Scripting

Write vanilla JavaScript for Web Components with functional core, imperative shell. Use when creating JavaScript files, building interactive components, or writing any client-side code.

Store project-specific insights and context into file-based memory. Use after completing tasks that reveal important details about THIS codebase. Use when user says "--project-store" or "--learn" (you decide which scope, may use both) or after discovering project-specific patterns. Skip for universal patterns (use coder-memory-store) or routine work.

Determines project type from context to configure analysis thresholds.Checks prompt, scans documents, or asks user if type cannot be inferred.Outputs project_type for use by python-plan-optimization skill.

Sets up comprehensive GitHub Actions CI/CD workflows for modern web applications. This skill should be used when configuring automated lint, test, build, and deploy pipelines, adding preview URL comments on pull requests, or optimizing workflow caching. Use when setting up continuous integration, deployment automation, GitHub Actions, CI/CD pipeline, preview deployments, or workflow optimization.

Create parametric 3D models using OpenSCAD, a script-based solid CAD modeler. Use when the user asks to create 3D printable objects, parametric designs, mechanical parts, CAD models, or requests .scad files. OpenSCAD uses constructive solid geometry (CSG) and extrusion of 2D shapes to create 3D models through code.

Comprehensive GitHub Pull Request code review skill. This skill should be used when users provide a GitHub PR URL and request a code review. Automatically fetches PR metadata, diff, comments, commits, and related issues using gh CLI. Creates organized review workspace, analyzes code against industry-standard criteria (functionality, security, testing, maintainability), and optionally adds inline comments to the PR. Trigger phrases include review this PR, code review, review pull request, check this PR, or when a GitHub PR URL is provided.

Comprehensive multi-AI code review system for Python, JavaScript, and TypeScript. Use when reviewing code for quality, security, performance, or best practices. Includes automated analysis scripts, language-specific patterns, and AI collaboration workflows for complex decisions.

WHEN: Machine Learning/Deep Learning code review, PyTorch/TensorFlow patterns, Model training optimization, MLOps checksWHAT: Model architecture review + Training patterns + Data pipeline checks + GPU optimization + Experiment trackingWHEN NOT: Data analysis only → python-data-reviewer, General Python → python-reviewer

Implement, refactor, or review worker-based multithreading in TypeScript/JavaScript apps (browser or Node). Use when offloading CPU-heavy loops to Web Workers, setting up a worker pool, moving data across threads, or diagnosing worker crashes, slowdowns, or synchronization bugs.

Python SDKとFastMCPフレームワークを使用したModel Context Protocol (MCP) サーバー構築のガイド。PythonベースのMCPサーバーの作成、デバッグ、最適化を行う際に使用してください。

Detect and clean redundant code in Python and TypeScript projects.Finds unused imports, dead functions, stale comments, debug statements,and unused dependencies. Use when asked to "clean code", "find dead code","remove unused imports", "check redundant code", or "清理代码".

Generate Pictionary drawing cards using AI (Groq) with fallback to hardcoded libraries. Use when creating new game cards, implementing category-based card selection, or handling AI card generation with graceful degradation.

Use when working with Ruby's object-oriented programming features including classes, modules, inheritance, mixins, and method visibility.

Browser automation scripts for testing, screenshots, and web interaction. 16 scripts with persistent state.

Creating new Claude Code skills for StickerNest. Use when the user asks to create a skill, build a skill, add a new skill, make a Claude skill, or extend Claude's capabilities for this project. Covers skill structure, YAML frontmatter, trigger-focused descriptions, and StickerNest-specific skill patterns.

Generate POSIX shell scripts following UNIX programming principles and a rigorous coding style. Use when: (1) creating or updating shell scripts; (2) when working on .sh files; (3) when working on files with #!/bin/sh shebang lines. Do not use when: (1) asked to create a Bash script.

Generate and run unit and integration tests using pytest (Python) or Jest (JavaScript) with fixtures, mocks, and async support. Use for test-driven development, code review validation, coverage verification, and regression testing. Target 80%+ code coverage. Supports pytest markers, Jest snapshots, and CI/CD integration. Triggers on "test", "TDD", "unit test", "integration test", "test coverage", "pytest", "jest".

Generate slide decks, audio podcasts, infographics, and video overviews from NotebookLM notebooks. Customizable by audience, format, language (80+), orientation, and visual themes. Use when asked to generate slides, create podcast, make infographic, video overview, or automate NotebookLM content creation.

Bidirectional markdown ↔ SQLite conversion with column limit protection and smart section extraction. Import with Python, query with sqlite3.

This skill should be used when fixing bugs, implementing features, debugging issues, or making code changes. Ensures understanding of code flow before implementation by: (1) Tracing execution path with specific file:line references, (2) Creating lightweight text diagrams showing class.method() flows, (3) Verifying understanding with user. Prevents wasted effort from assumptions or guessing. Triggers when users request: bug fixes, feature implementations, refactoring, TDD cycles, debugging, code analysis.