Skill UI

A meta-skill designed to monitor long-running processes, such as model fine-tunes or CI builds, executed within a detached tmux session. It captures output, automatically uses a sub-agent to diagnose failures, proposes a fix, and records the complete debugging process to memory. Ideal for intermittent failure debugging and continuous integration pipelines.

This meta-skill provides a comprehensive, step-by-step plan for complex software migrations. It intelligently coordinates multiple steps, including gathering migration requirements, classifying the source and target stacks (e.g., CJS to ESM, Py2 to Py3), searching authoritative guides, and analyzing repository diffs to ensure a guided, reliable upgrade path for large-scale projects.

This meta-skill automates the complex process of modernizing legacy PDF documents (e.g., historical contracts, scanned manuals, legal documents). It follows a structured four-step pipeline: structural extraction, natural-language rewriting of problem pages, generating an audit summary, and finally re-merging the content into a single, refined PDF. This ensures content is modernized while maintaining fidelity to the original meaning, providing a human review summary before finalization.

This meta-skill implements a combinator pattern for deep security analysis. It runs three independent gates—policy governance, secret scanning, and audit logging—over a candidate operation. It enforces a strict arbitration rule (Policy DENY > Scanner WARN > ALLOW) to provide a robust, multi-layered verdict, making it ideal for reviewing critical code changes or environment modifications for safety compliance.

A meta-skill designed to generate comprehensive and detailed travel itineraries and schedules. It intelligently orchestrates multiple steps, including extracting user preferences, checking local weather, searching Points of Interest (POI), and identifying practical time constraints (like opening hours and transit times). This ensures the final output is highly actionable, whether for a leisure trip or a business journey.

This tool assists researchers in structuring academic papers by mapping specific claims across different sections (Introduction, Method, Results, Discussion) to required external citations (BibTeX keys). It enforces citation density rules and ensures the correct role alignment (e.g., background, comparison, limitation) before the actual drafting process, guaranteeing that every core claim is properly supported and distributed.

This tool acts as a pre-drafting planning mechanism for academic or technical writing. It analyzes the user's request to extract and structure detailed preferences, such as target audience, citation style, depth, and desired emphasis. It determines the optimal generation mode (direct or preference-driven) before any writing or research takes place, ensuring all required criteria are met systematically.

Provides comprehensive, programmatic control over tmux sessions. Users can list, capture output from, send specific keystrokes, and programmatically navigate panes/windows in remote, long-running interactive CLI sessions. Essential for monitoring AI code generation tools (like Claude/Codex) or managing complex multi-terminal workflows via scripting.

Unship is a dedicated local workflow for front-end developers to compare multiple AI-generated UI alternatives (such as layouts, copy, or flows) directly within a running application environment. Instead of committing to one generated version, it adds temporary source-level variants, allowing for visual comparison. After the user selects the final version, the skill automatically cleans up all unused temporary code and attributes, ensuring a clean, production-ready codebase. Note: This tool is for local iteration only, not for production A/B testing or analytics.

Provides expert guidance for connecting to a local Power BI Desktop tabular model using PowerShell's Tabular Object Model (TOM) and ADOMD.NET. This skill enables model enumeration, executing complex DAX queries, modifying metadata (fields, measures, parameters), and managing the report canvas state via the Desktop Bridge. It is critical for direct model interaction when external CLIs are unavailable.

This tool traces the entire downstream dependency chain from a core semantic model to all connected reports and assets across multiple Fabric workspaces. Use it for crucial impact analysis before modifications, auditing model usage, or mapping cross-workspace data dependencies. It helps data stakeholders understand the full scope of influence a model has on the reporting layer.

This guide details the principles of observability, teaching developers how to instrument code by implementing structured logging, metrics, and distributed tracing. It ensures that production features emit sufficient telemetry to answer complex operational questions, transforming unknown failures into diagnosable events. Essential for any service running in production.