Explorar skills

AI Skills for Reaviz Projects

Python type checking expertise using ty - the extremely fast type checker by Astral. Use when: (1) Adding type annotations to Python code, (2) Fixing type errors reported by ty, (3) Migrating from mypy/pyright to ty, (4) Configuring ty for projects, (5) Understanding advanced type patterns (generics, protocols, intersection types), (6) Setting up ty in editors (VS Code, Cursor, Neovim, PyCharm).

When you or the user are going in circles, stuck on a problem, or repeating failed approaches. Use when the user says "I'm stuck," "this isn't working," "we keep going in circles," "try something different," "nothing works," "help," or when you detect that you've attempted the same category of solution 2+ times without success. Forces a structured step-back, reframe, and fresh approach.

AI Skills for Reaviz Projects

Automate Accelo tasks via Rube MCP (Composio). Always search tools first for current schemas.

Use when writing libGDX Java/Kotlin code involving 3D rendering — ModelBatch, ModelInstance, Model loading (G3DJ/G3DB/OBJ), ModelBuilder procedural meshes, Environment and lighting (DirectionalLight/PointLight), PerspectiveCamera, Materials and Attributes (ColorAttribute/TextureAttribute/BlendingAttribute), AnimationController, or camera controllers (CameraInputController/FirstPersonCameraControll

Automate Ragic tasks via Rube MCP (Composio). Always search tools first for current schemas.

Review someone else's PR as a code reviewer: read the PR diff, check against .claude/rules, leave inline comments on issues found, and submit a review with APPROVE or REQUEST_CHANGES. Use when the user asks the assistant to review a PR (subject omitted or = self), e.g.: "review PR", "review 這個 PR", "review 此 PR", "review 該 PR", "幫我 review 這個 PR" (without team subject), "review for me", "code revie

Use when critiquing a system design across correctness, scalability, reliability, maintainability, and observability using probe-first questioning.

Automate Gatherup tasks via Rube MCP (Composio). Always search tools first for current schemas.

Multi-session autonomous agent runner with progress checkpointing, failure recovery, and task dependency management. Uses a controller + sub-agent architecture: the main agent orchestrates state while sub-agents execute tasks in parallel via worktrees. Triggers on '/lp:run' command, or when a task involves many subtasks needing progress persistence, sleep/resume cycles across context windows, reco

Automate Fomo tasks via Rube MCP (Composio). Always search tools first for current schemas.