Skill UI

This guide details how to build automated threat intelligence enrichment pipelines within Splunk Enterprise Security. By leveraging the Threat Intelligence Framework, users can ingest, normalize, and correlate Indicators of Compromise (IOCs) from diverse external sources (such as TAXII, CSV, and custom APIs). The process uses KV Store collections and lookup searches to enrich raw security events with critical threat context, significantly reducing triage time for SOC teams.

A comprehensive set of specialized tools for deep interaction with source codebases. This context-mode is mandatory for advanced tasks such as running code snippets, analyzing files, batch processing repository commands, indexing knowledge, searching content, and fetching web data. It ensures that interactions are context-aware and highly efficient, moving beyond basic file listing or general chat prompts.

This skill is designed for professional workflow engineering using the n8n platform. It guides the user through the entire lifecycle, including creating, editing, validating, synchronizing (push/pull), and troubleshooting complex workflows. It strictly enforces context-root protocols, adheres to sync discipline, and requires using schema-first research to ensure technical accuracy, making it ideal for advanced automation development.

This skill provides an interactive, guided onboarding tour for the Context-Matic MCP server. It addresses the challenge of general AI models relying on outdated or incorrect public code by acting as a live, version-aware grounding layer. The tour walks users through the server's core function, demonstrates key tools (like fetching APIs, searching models, and finding endpoints), and guides them through selecting and exploring available APIs for their specific project language.

This skill analyzes the implementation gap by comparing approved feature requirements against the existing codebase, architecture, and context. It helps identify missing capabilities, potential integration challenges, and necessary technical research areas. The output provides multiple viable implementation options and a comprehensive analysis report, guiding the transition from requirements definition to technical design.

This skill automates the process of transforming high-level product specifications, requirements, and design documents into a detailed, actionable, and executable task plan. It follows a multi-stage workflow, including context loading, parallel research, and two rigorous review gates (Task Plan Review and Task-Graph Sanity Review). The output provides properly sized (1-3 hours), logically sequenced tasks, ensuring every requirement is covered and dependencies are explicitly managed, dramatically improving project planning accuracy.

A comprehensive tool for searching the Model Context Protocol (MCP) across various GitHub locations, including PRs, issues, and discussions. It allows users to track the full lifecycle of protocol specifications, from initial proposals to final merged changes. Furthermore, it facilitates deep dives into pull request reviews and comments, enabling the extraction of key maintainer rationales and design intent for accurate technical understanding.

This module provides multiple standardized abstractions for interacting with the OpenSearch API. It includes dedicated abstractions for clients, factories, and operational contexts, allowing developers to implement robust, scalable, and type-safe interactions with OpenSearch within the webiny ecosystem. Use these patterns to ensure consistent data access regardless of the specific usage pattern.

A comprehensive guide to implementing schema.org structured data using JSON-LD format. Learn to correctly identify page types (Product, Article, Organization, FAQPage) and apply the necessary schema markup to help search engines understand content context. This skill covers initial assessment, core principles (accuracy, validation), and optimizing for rich results like star ratings, site search blocks, and rich snippets, significantly boosting search engine visibility and CTR.

This skill generates robust JSON-LD structured data markup for various web components, including blogs, FAQs, tools, and SaaS pages. By implementing standard Schema.org types (WebSite, Article, FAQPage, etc.), you can significantly improve your SEO, boost click-through rates (CTR), and provide clear context to both search engines and AI systems. Includes implementation guidance for modern frameworks like Next.js.