Skill UI

This tool provides an end-to-end workflow for managing massive codebase migrations, framework upgrades, and structural refactors across hundreds of files. It uses a specialized CLI to orchestrate issue tracking, create reviewable PR batches, and verify CI status, ensuring complex changes are implemented safely and incrementally.

An internal tool designed to validate candidate meta-skills (SKILL.md) before they are registered in the system. It performs comprehensive linting checks, including structural validation (G1: parsing, reference checks, XML escaping) and a scheduler dry-run (G2) using stub executors, ensuring the skill is deterministic and functional. Output diagnostics in JSON format.

An internal, non-user-invocable tool designed to validate candidate meta-skills. It runs critical G3 (positive) and G4 (negative) smoke tests by simulating meta-resolution using LLM-generated fixtures. This ensures the structural integrity and robustness of the skill in a cross-vendor environment.

This module provides a comprehensive catalog of abstractions and utilities for handling API webhooks within the Webiny framework. It covers essential components such as payload types (IWebhookPayload), domain models (Webhook), delivery mechanisms, and core services like WebhookDispatcher and WebhookFactory. It supports advanced features including event routing, data validation, and secure payload signing, making it ideal for backend integration development.

This guide details the use of Deneb, a certified custom visual, to embed Vega and Vega-Lite declarative visualization specifications directly into Power BI reports (PBIR). It outlines the complete workflow, from data binding and spec authoring to injection and validation using the pbir CLI. It emphasizes best practices, such as preferring Vega-Lite and handling complex field name escaping for robust report mutation.

This skill guides the design, enforcement, auditing, and validation of Power BI report themes using the specialized pbir CLI. It helps standardize formatting—including colors, fonts, and structural properties—to ensure consistency, improve rebrandability, and maintain theme compliance across complex reports, minimizing reliance on local visual overrides.

The pbir CLI is a comprehensive tool for exploring, building, managing, formatting, and validating Power BI reports. It allows developers to interact with Power BI files (.pbir, .pbix, .pbip) programmatically, covering everything from structural inspection and data model querying to visual generation and publishing to Fabric. It guides users through best practices, emphasizing iterative development and explicit validation.

Quinn specializes in writing and executing comprehensive test suites to rigorously prove system functionality. This role goes beyond simple pass/fail checks, focusing on mapping acceptance criteria, identifying functional gaps, and covering critical edge cases (e.g., nulls, boundary values, error paths). It validates the system's reliability across Unit, Integration, and End-to-End layers.

This skill provides a deterministic, git-only method to verify claims made by AI agents (e.g., 'done', 'shipped', 'fixed'). Instead of trusting the agent's self-report, it audits the commit's diff and git history using the DOS kernel (`dos verify`, `dos commit-audit`) to confirm if the claimed change genuinely occurred and is backed by non-forgeable evidence. It acts as a critical quality gate.

A detailed, comprehensive reference guide covering best practices for securing modern applications. This checklist spans network architecture, API design, data encryption, authentication protocols, and regulatory compliance (GDPR, HIPAA, PCI-DSS), ensuring robust security across the entire technology stack.

This skill applies a rigorous, evidence-first discipline to coding tasks, inspired by Fable-like best practices. It guides agents through a structured workflow: inspecting the workspace, tracking goals and findings, grounding all conclusions in verifiable evidence, and executing thorough verification gates before declaring completion. Ideal for complex development, debugging, or adapting cross-model prompt guidance into robust, verifiable project rules.

A comprehensive playbook for optimizing the entire lifecycle of pull requests. It guides developers through systematic pre-flight cleanup, critical self-audits, local test verification, and structuring high-signal PR descriptions to ensure code quality and fast maintainer approval.