Skill UI

Extracts business domain knowledge from a codebase, optionally reusing an existing knowledge graph, and generates an interactive horizontal flow graph for dashboard visualization, with lightweight scanning and validation steps.

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 provides a robust system for tracking all code modifications using structured JSON records and enforcing a defined state machine (e.g., planned -> deployed). It is critical for AI coding workflows, ensuring that if a session expires or is abandoned, the next session receives the full context, progress summary, and blockers to resume seamlessly. Ideal for complex, multi-stage development projects and onboarding new codebases.

Generates professional documentation for software projects, covering READMEs, API references, architecture guides, inline comments, and changelogs, adapting style and scope to the codebase and user request.

Guides recording architecture decision records (ADRs), inline comments, and API docs. Captures the why behind design choices, alternatives considered, and trade-offs so future engineers and agents can understand the codebase.

A comprehensive guide and skill for generating and auditing high-quality technical documentation for Go projects. It covers writing accurate godoc comments, READMEs, CONTRIBUTING, and CHANGELOGs for both libraries and CLIs, adhering to professional best practices. Supports multi-agent orchestration for large-scale codebases.

A comprehensive guide to achieving high code quality in Go projects using `golangci-lint`. This skill covers the entire development lifecycle, including setting up the essential `.golangci.yml` configuration, running automated linters (style, security, complexity), automatically fixing issues, interpreting detailed lint output, and correctly suppressing false positives using `//nolint` directives. Ideal for enforcing best practices in CI/CD pipelines and maintaining legacy codebases.

This skill acts as a comprehensive Go modernization engineer, scanning entire codebases to update outdated patterns, deprecated APIs, and standard library usage. It utilizes multi-agent orchestration to check language features, testing patterns, and tooling/infra, ensuring the codebase adheres to the latest Go idioms for maximum safety and readability. Ideal for CI/CD pipelines or large-scale code reviews.

A comprehensive guide and skill set for implementing dependency injection in Go using the samber/do toolkit. It covers core concepts like defining services (Lazy, Eager, Transient), managing service lifetimes, handling dependencies via provider functions, and organizing large codebases using package-level injection.

This tool generates a comprehensive context map of a codebase before making any modifications. It guides developers to systematically analyze all relevant files, dependencies, existing tests, and common patterns. Use it to assess the full scope of a task, identify potential breaking changes, and ensure a robust and stable development cycle.

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.

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.