Skill UI

Guides learners through reconnaissance, scanning, vulnerability analysis, exploitation, and reporting phases of authorized penetration testing, pairing command examples with tool choices and professional deliverables.

Structured checklist guiding the planning, scoping, environment prep, tester selection, and reporting phases of penetration tests to keep security assessments thorough and compliant.

This skill provides robust mechanisms to verify the integrity of AI agent plugins, tools, and dependencies. It generates deterministic SHA-256 manifests (INTEGRITY.json) for all components, allowing users to detect unauthorized modifications, track provenance, and ensure that deployed assets match their published versions. Use this during CI/CD pipelines, code review, and pre-production promotion to secure the entire agent ecosystem.

This comprehensive tool provides robust automation capabilities for Airtable using the Rube MCP framework. It allows users to perform full CRUD operations (Create, Read, Update, Delete) on records, bases, and tables. Key workflows include searching and filtering records using complex formulas, managing field schemas, and handling comments, significantly streamlining data management and workflow automation.

This skill generates deep, clickable URLs to various resources within the Arize monitoring UI. It supports linking to specific traces, spans, sessions, datasets, evaluators, and annotation configurations. It is essential for sharing specific debugging artifacts or navigating directly to key data points within the MLOps platform by requiring precise resource IDs and time ranges.

This toolset provides comprehensive automation for Cal.com scheduling operations through Rube MCP. It enables users to manage the entire booking lifecycle, including listing and creating bookings, checking real-time availability and finding open slots, configuring and managing webhooks for event triggers, and managing organizational teams. It is essential for integrating scheduling workflows into larger automation processes.

This toolkit provides comprehensive automated control over CircleCI CI/CD pipelines via Rube MCP. Users can trigger new builds, monitor workflow and job statuses, retrieve detailed job information, download build artifacts, and extract detailed test metadata. It streamlines complex DevOps operations by managing the entire CI/CD lifecycle.

This workflow guides developers through generating standardized, descriptive commit messages using the Conventional Commits specification. It provides a structured XML template (including type, scope, description, body, and footer) and integrates directly into the Git workflow, ensuring project history is clean, traceable, and machine-readable. Ideal for maintaining large, collaborative codebases.

Copilot Spaces allow users to consolidate and manage project-specific knowledge, including documentation, code snippets, architectural standards, and operational instructions. By loading a Space, Copilot grounds its responses not just on general knowledge, but on the curated, authoritative context of the entire project, enabling accurate Q&A, code generation, and workflow execution based on team standards. Ideal for onboarding, large-scale projects, and maintaining consistency.

This skill is designed to retrieve and display detailed usage metrics for GitHub Copilot within organizations and enterprises. Users can analyze adoption rates, total suggestions, acceptance rates, and chat interactions, broken down either by the entire organization/enterprise or on a per-user basis. It supports querying data for specific historical dates using GitHub CLI and REST API.

This tool analyzes specification files to extract all defined requirements and cross-references them with the current codebase implementation status. It systematically checks for unimplemented features, searches existing GitHub issues to prevent duplicates, and automatically generates detailed issues using a standardized feature request template. It is essential for robust product management, ensuring every defined requirement is tracked and scheduled for development.

This guide provides a detailed template and directive for generating machine-readable, deterministic implementation plans. It is designed for complex software development tasks, such as adding new features, refactoring existing code, or designing system architecture. The output ensures that all steps are atomic, measurable, and structured for autonomous execution by AI agents or human teams, minimizing ambiguity and dependency.