Skill UI

Transforms repo structure and commit history into two actionable markdowns—an architecture summary and a narrative story—so analysts can trace system intent, data flow, and team evolution.

Maintains the repository's llms.txt guidance file by auditing current documentation, specs, and structure to ensure the navigation summary matches reality and stays compliant with the official specification.

This skill provides comprehensive tools and methodologies for generating OpenAPI/Swagger documentation within Go projects. By utilizing specialized annotation comments (@Summary, @Param, @Success, etc.), developers can treat their code as a self-documenting contract. It supports integrating with various popular Go frameworks (Gin, Echo, Fiber) and handles complex features like security definitions (JWT, OAuth2) and custom type tagging, ensuring the Swagger UI is always the authoritative source of truth for API consumers.

This skill provides comprehensive code reviews, helping users assess code quality, identify various potential issues (syntax, logic, security, performance), and receive actionable suggestions for improvement. It generates a detailed, structured report covering a summary, found issues, and quality metrics.

Transforms an exported JSON list of open pull requests into a structured, blockers-first digest. Ideal for standup meetings or triage sessions, this tool identifies which PRs are blocked (due to failing checks, required changes, or staleness) and which are ready to merge, providing a concise summary count for quick status updates.

This tool generates comprehensive weekly telemetry reports for the Azure Backup MCP toolset. It queries live production data from Kusto, performing advanced error analysis and classifying failures into three categories: Customer error, Azure Service failure, or MCP Tool Bug. The report correlates usage metrics with merged PRs and releases, producing an Outlook-compatible HTML summary for assessing tool health and stability.

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 skill automates the creation of high-quality, structured pull request descriptions. By analyzing git diffs, commit lists, or raw changes, it generates comprehensive sections covering the summary, motivation, specific changes, detailed testing procedures, and crucial reviewer guidance. Use it to ensure every code change is fully documented for effective peer review.

Workthreads analyzes a team's coding history across multiple repositories to generate a structured weekly status report. It clusters raw logs into 'work threads' and automatically tags their lifecycle status (new, open loops, closed, reverted). This is essential for leads needing a high-level, actionable summary of project progress, outstanding tasks, and completed features without reading thousands of lines of raw activity.