Desenvolvimento

Checks Java code for SOLID principles violations with Java-specific patterns. Use when user asks to "check SOLID principles", "is this good OOP", "single responsibility", "SOLID violations", "open closed principle", or "dependency inversion".

Comprehensive interview for planning new features or changes. Use when the user wants thorough upfront planning before implementation, or when starting work on a complex feature.

Call x-callback-url schemes from the CLI synchronously. Use when invoking macOS app URL schemes (Things, Bear, OmniFocus, etc.).

Reviews Java code for thread safety, race conditions, deadlocks, and Java 21 virtual thread compatibility. Use when user asks to "review concurrency", "is this thread safe", "check for race conditions", "concurrency issues", or "virtual thread compatible".

Generates JUnit 5 and Mockito unit tests or Testcontainers integration tests, auto-detecting project setup. Use when user asks to "write tests", "generate tests", "add unit tests", "create test class", "test this service", or "write integration tests".

Turn a bug symptom into a fix with a regression test that locks it down. If the user opens vague ("there's a bug", "/diagnose"), interview them one question at a time until you have enough to attempt a reproduction; if you still cannot reproduce, say so explicitly. Then drive the work through five phases — build a deterministic feedback loop, reproduce, hypothesise, probe, write a spec — and hand

Pomodoro — focus timer with music (alias for /focus)

Reviews Java REST API design including HTTP methods, status codes, naming, and versioning. Use when user asks to "review my API", "check REST design", "is this good REST", "review endpoints", "API design review", "check my controller", or "review HTTP API".

Play music — start or switch genre/station

Comprehensive toolkit for managing large Claude Code skill collections including bulk downloading from GitHub, organizing into categories, detecting and removing duplicates, consolidating skills, and maintaining clean skill repositories with 100+ skills.

Model interpretability and explainability using SHAP (SHapley Additive exPlanations). Use this skill when explaining machine learning model predictions, computing feature importance, generating SHAP plots (waterfall, beeswarm, bar, scatter, force, heatmap), debugging models, analyzing model bias or fairness, comparing models, or implementing explainable AI. Works with tree-based models (XGBoost, L

Mood — tell the DJ how you're feeling and it picks the right music