Skill UI

Automatically orchestrate Highergov operations through Composio’s Highergov toolkit with Rube MCP, emphasizing tool discovery, connection checks, schema compliance, and session reuse for structured workflow automation.

Execute complex and compute-intensive workloads directly on fully managed Hugging Face cloud infrastructure. This skill eliminates the need for local setup, allowing users to run jobs using cloud CPUs, GPUs, or TPUs. Ideal for large-scale data processing, batch inference, reproducible model training, and scheduled automation tasks, while persisting results to the Hugging Face Hub.

Identifies and rewrites AI-generated phrasing by removing inflated claims, promotional language, formulaic structures, and robotic cadence so reviewed prose sounds natural, varied, and personality-driven.

An expert architect specializing in designing, implementing, and managing complex hybrid and multi-cloud environments. Expertise spans major public clouds (AWS, Azure, GCP), private clouds (OpenStack, VMware), and container platforms (Kubernetes). Focus areas include cross-cloud networking, Infrastructure as Code (IaC) using Terraform, workload optimization, zero-trust security implementation, and FinOps cost management.

This skill provides structured patterns for combining vector similarity search with traditional keyword-based search. It is essential for building advanced Retrieval-Augmented Generation (RAG) systems, sophisticated search engines, or any retrieval task requiring high recall. Use this when pure semantic understanding is insufficient, and precise matching of specific terms (like names or codes) is necessary.

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 reference architecture for implementing large-scale AI image generation using Ideogram. This system guides developers through building robust pipelines, including structured prompt templating (for brand consistency), utilizing multiple API endpoints (Generate, Edit, Remix), and implementing full asset workflow management from generation to final CDN delivery. Ideal for establishing brand asset systems and scalable AI integrations.

This guide details best practices for securing Ideogram API integrations. It covers essential steps like using environment variables for key storage, implementing key rotation procedures, establishing server-side proxies to prevent key exposure, and sanitizing prompts to mitigate data leaks. Use this when setting up, maintaining, or auditing API security infrastructure.

This guide outlines the process of migrating codebase dependencies and logic when upgrading the Ideogram API from legacy versions (V1/V2) to the robust V3 endpoints. It addresses critical breaking changes, including the shift from JSON body to multipart/form-data, changes in model naming, aspect ratio syntax, and the integration of new V3 features like rendering speed and style presets. Provides structured code adapters for smooth transition.

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.