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Found 17 Skills
SOLID principles for clean code design and architecture
Holistic, system-aware planning before implementing non-trivial tasks. Use when the task involves new features, architectural decisions, multi-file changes, unclear requirements, or multiple valid approaches. Triggers on "/plan", "plan this", "design an approach", "let's plan first".
Invoke IMMEDIATELY via python script when user requests codebase understanding, architecture comprehension, or repository orientation. Do NOT explore first - the script orchestrates exploration.
Maps and documents codebases of any size by orchestrating parallel subagents. Creates docs/CODEBASE_MAP.md with architecture, file purposes, dependencies, and navigation guides. Updates CLAUDE.md with a summary. Use when user says "map this codebase", "cartographer", "/cartographer", "create codebase map", "document the architecture", "understand this codebase", or when onboarding to a new project. Automatically detects if map exists and updates only changed sections.
Generates Mermaid diagrams from Trailmark code graphs. Produces call graphs, class hierarchies, module dependency maps, containment diagrams, complexity heatmaps, and attack surface data flow visualizations. Use when visualizing code architecture, drawing call graphs, generating class diagrams, creating dependency maps, producing complexity heatmaps, or visualizing data flow and attack surface paths as Mermaid diagrams.
Deep analysis of GitHub repositories to understand their core architecture, design philosophy, technical decisions, and implementation patterns. This skill should be used when users provide a GitHub URL and request comprehensive understanding of the repository's structure, purpose, key abstractions, or technical approach.
Use ONLY when creating NEW registrable components in ML projects that require Factory/Registry patterns. ✅ USE when: - Creating a new Dataset class (needs @register_dataset) - Creating a new Model class (needs @register_model) - Creating a new module directory with __init__.py factory - Initializing a new ML project structure from scratch - Adding new component types (Augmentation, CollateFunction, Metrics) ❌ DO NOT USE when: - Modifying existing functions or methods - Fixing bugs in existing code - Adding helper functions or utilities - Refactoring without adding new registrable components - Simple code changes to a single file - Modifying configuration files - Reading or understanding existing code Key indicator: Does the task require @register_* decorator or Factory pattern? If no, skip this skill.
Analyze the source code of GitHub open-source repositories and generate structured analysis reports. Supports generating reports such as project architecture overview, code quality analysis, core module description, etc., and optional synchronization to Notion.
Use during implementation when designing modules, functions, and components requiring SOLID principles for maintainable, flexible architecture.
Senior code review pass. Use PROACTIVELY as the FINAL task after code changes. Reviews against project rules, fixes issues, runs quality gates. Focuses on logic and architecture while delegating style to automation.
Review an existing game codebase for architecture, performance, and best practices
Staff-level codebase health review. Finds monolithic modules, silent failures, type safety gaps, test coverage holes, and LLM-friendliness issues.