Skill UI

Build sophisticated, event-driven automations using Granola's data triggers via Zapier webhooks. This guide details the event model, payload structure, and advanced filtering patterns. Implement custom handlers in JavaScript or Python to process meeting data, route based on attendees, or automatically update external systems like CRMs and task managers.

This guide details a production-ready reference architecture for applications built on Groq's LPU inference API. It covers sophisticated model routing based on latency, quality, or cost needs, implementing streaming pipelines, and establishing robust multi-provider fallback chains (e.g., Groq primary to OpenAI backup). Ideal for designing and reviewing complex, resilient LLM systems.

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.

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.

This workflow executes the primary Ideogram API calls for advanced text-to-image generation. Ideogram excels at rendering legible text within images, a crucial capability for creating realistic signs, menus, or branding elements. Use this for generating high-quality social media graphics, marketing banners, product mockups, and posters that require accurate and stylized typography combined with illustration.

LitGPT provides clean, readable, and production-ready implementations for over 20 state-of-the-art LLMs (including Llama, Gemma, Phi, Mistral). It supports comprehensive workflows, including full fine-tuning, efficient LoRA/QLoRA adaptation, and pretraining from scratch. Ideal for developers needing academic understanding or robust, deployable model architectures.

This skill outlines a comprehensive, multi-agent orchestration workflow designed for sophisticated production issue resolution. It systematically combines AI code assistants, observability platforms (like Sentry/DataDog), and automated techniques (e.g., git bisect, distributed tracing) into a rigorous four-phase process: Issue Analysis, Root Cause Investigation, Fix Implementation, and Verification. It guides best practices for reducing Mean Time To Recovery (MTTR) and improving system resilience in complex, multi-system environments.

Automated guidance for generating infographic outlines, applying best practices across diagrams, charts, presentations, and visual documentation, with checks to keep outputs production-ready.

A comprehensive set of production-ready client patterns for integrating with the Instantly.ai API v2 using TypeScript and Python. It provides robust solutions for managing API interactions, including type safety, sophisticated retry logic, pagination handling, and multi-tenant support, essential when building reliable, reusable wrappers without an official SDK.

This sophisticated skill automates the entire Pull Request (PR) quality assurance lifecycle. It systematically fetches and categorizes CI check failures and detailed review feedback using the LOGAF priority scale. The workflow guides users through root cause analysis, proposing minimal, targeted fixes, replying to reviewers, and committing updates iteratively until all checks pass, ensuring high code quality before merging.

This advanced workflow enables users to perform deep analyses on large-scale people intelligence datasets. Users can build custom queries with multi-dimensional filters, run comparisons across different candidate pools (e.g., Q1 vs Q4), and aggregate skill density by geographical region. It is essential for talent acquisition teams needing to identify market trends and optimize hiring strategies beyond standard search functions.

This guide details how to apply sophisticated artistic styles and visual effects to Kling AI video generation. Users can achieve diverse aesthetics—such as Cinematic, Anime, Watercolor, or Cyberpunk—either through detailed prompt engineering or by utilizing the dedicated Effects API (e.g., hug, kiss). It also provides methods for pre-processing images using Kolors for highly consistent and professional video outputs.