnostic reference for common errors and exceptions encountered with the Instantly.ai API v2. It covers critical areas including HTTP status codes (400, 401, 429, 500), campaign lifecycle issues (e.g., stuck in draft), account health checks, lead duplication handling, and implementing rate limit backoff. Use this when debugging failed API requests or troubleshooting complex campaign, account, or lead management issues.

This skill guide provides comprehensive instructions for deploying Instantly.ai's API v2 webhook receivers and automation services to major cloud platforms. It covers setting up resilient, public HTTPS endpoints using Vercel serverless functions, Google Cloud Run containers, or Fly.io services. Use this when moving from local development to production or setting up robust webhook endpoints that handle real-time event processing.

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 guide provides a comprehensive reference for diagnosing and resolving common errors encountered when interacting with the Kling AI API. It covers various HTTP status codes (e.g., 400, 401, 429), task-level failures (e.g., content policy violations, low image quality), proper JWT token management, and implementing rate limit handling with exponential backoff. Use this resource when troubleshooting failed video generation or API integration issues.

This skill provides comprehensive patterns for integrating external applications with the Lindy AI platform. It covers three primary channels: Webhook triggers for receiving inbound data, HTTP actions for making outbound API calls, and executing custom Python/JavaScript code (Run Code). Use this when building complex, multi-step automation workflows or connecting internal systems to Lindy agents.

A comprehensive guide for diagnosing and fixing common Lokalise API errors and exceptions. This skill details the error response format and provides diagnostic cURL commands for specific HTTP status codes (401, 400, 404, 429, 413, 500, 503). Use it when encountering failed requests, debugging integration issues, or needing to verify API token validity and rate limit status.

Develop robust, multi-channel enterprise agents designed for the Microsoft 365 ecosystem, including Teams and Copilot Studio. This SDK provides a comprehensive Python framework featuring aiohttp hosting, advanced AgentApplication routing, real-time streaming responses, and secure authentication via MSAL. Ideal for building sophisticated, production-grade bots and automation tools that integrate deeply with enterprise Microsoft services.

A comprehensive quick reference guide for troubleshooting and resolving common HTTP errors (4xx, 5xx) encountered when integrating with the MaintainX API. It provides detailed root causes, diagnostic commands (using curl/jq), and specific fixes for various status codes, such as 400 Bad Request, 401 Unauthorized, 429 Rate Limit, and 500 Internal Server Error, ensuring stable application integration.

This guide details the process of building Model Context Protocol (MCP) servers. These servers are crucial for enabling Large Language Models (LLMs) to interact with external APIs and services, facilitating complex, real-world task completion. It provides comprehensive coverage on architectural planning, choosing appropriate languages (Python, TypeScript, C#), and selecting transport mechanisms (HTTP, stdio) for robust integration within enterprise ecosystems like Azure and Foundry.