Skill UI

Provides a comprehensive guide and Python implementation for creating container-based hosted agents in Azure AI Projects. It utilizes ImageBasedHostedAgentDefinition to define the agent's container image, required resources (CPU/memory), supported tools, and communication protocols. Essential for deploying robust, production-ready AI agents within the Azure ecosystem.

Map web inputs for reflected or stored HTML injection, send crafted tags via URLs, POST bodies, or visible fields, and document appearance/phishing manipulations for authorized security assessments.

A comprehensive utility designed to collect all necessary diagnostic evidence for troubleshooting Ideogram API interactions. It gathers environment details (Node, Python, OS), performs API connectivity tests, captures network information, and packages the results into a redacted tarball suitable for attaching to technical support tickets, ensuring all sensitive data is masked.

This comprehensive guide provides a multi-platform deployment solution for Ideogram-powered image generation APIs. It includes detailed code and setup steps for Vercel, Google Cloud Run, and self-hosted Docker containers. The solution addresses key production concerns, including secure secret management (API keys), handling generation timeouts, and ensuring generated images are persisted to durable cloud storage (like S3) with CDN integration for reliable service operation. Use this when migrating Ideogram prototypes to a production environment.

A comprehensive guide to implementing robust observability for Ideogram AI image generation APIs. Learn how to track critical metrics such as generation duration (latency), estimated API costs, error rates, and content safety rejections. This skill involves instrumenting API calls using TypeScript, integrating cost estimation, and setting up Prometheus alerting rules to ensure stable and reliable AI operation.

This skill guide provides advanced techniques for optimizing Ideogram API usage. It covers selecting optimal model tiers (e.g., Turbo vs. Standard) based on desired quality and speed, implementing prompt-based caching to reduce API calls and costs, and managing parallel generation with concurrency limits for high throughput. Additionally, it demonstrates CDN integration for rapid asset delivery.

This skill guides developers on building scalable, event-driven pipelines around Ideogram's synchronous API. It demonstrates implementing robust async patterns, including using job queues (like BullMQ) for batch generation, handling webhook callbacks for post-processing, and setting up full asset modification pipelines. Ideal for production-grade marketing and content workflows.

A comprehensive framework for managing availability and reliability incidents (outages, degradations, failed deploys). It guides the entire lifecycle, from automated severity classification (SEV1-SEV4) and timeline reconstruction to multi-team coordination and structured post-incident review (PIR). Essential for SRE and DevOps teams leading major incident responses.

Automates incident postmortem templates for technical documentation, offering structured guidance, best practices, template snippets, and validation cues across API docs, user guides, and architecture narratives.

A comprehensive guide for Site Reliability Engineers (SRE) covering the entire incident lifecycle. It provides structured methodologies for initial severity assessment, establishing an incident command structure, advanced observability-driven investigation (tracing, metrics, logs), systematic troubleshooting, and crucial post-incident root cause analysis (blameless post-mortems). Ideal for managing complex, large-scale system outages.

This skill provides a comprehensive, multi-phase guided workflow for professional incident response management. Following modern SRE principles and the Incident Command System (ICS), it guides users from initial detection and triage (P0-P3 classification) through deep investigation (observability, debugging, security checks), culminating in structured resolution and post-mortem analysis. Use this when managing critical system outages or performance degradation.

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.